Patent Publication Number: US-2022235798-A1

Title: Electric powered work machine and method of controlling noise generated by electric powered work machine

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of Japanese Patent Application No. 2021-011309 filed on Jan. 27, 2021 with the Japan Patent Office, the entire disclosure of which is incorporated herein by reference. 
     BACKGROUND 
     The present disclosure relates to noise control in an electric powered work machine. 
     Japanese Patent Application Publication No. H6-508695 discloses active noise control (ANC) being applied to noise reduction of electric powered work machines. 
     ANC is a technique to cancel a noise, which is generated from a noise source, with a control sound. The noise is measured by a first microphone. The control sound is emitted from a speaker. The control sound is produced based on the noise measured by the first microphone. The control sound is produced at a location where the noise needs to be canceled (hereinafter simply referred to as “canceling location”), having an inverted phase of the noise. The control sound is produced by an adaptive filter. Characteristics of the adaptive filter are sequentially calculated in accordance with, for example, an adaptive algorithm. Examples of the adaptive algorithm may include Filtered-X algorithm or Normalized Least Mean Square (NLMS) algorithm. 
     In addition to the adaptive filter, ANC uses a second order system filter. In the second order system filter, characteristics of a second order system are modeled. The second order system corresponds to a path from a speaker to a second microphone that detects an error. The adaptive filter and the second order system filter are digital filters. Each of these digital filters has a certain number of taps (for example, in a range of several hundreds of taps) based on the length of time necessary for its impulse response to sufficiently converge. 
     SUMMARY 
     It is difficult to use ANC without a computer with a high computing processing capability. Adaptive algorithm calculations require an enormous amount of processing. The calculations need to be completed within a period sufficiently shorter than the time for the noise detected by the first microphone to propagate and arrive at the canceling location. 
     It is desirable that one aspect of the present disclosure provides a technique to reduce the amount of computing processing necessary for reducing a noise of an electric powered work machines. 
     An electric powered work machine according to one aspect of the present disclosure includes a motor. The motor generates a driving force necessary for performing a jobsite work. Examples of the jobsite work includes work at do-it-yourself carpentry, manufacturing, gardening, and construction sites. 
     The electric powered work machine includes a reference acquirer. The reference acquirer acquires a reference signal. The reference signal has a correlation with a target noise. The target noise corresponds to a noise generated due to operation of the motor. 
     The electric powered work machine includes a first digital filter (or noise control filter). The first digital filter includes a series of taps. Each tap of the series of taps has an adjustable coefficient. The first digital filter is configured to (i) receive the reference signal from the reference acquirer and (ii) generate a control signal to cancel or attenuate the target noise. 
     The electric powered work machine includes a control sound source (or control source, or secondary source, or secondary sound source, or control loudspeaker, or secondary loudspeaker). The control sound source produces an artificial noise (or canceling sound, or attenuating sound, or secondary sound, or canceling acoustic signal, or attenuating acoustic signal, or secondary signal) in accordance with the control signal. 
     The electric powered work machine includes an error sensor. The error sensor converts a synthesized sound at a given canceling location (or a given attenuating location) to an error signal. The synthesized sound corresponds to a combined sound of the artificial noise and the target noise at the canceling location. The error sensor may be configured to detect (or acquire) the synthesized sound. The error signal may digitally indicate the synthesized sound detected by the error sensor. 
     The electric powered work machine includes a second digital filter (or second order system filter). The second digital filter includes transfer characteristics of a second order system. The second order system corresponds to a path from the control sound source to the error sensor. In other words, in the second digital filter, the second order system is modeled. That is, the second digital filter includes transfer characteristics that are the same as (or almost the same as, or similar to) actual transfer characteristics (or a response) of the second order system. The second digital filter includes N taps. The second digital filter (i) receives the reference signal from the reference acquirer and (ii) generates a filtered reference signal. 
     The electric powered work machine includes a characteristics adjustor. The characteristics adjustor adjusts (or updates) the adjustable coefficient of each tap of M taps in the series of taps in accordance with an adaptive algorithm. The adaptive algorithm uses the error signal and the filtered reference signal. The M taps may be any number of taps in the series of taps. Each of M and N is a positive integer satisfying M&lt;N. The any number of taps may include all taps in the series of taps. 
     Such a configuration can reduce the number of taps of the first digital filter, while inhibiting divergence of the first digital filter. As a result, it is possible to reduce the amount of the computing processing for the adaptive algorithm. 
     M taps may correspond to all taps of the series of taps. The characteristics adjustor may update the adjustable coefficient for all taps of the M taps. 
     The electric powered work machine may include a divergence determiner. The divergence determiner may determine whether the first digital filter indicates a divergence tendency. The characteristics adjustor may update the adjustable coefficient of each tap of L taps in the series of taps prior to a determination, by the divergence determiner, that the first digital filter indicates a divergence tendency. The characteristics adjustor may set the adjustable coefficient of each tap of an M+1 th  tap and subsequent taps in the series of taps to a given value and update the adjustable coefficient of each tap of 1 st  to M th  taps in the series of taps, in response to a determination, by the divergence determiner, that the first digital filter indicates a divergence tendency. L taps may correspond to all taps of the series of taps. L may be a positive integer satisfying L≥N. 
     The given value may be a coefficient of a corresponding tap in an imaginary digital filter. The imaginary digital filter may include characteristics obtained by multiplying an impulse response of a first order system by characteristics of a reverse filter of the second order system filter. The first order system corresponds to a path from the motor to the error sensor. Multiplying the impulse response of the first order system by the characteristics of the reverse filter of the second order system filter is, in other words, dividing the impulse response of the first order system by the characteristics of the second digital filter. The reverse filter of the second digital filter may be reverse characteristics of an impulse response of the second order system (specifically, a sound propagation path from the control sound source to the error sensor). That is, the imaginary digital filter may include characteristics obtained by dividing the impulse response of the first order system by the impulse response of the second order system. 
     The divergence determiner may determine whether the first digital filter indicates a divergence tendency based on an intensity of the error signal and/or a change tendency in the intensity. 
     The divergence determiner may determine whether the first digital filter indicates a divergence tendency based on an output intensity of each tap of the L taps, a magnitude of the adjustable coefficient of each tap of the L taps, and/or a change tendency in a parameter used for updating the adjustable coefficient. 
     The L taps may have a length that corresponds to a length of time necessary for the impulse response of the first order system to converge. 
     N taps may have a length (or a total number of taps) to complete a process necessary for producing the artificial noise. The process necessary for producing the artificial noise may include a first process. The first process is executed by the characteristics adjustor. The first process includes updating of the adjustable coefficient by the characteristics adjustor in accordance with the reference signal within a first time period. The first time period corresponds to a time required from an acquisition of the reference signal by the reference acquirer to a detection of the target noise corresponding to the reference signal by the error sensor. The process necessary for producing the artificial noise may include a second process. The second process is executed by the first digital filter. The second process includes generation of the control signal in accordance with the reference signal by the first digital filter with the adjustable coefficient updated by the first process. 
     The characteristics adjustor may stop updating of the adjustable coefficient in response to the adjustable coefficient being updated a given number of times by the characteristics adjustor (or the number of updating of the adjustable coefficient by the characteristics adjustor reaching a threshold). The given number of times may include one time. 
     The characteristics adjustor may update the adjustable coefficient based on an update value. The update value corresponds to a value obtained by multiplying an update step size by a gradient vector. The update step size indicates a degree to which the adjustable coefficient is varied. The gradient vector indicating a direction toward which the adjustable coefficient is varied. 
     The characteristics adjustor may calculate the update value with an average value of the gradient vector that is repeatedly calculated every two or more processing cycles. 
     Such a configuration makes it possible to inhibit the updating of the adjustable coefficient of the first digital filter from being affected by a sudden variation in an external environment. 
     The characteristics adjustor may change the update step size in accordance with a converging status of the first digital filter. 
     Such a configuration makes it possible to further reduce divergence of the first digital filter. 
     The reference acquirer may include a reference sensor. The reference sensor detects the target noise to thereby generate the reference signal. 
     A distance between the reference sensor and the control sound source may be larger than a distance between the control sound source and the error sensor. 
     The electric powered work machine may generate a drive signal for driving the motor. The reference signal may correspond to the drive signal. 
     The reference acquirer may include a third digital filter. The third digital filter includes characteristics identical to characteristics of the second digital filter. The third digital filter being (i) receives the control signal from the first digital filter and (ii) generates an arrival signal. The arrival signal indicates the artificial noise that has arrived at the error sensor. 
     The reference acquirer may include an adder. The adder adds the arrival signal to the error signal to generate the reference signal. 
     The electric powered work machine may include a fan. The fan is driven by the motor to generate an airflow. The electric powered work machine may include a flow path. The flow path allows passage of the airflow generated by the fan. The electric powered work machine may include a discharge port. The discharge port discharges the airflow from the flow path. The control sound source and the error sensor may be arranged such that the discharge port corresponds to the canceling location. 
     The flow path may include an inner wall configured to guide the airflow. At least a part of the inner wall may include a sound absorbing material. The sound absorbing material reduces a sound generated due to a friction between the sound absorbing material and the airflow. The error sensor may be disposed at a position so that the error sensor faces the flow path with the sound absorbing material interposed therebetween. 
     Such a configuration makes it possible to inhibit a noise except the target noise from being detected by the error sensor. This makes it possible to improve an accuracy in reducing the target noise with the artificial noise. 
     Another aspect of the present disclosure provides a method of controlling a noise generated by an electric powered work machine. The method includes acquiring a reference signal. The reference signal has a correlation with a target noise. The target noise corresponds to a noise generated due to operation of the motor in the electric powered work machine. The method includes generating a control signal from the reference signal by a first digital filter. The control signal is used to cancel or attenuate the target noise. The first digital filter includes a series of taps. The first digital filter includes adjustable characteristics. The method includes producing an artificial noise by a control sound source in accordance with the control signal. The method includes converting a synthesized sound at a canceling location (or an attenuating location) to an error signal by an error sensor. The canceling location is a given position. The synthesized sound corresponds to a combined sound of the artificial noise and the target noise. The method includes generating a filtered reference signal from the reference signal by a second digital filter. The second digital filter includes transfer characteristics of a second order system. The second order system corresponds to a path from the control sound source to the error sensor. In other words, in the second digital filter, the second order system is modeled. The second digital filter includes N taps. The method includes updating coefficients of M taps in the series of taps in accordance with an adaptive algorithm. The adaptive algorithm uses the error signal and the filtered reference signal. The M taps may be any number of taps in the series of taps. Each of M and N is a positive integer satisfying M&lt;N. 
     Such a method may achieve the same effects as the effects achieved by the above-described electric powered work machine. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Example embodiments of the present disclosure will be described hereinafter by way of example with reference to the accompanying drawings, in which: 
         FIG. 1  is a perspective view of the appearance of a dust collector according to a first to a third embodiment; 
         FIG. 2  is a bottom view of a dust collector main body; 
         FIG. 3  is a perspective view of an internal state of the dust collector main body with a lower housing removed; 
         FIG. 4  is a perspective view of an upper housing without components installed therein, the upper housing being viewed from a side where a joining surface connecting the upper housing with the lower housing is provided; 
         FIG. 5  is a perspective view of the lower housing without components installed therein, the lower housing being viewed from the side where the joining surface is provided; 
         FIG. 6  is a perspective view of a state of the lower housing with some components installed therein; 
         FIG. 7  is a plan view of the lower housing; 
         FIG. 8  is a block diagram illustrating the electrical configuration of the dust collector; 
         FIG. 9  is a block diagram of a model of a feed-forward ANC system; 
         FIG. 10  is a block diagram illustrating an example configuration of a noise control filter; 
         FIG. 11  is a block diagram illustrating an example configuration of a second order system filter; 
         FIG. 12  is a flow chart of a noise reduction process; 
         FIG. 13  is a flow chart of a coefficient update process; 
         FIG. 14  is a flow chart of a divergence determination process; 
         FIG. 15  is a flow chart of a coefficient update process according to a second embodiment; 
         FIG. 16  is a flow chart of a coefficient update process according to a third embodiment; 
         FIG. 17  is a flow chart of a coefficient/step size update process; 
         FIG. 18  is a flow chart of a divergence determination process according to the third embodiment; 
         FIG. 19  is a perspective view of the appearance of a handheld vacuum cleaner according to a fourth embodiment; 
         FIG. 20  is a cross-sectional view of the handheld vacuum cleaner; 
         FIG. 21  is a perspective view of the handheld vacuum cleaner in a state with a housing and some components thereof removed and with an error detection microphone and a control speaker attached; 
         FIG. 22  is a block diagram of a model of a feedback ANC system; 
         FIG. 23  is a block diagram of a model of an ANC system used for calculating errors of the second order system; 
         FIG. 24  is an equivalent block diagram of the block diagram in  FIG. 23  with some modifications; and 
         FIG. 25  is an equivalent block diagram of the block diagram in  FIG. 24  with further modifications. 
     
    
    
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     1. First Embodiment 
     [1-1. Configuration of Dust Collector] 
     A dust collector  1 , which is one example of the electric powered work machine, will be described. The dust collector  1  is used in a state carried by an operator of the dust collector  1  on his or her back. For convenience of description, the direction (front, back, up, down, left, and right) with respect to the dust collector  1  is defined as illustrated in  FIGS. 1 to 7  in the first embodiment. 
     As illustrated in  FIGS. 1 to 7 , the dust collector  1  includes a main body  3 , an operation device  6 , and attachments  7 . 
     The attachments  7  include a first shoulder strap  71 A, a second shoulder strap  71 B, and a waist belt  72 . The first and second shoulder belts  71 A,  71 B and the waist belt  72  are attached to the back surface of the main body  3 . The first shoulder strap  71 A extends from the upper left end of the main body  3 . The second shoulder strap  71 B extends from the upper right end of the main body  3 . The first shoulder strap  71 A is worn over the left shoulder of the operator. The second shoulder strap  71 B is worn over the right shoulder of the operator. The waist belt  72  extends from near the bottom end of the main body  3 . The waist belt  72  is fastened around the waist of the operator. The main body  3  is suspended from the back of the operator by means of the attachments  7 . 
     The operation device  6  includes a switch to actuate or stop the dust collector  1 . The operation device  6  is manipulated by the operator. The operation device  6  is connected, via a cable  61 , to the main body  3  near the center of the bottom end of the main body  3 . 
     The main body  3  includes a housing  30 . 
     The housing  30  includes a lower housing  301 , an upper housing  302 , and a plate  303 . The lower housing  301  has an opening on its front surface. The lower housing  301  is shaped like a box with a bottom. The upper housing  302  has an opening on its front surface and back surface. The upper housing  302  is shaped like a frame. The plate  303  covers the opening on the upper side of the upper housing  302 . The plate  303  is plate-shaped. The housing  30  may be, for example, molded by injecting a resin material. 
     The housing  30  includes a suction port  31 , a dust collecting chamber  32 , a first flow path  33 , a motor chamber  34 , a second flow path  35 , an exhaust chamber  36 , a first battery compartment  37 A, a second battery compartment  37 B, and a component placement portion  38 . 
     The suction port  31  is provided in the central portion of the top end of the housing  30 . The suction port  31  is connected to a first end of a flexible hose (not illustrated). A second end of the hose is connected to a nozzle having a suction port. 
     The dust collecting chamber  32  is a space provided on the upper side of the interior of the housing  30 , and has a rectangular shape. The dust collecting chamber  32  stores a dust bag  41  that is connected to the suction port  31 . The dust bag  41  is made of, for example, paper. The dust bag  41  traps and collects grit and dust sucked from the suction port  31 . 
     The first flow path  33  is provided along the right side of the dust collecting chamber  32 . The bottom end of the first flow path  33  is connected to the motor chamber  34 . In the housing  30 , a filter  42  is arranged at the border between the first flow path  33  and the dust collecting chamber  32 . Examples of the filter  42  may include a high efficiency particulate air filter (HEPA). 
     The motor chamber  34  is a rectangular shaped space provided inside the housing  30  below the dust collecting chamber  32 . The motor chamber  34  includes an inlet port  341  provided in the central portion of the right end of the motor chamber  34 . The inlet port  341  is connected to the first flow path  33 . The motor chamber  34  includes an outlet port  342  provided in the upper portion of the left end of the motor chamber  34 . The outlet port  342  is connected to the second flow path  35 . The motor chamber  34  houses a drive unit (or drive system)  43 . 
     The drive unit  43  includes a fan  431 , a motor  432 , and a damper  433 . The fan  431  is connected to the rotor of the motor  432 . The fan  431  is driven by the motor  432  to generate an airflow. The airflow travels from the inlet port  341  into the motor chamber  34 , and then flows out from the outlet port  342 . The damper  433  has an annular shape, covering the circumference of the motor  432 . The damper  433  absorbs a noise generated by the motor  432 . The damper  433  may be a sponge, for example. In the first embodiment, the motor  432  is covered with the damper  433 , thereby not being illustrated in  FIGS. 3  and  6 . In  FIGS. 3 and 6 , the motor  432  is arranged in the center of the damper  433 . 
     The second flow path  35  connects the outlet port  342  with the exhaust chamber  36 . The second flow path  35  has a sound absorbing material  46  arranged therein. The lower housing  301  includes a first wall  301   a  that separates the second flow path  35  and the dust collecting chamber  32 . The sound absorbing material  46  is provided on the first wall  301   a . The sound absorbing material  46  may be a sponge. 
     The exhaust chamber  36  is a space provided inside of the housing  30  on the left side of the motor chamber  34 . The exhaust chamber  36  includes a discharge port  361  provided on the bottom surface of the housing  30 . The discharge port  361  has the shape of slits. 
     In the main body  3  configured as described above, when the drive unit  43  generates airflow, external air is introduced through the suction port  31  (specifically, through a hose, a nozzle, or other attachment(s) connected to the suction port  31 ) to the inside of the housing  30 . The introduced external air reaches the dust collecting chamber  32  and passes through the dust bag  41 . The passage of the external air through the dust bag  41  leaves grit and dust contained in the external air trapped and collected inside the dust bag  41 . The air that passes through the dust bag  41  flows through the filter  42 , then reaching the first flow path  33 . The filter  42  traps and collects finer grit and dust that cannot be caught by the dust bag  41 . The air that reaches the first flow path  33  passes through the motor chamber  34  and the second flow path  35 , then reaching the exhaust chamber  36 . The air that reaches the exhaust chamber  36  flows through the discharge port  361 , being discharged to the outside of the housing  30 . 
     The first battery compartment  37 A houses a first battery pack  45 A. The first battery compartment  37 A is provided in the vicinity of the bottom end of the housing  30 . The first battery compartment  37 A includes a first battery mounting hole  371 A that is open at around the lower left end of the housing  30 . The second battery compartment  37 B houses a second battery pack  45 B. The second battery compartment  37 B is disposed in the vicinity of the bottom end of the housing  30 . The second battery compartment  37 B includes a second battery mounting hole  371 B that is open at around the lower right end of the housing  30 . The first and second battery packs  45 A,  45 B are respectively inserted from the first and second battery mounting holes  371 A,  371 B to the first and second battery compartments  37 A,  37 B. Examples of each of the first and second battery packs  45 A,  45 B include a general-purpose battery. Each of the first and second battery packs  45 A,  45 B can be used for a power source of an electric powered work machine of various types. 
     The component placement portion  38  is a space in the housing  30  between an air flowing area and a battery area. The air flowing area includes the motor chamber  34 , the second flow path  35 , and the exhaust chamber  36 . The battery area includes the first and second battery compartments  37 A,  37 B. In the component placement portion  38 , various electrical components are arranged. The component placement portion  38  includes a first area  381  and a second area  382 . The first area  381  is surrounded on its three sides by the motor chamber  34 , the second flow path  35 , and the discharge port  361 . The second area  382  is interposed between the motor chamber  34  and the first and second battery compartments  37 A,  37 B. The second area  382  communicates with the first area  381 . 
     In the second area  382 , a connector  52  and a reference microphone  53  are provided. 
     The connector  52  is arranged between the first and second battery compartments  37 A,  37 B. The connector  52  connects the cable  61  to a circuit in the main body  3 . 
     The reference microphone  53  is mounted using a first mounting hole  344 . The first mounting hole  344  is formed on a second wall  343  that defines a boundary of the motor chamber  34 . The reference microphone  53  is mounted such that the reference microphone  53  is directional toward the inside of the motor chamber  34 . The reference microphone  53  detects a target noise generated inside the housing  30 . Specifically, the target noise includes a noise generated by the motor  432  and the fan  431 , and a noise generated by airflow produced by the drive unit  43 . The reference microphone  53  outputs a first detection signal indicating the target noise detected. 
     In the first area  381 , a control speaker (or control sound source, or control loudspeaker, or secondary loudspeaker, or secondary source, or secondary sound source)  54 , an error microphone  55 , and a drive controller  44  are provided. The control speaker  54  and the error microphone  55  are mounted respectively using a second mounting hole  304  and a third mounting hole  305 . The second mounting hole  304  and the third mounting hole  305  are formed on the bottom surface of the lower housing  301 . The control speaker  54  and the error microphone  55  are mounted such that the control speaker  54  and the error microphone  55  are directional toward the outside of the housing  30 . As illustrated in  FIG. 7 , the drive controller  44  is attached to a third wall  383  that defines a boundary between the first area  381  and the motor chamber  34 . The drive controller  44  includes a circuit board having circuit(s) that perform power supply control, motor control, noise control, and so on. Details of the drive controller  44  will be described later. 
     The error microphone  55  is provided in the vicinity of a canceling location (or an attenuating location). The canceling location corresponds to a position where the target noise needs to be canceled or attenuated by a sound produced (or emitted) from the control speaker  54  (hereinafter referred to as “artificial noise”). Examples of the canceling location may include the discharge port  361 . The error microphone  55  is situated at (i) a position substantially (or acoustically) equivalent to the canceling location (a position that can be considered as the canceling location), and (ii) a position where the airflow does not reach the error microphone  55 . The control speaker  54  is situated at a position where the phase of the artificial noise at the position of the error microphone  55  is identical to the phase of the artificial noise at the canceling location. The reference microphone  53 , the control speaker  54 , and the error microphone  55  are arranged such that a secondary time of arrival is shorter than a primary time of arrival. The secondary time of arrival corresponds to a time period in which the artificial noise travels from the control speaker  54  and arrives at the canceling location. The primary time of arrival corresponds to a time period in which the target noise travels from the position of the reference microphone  53  and arrives at the canceling location. During the time period corresponding to the difference between the primary time of arrival and the secondary time of arrival, a process to produce the artificial noise is executed. 
     The control speaker  54  emits the artificial noise toward the outside of the housing  30 . The error microphone  55  detects a synthesized sound discharged from the discharge port  361 . The synthesized sound corresponds to the combined sound of the target noise and the artificial noise. The error microphone  55  outputs a second detection signal indicating the detected synthesized sound. The control speaker  54  has an ability to emit a sound that is sufficiently louder than the target noise. The error microphone  55  has an ability to receive the synthesized sound without distortion. 
     [1-2. Drive Controller] 
     As illustrated in  FIG. 8 , the drive controller  44  includes a control circuit  441 , a dust collection circuit group  442 , a noise control circuit group  443 , and a power supply circuit  447 . The dust collector  1  includes a noise controller  10 . As illustrated in  FIG. 8 , the noise controller  10  and the drive controller  44  have some part thereof in common. 
     The power supply circuit  447  generates a power supply voltage from an electric power fed from the first battery pack  45 A and/or the second battery pack  45 B. The power supply circuit  447  feeds (or applies) the generated power supply voltage to each part of the dust collector  1 . 
     The control circuit  441  in the first embodiment is in the form of, for example, a microcomputer. Specifically, the control circuit  441  includes a CPU  441 A and a memory  441 B. The control circuit  441  may include a combination of electronic components, such as discrete devices, in place of or in addition to the microcomputer. The control circuit  441  may include a digital signal processor (DSP), an application specific integrated circuit (ASIC) and/or an application specific standard product (ASSP). The control circuit  441  may include a programmable logic device that is rewritable. The programmable logic device may include, for example, a field programmable gate array (FPGA). The control circuit  441  may include a combination of the microcomputer, the DSP, the ASIC, the ASSP and/or the programmable logic device. 
     The dust collection circuit group  442  includes various types of circuits that are necessary to perform the function of the dust collector  1 . The dust collection circuit group  442  in the first embodiment includes a motor drive circuit, a battery switching circuit, and a fault (or failure) detection circuit. The motor drive circuit drives the motor  432 . The battery switching circuit switches the power supply source between the first battery pack  45 A and the second battery pack  45 B depending on the remaining energies (or remaining electric power) of the first and second battery packs  45 A,  45 B. The fault detection circuit detects various types of faults (or failures) in relation to driving of the motor  432 . 
     The noise control circuit group  443  includes various types of circuits that are necessary to perform the function of the noise controller  10 . The noise control circuit group  443  includes a first analog/digital (A/D) converter  444 , a second A/D converter  445 , and a digital/analog (D/A) converter  446 . 
     The first A/D converter  444  receives a first detection signal from the reference microphone  53 . The first A/D converter  444  converts the first detection signal to digital data and feeds the digital data into the control circuit  441 . A reference signal x n  (see  FIG. 9 ), which will be described later, corresponds to the digital data fed from the first A/D converter  444 . The second A/D converter  445  receives the second detection signal from the error microphone  55 . The second A/D converter  445  converts the second detection signal to digital data and feeds the digital data into the control circuit  441 . An error signal e n  (see  FIG. 9 ), which will be described later, corresponds to the digital data fed from the second A/D converter  445 . The D/A converter  446  receives digital data (a control signal u n  to be described later) outputted from the control circuit  441 . The D/A converter  446  converts the control signal u n  to an analog signal and feeds the analog signal into the control speaker  54 . 
     The control circuit  441  controls the dust collection circuit group  442 , thereby achieving the function of the dust collector  1 . Moreover, the control circuit  441  executes a noise reduction process, thereby achieving the function to reduce the noise generated by the dust collector  1  (that is, the function of the noise controller  10 ). 
     The noise controller  10  includes the control circuit  441  that executes the noise reduction process, the noise control circuit group  443 , the reference microphone  53 , the control speaker  54 , and the error microphone  55 . 
     The control circuit  441  executes the noise reduction process, thereby achieving feed-forward active noise control (ANC). 
     [1-3. ANC Model] 
     Referring now to  FIG. 9 , a feed-forward ANC model (hereinafter simply referred to as “ANC model”) achieved by the noise controller  10  is described. The noise controller  10  can be represented by the control model (specifically, the ANC model) illustrated in  FIG. 9 . 
     As illustrated in  FIG. 9 , the ANC model includes a reference sensor M 1 , a control sound source M 2 , an error sensor M 3 , a noise control filter M 4 , a second order system filter M 5 , and a coefficient updater M 6 . The reference sensor M 1  corresponds to the reference microphone  53  and the first A/D converter  444 . The control sound source M 2  corresponds to the D/A converter  446  and the control speaker  54 . The error sensor M 3  corresponds to the error microphone  55  and the second A/D converter  445 . The noise control filter M 4 , the second order system filter M 5 , and the coefficient updater M 6  correspond to the control circuit  441 . Specifically, the noise control filter M 4 , the second order system filter M 5 , and the coefficient updater M 6  are achieved by execution of corresponding processes by means of the control circuit  441  in accordance with computer programs. However, the noise control filter M 4 , the second order system filter M 5 , and the coefficient updater M 6  may be partly or entirely achieved by hardware (or hardwired system). 
     The reference sensor M 1  generates the reference signal x n . The reference signal x n  corresponds to digital data indicating the target noise detected by the reference microphone  53  (specifically, the first detection signal), that is, the digital data outputted from the first A/D converter  444 . The subscript “n” as in the reference signal x n  indicates that it is the n th  sample data. 
     In the first embodiment, the noise control filter M 4  is in the form of a digital filter, more specifically in the form of a finite impulse response (FIR) filter, such as the one exemplified in  FIG. 10 . As illustrated in  FIG. 10 , the noise control filter M 4  includes L taps where “L” is a positive integer. More specifically, the noise control filter M 4  includes a first tap  101 , a second tap  102 , a third tap  103 , . . . and an L th  tap  104 . Each of the 2 nd  to L th  taps  102  to  104  includes a delay device  120  and an adder  130 . The delay device  120  introduces a delay of one sampling period to a signal inputted to the delay device  120  and outputs the delayed signal. Each of the 1 st  to L th  taps  101  to  104  includes a multiplier  110  in which the coefficient of the corresponding tap is set. For example, a coefficient w 1  is set in the multiplier  110  of the first tap  101 , a coefficient w 3  is set in the multiplier  110  of the third tap  103 , and a coefficient w L  is set in the multiplier  110  of the L th  tap  104 . In the noise control filter M 4 , operations schematically illustrated by a block diagram in  FIG. 10  are performed. The operations are executed, for example, in accordance with computer programs in the present embodiment as mentioned above. By the operations, a control signal u n  is generated from an L-dimensional reference vector x(n). The elements of the L-dimensional reference vector x(n) are L reference signals {x n , x n-1 , . . . , x n-L+1 } that are most recently detected. 
     The control sound source M 2  produces the artificial noise in accordance with the control signal u n . 
     The error sensor M 3  generates the error signal e n . The error signal e n  corresponds to digital data indicating the synthesized sound (that is, the second detection signal) detected by the error microphone  55 , that is, the digital data outputted from the second A/D converter  445 . 
     Hereinafter, a sound propagation path from the reference sensor M 1  to the error sensor M 3  is referred to as “first order system” while a sound propagation path from the control sound source M 2  to the error sensor M 3  is referred to as “second order system”. 
     In the first embodiment, the second order system filter M 5  is in the form of a digital filter, more specifically in the form of an FIR filter, such as the one exemplified in  FIG. 11 . As illustrated in  FIG. 11 , the second order system filter M 5  includes N taps where “N” is a positive integer. More specifically, the second order system filter M 5  includes a first tap  201 , a second tap  202 , a third tap  203 , . . . and an N th  tap  204 . Each of the 2 nd  to N th  taps  202  to  204  includes a delay device  220  and an adder  230 . The delay device  220  introduces a delay of one sampling period to an input signal and outputs the delayed signal. Each of the 1 st  to N th  taps  201  to  204  includes a multiplier  210  in which the coefficient of the corresponding tap is set. For example, a coefficient c 1  is set in the multiplier  210  of the first tap  201 , a coefficient c 2  is set in the multiplier  210  of the second tap  202 , and a coefficient c N  is set in the multiplier  210  of the N th  tap  204 . In the second order system filter M 5 , operations schematically illustrated by a block diagram in  FIG. 11  are performed. The operations are executed, for example, in accordance with computer programs in the present embodiment as mentioned above. By the operations, a filtered reference signal r n  is generated from an N-dimensional reference vector x(n). The elements of the N-dimensional reference vector x(n) are N reference signals {x n , x n-1 , . . . x n-N+1 } that are most recently detected. The second order system filter M 5  corresponds to a filter modeled on the transfer characteristics of the second order system. The coefficient of each tap in the second order system filter M 5  is, for example, a fixed value. The filtered reference signal r n  corresponds to a signal generated by imparting the influence of the second order system to the reference signal x n . The influence of the second order system is added on to the artificial noise having arrived the error sensor M 3 . 
     The coefficient updater M 6  updates the coefficients {w 1 , w 2 , w L } of the L taps included in the noise control filter M 4  such that the error signal e n  becomes the lowest by noise cancellation or noise attenuation between the target noise and the artificial noise at the position of the error sensor M 3  (that is, a position that can be considered as the canceling location). Hereinafter, the L-dimensional vector having the coefficients {w 1 , w 2 , . . . , w L } as its elements are referred to as “coefficient vector w(n)”. 
     The coefficients of the noise control filter M 4  may be updated with, for example, the Filtered-x LMS algorithm that is one of adaptive algorithms. 
     In the noise controller  10 , the total number of taps L of the noise control filter M 4  has a size that corresponds to the length of time within which the impulse response of the first order system sufficiently converges. The total number of taps L is set, for example, in a range from several hundreds to one thousand and several hundreds. The total number of taps N of the second order system filter M 5  is L or smaller. The total number of taps N is large enough to complete the noise reduction process within a processing time allotted to the noise reduction process. That is, the total number of taps N of the second order system filter M 5  is set depending on the processing capacity of the control circuit  441 . Moreover, the total number of taps N of the second order system filter M 5  is set to a value smaller than the number corresponding to the length of time within which the impulse response of the second order system sufficiently converges. In other words, the second order system filter M 5  represents part of the impulse response of the second order system. More specifically, the second order system filter M 5  represents the impulse response of the second order system except the latter half of the response. In other words, the second order system filter M 5  reproduces approximate characteristics of the impulse response of the second order system. 
     Hereinafter, the tap that processes the most recent signal in each of the noise control filter M 4  and the second order system filter M 5  is defined as the first tap. Moreover, the tap that processes the signal obtained in m sampling period (or interval) before the sampling period in which the most recent signal is obtained is defined as m+1 th  tap. For example, the fifth tap processes the signal obtained in four sampling periods before the sampling period of the most recent signal. Furthermore, between any two taps, the one with a smaller number is described as a higher-order tap while the one with a larger number is described as a lower-order tap. 
     The coefficients of the noise control filter M 4  are updated by the adaptive algorithm (specifically, by the coefficient updater M 6 ). When the coefficients of the noise control filter M 4  indicate a divergence tendency, M taps (specifically, from the first to the M th  taps) are used in the noise control filter M 4 . The letter M represents a positive integer equal to or smaller than N. The positive integer M is experimentally determined in advance by, for example, simulation using the following approach. 
     From an impulse response P of the first order system and an impulse response C of the second order system estimated in advance, transfer characteristics (hereinafter referred to as “theoretical characteristics”) P/C are calculated. The calculation of P/C means an operation to multiply P by 1/C (in other words, to divide P by C). That is, 1/C means an inverse response of the impulse response C of the second order system. For example, assume that the theoretical characteristics P/C are the true values of the noise control filter M 4  (that is, the true value of each coefficient of the noise control filter M 4 , and thus the true values of the transfer characteristics of the noise control filter M 4 ). Then, for each of the coefficients w 1  to w L  of the taps in the noise control filter M 4  when a divergence tendency is detected, the deviation from the corresponding true value is calculated. Subsequently, out of the taps with deviations as large as or larger than a given threshold, the highest-order tap and the taps lower than the highest-order tap are eliminated. The number of the remaining taps after the elimination may be determined as M. 
     Alternatively, for example, the number of taps M may be determined by a first approach described below. That is, for each of the coefficients w 1  to w L  of the taps of the noise control filter M 4 , the square value SLa of the coefficient of the lowest-order tap is calculated. Moreover, the sum of squares SUa of the taps higher than the lowest-order tap is calculated. Then, the square value SLa and the sum of squares SUa are compared. If the result of the comparison is “α×SUa&lt;SLa”, the lowest-order tap is eliminated. The number that a represents is larger than zero and smaller than one, and may be, for example, ½. If the lowest-order tap is eliminated, the same process is performed with respect to the rest of the taps. This process is repeated until “α×SUa≥SLa” is established. Then, the number of remaining taps when “α×SUa≥SLa” is established may be determined as M. 
     Alternatively, for example, the number of taps M may be determined by a second approach described below. That is, in the L taps, a first tap group and a second tap group are determined as appropriate, which will be described below. Each of the first and second tap groups includes two or more consecutive taps. The taps in the first tap group are higher in order than taps in the second tap group. The sum of squares SUb of the coefficients of the taps in the first tap group, and the sum of squares SLb of the coefficients of the taps in the second tap group, are calculated. Then, the sum of squares SLb and the sum of squares SUb are compared. If the result of the comparison is “α×SUb&lt;SLb”, the second tap group may be eliminated and the number of remaining taps may be determined as M. It does not have to be the entire second tap group to be eliminated. One or more consecutive tap(s) of the second tap group including the highest-order tap may be kept uneliminated. 
     Each of the first and second tap groups may be determined in any suitable manner. For example, the 1 st  tap to p th  tap may be assigned to the first tap group, and the p+1 th  tap to L th  tap may be assigned to the second tap group. In this case, the p th  tap may be any one of the 3 rd  tap to L−2 th  tap. More specifically, the p th  tap may be, for example, any one of the P1 th  tap to P2 th  tap. P1 may be, for example, L/3 (if the number is indivisible, the decimal may be rounded up to the whole number, for example), and P2 may be, for example, 2L/3 (if the number is indivisible, the decimal may be rounded up to the whole number, for example). Alternatively, the p th  tap may be, for example, the middle tap (or the tap almost at the middle) of L taps. 
     Each of the first and second tap groups may include any number of taps. The first tap group does not have to include the 1 st  tap which is the highest in the order. The second tap group does not have to include the L th  tap which is the lowest. The taps in the second tap group do not have to be taps consecutive to taps in the first tap group. For example, there may be one or more tap(s) between the first and second taps groups that is/are not included in the first and second tap groups. 
     In the above-described comparison, if the result is “α×SUb≥SLb”, the each of the first and second tap groups may be redetermined, for example. Specifically, for example, one or more tap(s) from the lowest in the present first tap group may be eliminated from the first tap group. Alternatively or additionally, one or more taps) that is/are consecutive tap(s) of the highest tap in the present second tap group may be added to the second tap group. Then, the above-described comparison may be made again based on the first and second tap groups that are redetermined in this manner. 
     The number of taps M may be determined by the combination of the above-described first and second approaches. For example, the number of taps M may be first temporarily determined by the second approach. Then, the first approach may be applied to the temporarily determined the 1 st  tap to M th  tap to determine the number of taps M. 
     [1-4. Process] 
     [1-4-1. Noise Reduction Process] 
     Referring now to the flow chart of  FIG. 12 , the noise reduction process executed by the control circuit  441  will be described. The noise reduction process is repeatedly executed with the same period as the sampling period of the first and second A/D converters  444 ,  445 . The sampling period is set to a period that corresponds to twice the maximum frequency of the target noise. The period in which the noise reduction process is executed is referred to as “processing cycle”. 
     The control circuit  441  includes a first shift register, a second shift register, a third shift register, and L registers (hereinafter referred to as “first register group”). The control circuit  441  uses the first shift register for calculations related to the noise control filter M 4 . In the first shift register, L reference signals x n  (that is, the L-dimensional reference vector x(n)) are sequentially stored. The control circuit  441  uses the second shift register for calculations related to the second order system filter M 5 . In the second shift register, N reference signals x n  to x n-N+1  (that is, the N-dimensional reference vector x(n)) are sequentially stored. The control circuit  441  uses the third shift register for calculations related to the coefficient updater M 6 . In the third shift register, L filtered reference signals r n  to r n-L+1  (that is, the filtered reference vector r(n)) are sequentially stored. The control circuit  441  stores the results of processing executed in the coefficient updater M 6  in the first register group. More specifically, the L coefficients w 1  to w L  (that is, the coefficient vector w(n)) to be fed into the noise control filter M 4  are stored in the first register group. A coefficient “w 1 ” represents the coefficient of the i th  tap. 
     When the control circuit  441  is activated, a divergence flag FL is initialized to zero (that is, OFF). Moreover, when the control circuit  441  is activated, the coefficients of the L taps in the noise control filter M 4 , that is the coefficient vector w(n), are initialized to a preset initial value. If updated values of the coefficient vector w(n) are not converging (that is, tend to diverge), the divergence flag FL is set to one (that is, ON). The initial values of the coefficient vector w(n) may be values indicating, for example, the theoretical characteristics P/C (specifically, the coefficient of each tap in the digital filter in which the theoretical characteristics P/C are embodied). Alternatively, the initial values of the coefficient vector w(n) may be set to, for example, a given value/given values (for example, all set to one). 
     As illustrated in  FIG. 12 , in response to an initiation of the noise reduction process, the control circuit  441  acquires the reference signal x n  in S 110 . The control circuit  441  stores the acquired reference signal x n  in each of the first and second shift registers. 
     In S 120 , the control circuit  441  executes a process to perform the function of the noise control filter M 4 . Specifically, the control circuit  441  calculates the control signal u n  using the reference vector x(n) stored in the first shift register and the coefficient vector w(n) stored in the first register group. Specifically, the control circuit  441  calculates the control signal u n  in accordance with Formula (1). 
     
       
         
           
             
               
                 
                   
                     u 
                     n 
                   
                   = 
                   
                     
                       ∑ 
                       
                         i 
                         = 
                         1 
                       
                       L 
                     
                     
                       ( 
                       
                         
                           x 
                           
                             n 
                             - 
                             i 
                             + 
                             1 
                           
                         
                         × 
                         
                           w 
                           i 
                         
                       
                       ) 
                     
                   
                 
               
               
                 
                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
     
     In S 130 , the control circuit  441  executes a coefficient update process. The coefficient update process includes updating the coefficient vector w(n) of the noise control filter M 4  in accordance with the adaptive algorithm. 
     In S 140 , the control circuit  441  executes a divergence determination process including (i) adjusting the configuration of the noise control filter M 4  and (ii) not adjusting the configuration of the noise control filter M 4 . The (i) adjusting the configuration of the noise control filter M 4  is executed when the coefficient vector w(n) calculated in the coefficient update process indicates a divergence tendency. The (ii) not adjusting the configuration of the noise control filter M 4  is executed when the coefficient vector w(n) calculated in the coefficient update process does not indicate a divergence tendency. 
     In S 150 , the control circuit  441  outputs the control signal u n  calculated in S 120  to the D/A converter  446 . The control signal u n  is converted to an analog signal by the D/A converter  446  and fed into the control speaker  54 . Accordingly, the control speaker  54  produces the artificial noise based on the control signal u n . 
     [1-4-2. Coefficient Update Process] 
     Referring now to the flow chart in  FIG. 13 , details of the coefficient update process in S 130  will be described. 
     In response to an initiation of the coefficient update process, the control circuit  441  executes the process in S 210  to function as the second order system filter M 5 . Specifically, the control circuit  441  calculates the filtered reference signal r n  using the N-dimensional reference vector x(n) stored in the second shift register and N coefficients c 1  to c N  preset in the taps of the second order system filter M 5 . Specifically, the control circuit  441  calculates the filtered reference signal r n  in accordance with Formula (2). The control circuit  441  stores the calculated filtered reference signal r n  in the third shift register. 
     
       
         
           
             
               
                 
                   
                     r 
                     n 
                   
                   = 
                   
                     
                       ∑ 
                       
                         i 
                         = 
                         1 
                       
                       N 
                     
                     
                       ( 
                       
                         
                           x 
                           
                             n 
                             - 
                             i 
                             + 
                             1 
                           
                         
                         × 
                         
                           c 
                           i 
                         
                       
                       ) 
                     
                   
                 
               
               
                 
                   ( 
                   2 
                   ) 
                 
               
             
           
         
       
     
     In S 220 , the control circuit  441  calculates the sum of square R n  of the L elements included in the filtered reference vector r(n) stored in the third shift register. The filtered reference vector r(n) is an L-dimensional vector having most recently calculated L filtered reference signals {r n , r n-1 , . . . , r n-L+1 } as its elements. Hereinafter, the sum of square R n  is referred to as “normalized value”. 
     In S 230 , the control circuit  441  acquires the error signal e n . The error signal e n  is a scalar value. In S 240 , the control circuit  441  calculates a gradient vector S(n). 
     As expressed in Formula (3), the gradient vector S(n) corresponds to the product of the filtered reference vector r(n) stored in the third shift register and the error signal e n  acquired in S 230 . The gradient vector S(n) indicates the direction toward which the coefficient vector w(n) varies in the L-dimensional coordinate space representing the coefficient vector w(n). 
         S ( n )= e   n   ×r ( n )  (3)
 
     In S 250 , the control circuit  441  updates the coefficient vector w(n) using Formula (4). The control circuit  441  stores the updated coefficient vector w(n+1) in the first register group. Accordingly, the coefficient vector w(n+1) is fed into the noise control filter M 4 . In Formula (4), the letter μ corresponds to a scalar value for adjusting the speed of convergence and the estimated accuracy of an adaptive operation. Hereinafter, the scalar value μ is referred to as “updating step size”. Examples of the updating step size μ may include a specified fixed value. 
     
       
         
           
             
               
                 
                   
                     w 
                     ⁡ 
                     ( 
                     
                       n 
                       + 
                       1 
                     
                     ) 
                   
                   = 
                   
                     
                       w 
                       ⁡ 
                       ( 
                       n 
                       ) 
                     
                     + 
                     
                       
                         μ 
                         · 
                         
                           S 
                           ⁡ 
                           ( 
                           n 
                           ) 
                         
                       
                       
                         R 
                         n 
                       
                     
                   
                 
               
               
                 
                   ( 
                   4 
                   ) 
                 
               
             
           
         
       
     
     [1-4-3. Divergence Determination Process] 
     Referring now to the flow chart in  FIG. 14 , details of the divergence determination process in S 140  will be described. 
     In response to an initiation of the divergence determination process, the control circuit  441  determines in S 310  whether the divergence flag FL is set to OFF (specifically, FL=0). If the divergence flag FL is set to ON (specifically, FL=1), the control circuit  441  terminates the divergence determination process. If the divergence flag FL is set to OFF, the process proceeds to S 320 . 
     In S 320 , the control circuit  441  acquires a divergence determination parameter that is used for divergence determination. The divergence determination includes determining whether the coefficient vector w(n) updated in S 130  indicates a divergence tendency. The divergence determination parameter includes a first determination parameter, a second determination parameter, and/or a third determination parameter. For divergence determination, at least one parameter of the first to third determination parameters is used. 
     The first determination parameter is a value obtained by subtracting the amount of deviation in a low-order tap group in the noise control filter M 4  from the amount of deviation in a high-order tap group. The amount of deviation in the high-order tap group corresponds to the degree to which the coefficients of the taps in a first high-order tap group deviate from the respective true values. The first high-order tap group corresponds to A taps that are from the 1 st  tap to A th  tap. The amount of deviation in the low-order tap group corresponds to the degree to which the coefficients of the taps in a first low-order tap group deviate from the respective true values. The first low-order tap group corresponds to L−A taps that are from the A+1 th  tap to L th  tap. The amount of deviation in each tap group may be, for example, the sum of squares of the deviations of the coefficients from the respective true values, or the sum of the absolute values of the deviations of the coefficients from the respective true values. The number of taps A in the first high-order tap group may be the same as the number of taps M used in the noise control filter M 4  when the coefficient vector w(n) indicates a divergence tendency. 
     The second determination parameter is an absolute value of the error signal e n . 
     The third determination parameter corresponds to the magnitude of a difference vector. The difference vector corresponds to the vector obtained by subtracting the coefficient vector w(n+1) after updating from the coefficient vector w(n) before updating. The magnitude of the difference vector may be, for example, the sum of squares of the elements included in the difference vector, or the sum of the absolute values of the elements. 
     In S 330 , the control circuit  441  determines whether the coefficients of the noise control filter M 4  tend to diverge, using the divergence determination parameter acquired in S 320 . In response to a determination that the coefficients of the noise control filter M 4  tend to diverge, the control circuit  441  proceeds to S 340 . In response to a determination that the coefficients of the noise control filter M 4  do not tend to diverge, the control circuit  441  terminates the divergence determination process. 
     Specifically, if the first determination parameter is used as the divergence determination parameter, the control circuit  441  may determine a divergence tendency in response to the first determination parameter being a negative value. The first determination parameter being a negative value means that the amount of deviation in the low-order tap group is larger than the amount of deviation in the high-order tap group. 
     If the second determination parameter is used as the divergence determination parameter, the control circuit  441  may determine a divergence tendency in response to the second determination parameter being at or above a threshold. The threshold may be set based on, for example, the maximum noise value tolerated in the noise controller  10 . The threshold may be, for example, twice the maximum noise value. The control circuit  441  may determine a divergence tendency in response to a monotonic increase in the second determination parameter over two or more (for example, three) processing cycles. 
     If the third determination parameter is used as the divergence determination parameter, the control circuit  441  may determine a divergence tendency in response to a monotonic increase in the third determination parameter over two or more (for example, three) processing cycles. 
     To determine a divergence tendency, any combination of the first to third determination parameters may be used. The control circuit  441  may use two or more parameters out of the first to third determination parameters. In this case, the control circuit  441  may determine a divergence tendency in response to, for example, at least one of the used parameters indicating a divergence tendency. For another example, the control circuit  441  may determine a divergence tendency in response to any two or more parameters out of the used parameters each indicating a divergence tendency. 
     In S 340 , the control circuit  441  imposes a restriction on the noise control filter M 4 . M taps from the 1 st  tap to M th  tap in the noise control filter M 4  will be simply referred to as “second high-order tap group”, and L−M taps from M+1 th  to L th  taps will be simply referred to as “second low-order tap group”. Imposing a restriction on the noise control filter M 4  may include, for example, setting each of the coefficients w M+1  to w L  of the second low-order tap group to a fixed value. The fixed value may be, for example, identical to the coefficient of the corresponding tap in the low-order tap group (from the M+1 th  to L th  taps) in an imaginary filter that represents the theoretical characteristics P/C. Each fixed value may be set to any given value. 
     For another example, imposing a restriction on the noise control filter M 4  may include disabling each tap in the second low-order tap group and enabling each tap in the second high-order tap group. That is, a restriction may be imposed on the noise control filter M 4  so that not the disabled taps but the enabled taps are used for calculating the control signal u n . If the process of S 340  is executed (specifically, if a restriction is imposed on the noise control filter M 4 ), the control circuit  441  generates the control signal u n  using the noise control filter M 4  with a restriction in S 120  of the subsequent processing cycle. 
     In S 350 , the control circuit  441  sets the divergence flag FL to ON (specifically, FL=1). Based on this setting, the detection of the divergence tendency is stored. After the process of S 350  is executed, the control circuit  441  terminates this process. 
     As described above, in response to a determination that the coefficient vector w(n) of the noise control filter M 4  indicates a divergence tendency, a restriction is imposed on the noise control filter M 4 . Once the restriction is imposed, the restriction is not basically removed while the control circuit  441  is active. After the restriction is imposed, calculation for the control signal u n  using the restricted noise control filter M 4  continues until, for example, operation of the control circuit  441  stops. 
     [1-5. Correspondence of Terms] 
     In the first embodiment, the noise control filter M 4  corresponds to one example of the first digital filter of the present disclosure. The second order system filter M 5  corresponds to one example of the second digital filter of the present disclosure. The reference microphone  53  and the first A/D converter  444  (specifically, the reference sensor M 1 ) correspond to one example of the reference acquirer of the present disclosure. The processes of S 220  to S 250  and S 340  correspond to one example of characteristics adjustor of the present disclosure. The processes of S 320  to S 330  correspond to one example of the divergence determiner of the present disclosure. 
     [1-6. Effects] 
     According to the first embodiment described in detail above, the following effects are achieved. 
     (1a) In the first embodiment, the number of taps N of the second order system filter M 5  is set shorter (or lower) than the length (or the number) that corresponds to the length of time period within which the impulse response of the second order system sufficiently converges. This reduces the amount of the computing processing necessary for noise control. 
     (1b) In the first embodiment, the coefficients w 1  to w L , of all the taps (L taps) included in the noise control filter M 4  are updated before a divergence tendency is detected. On the other hand, after a divergence tendency is detected, the coefficients w M+1  to w L  of the second low-order tap group are set to fixed values or are disabled so that the coefficients w 1  to w M  of the second high-order tap group are updated. This inhibits the coefficients of the noise control filter M 4  from diverging even if the second order system filter M 5  includes a second order system estimation error. The second order system estimation error means an error of the second order system filter M 5 . More specifically, the second order system estimation error indicates the difference between the actual characteristics of the second order system and the characteristics represented by the second order system filter M 5 . If the number of taps N of the second order system filter M 5  is set to an insufficient length, a measurable error may occur in the second order system estimation error. 
     (1c) In the first embodiment, the error microphone  55  is situated at a position where the airflow generated by the drive unit  43  does not reach the error microphone  55 . In other words, the error microphone  55  is situated at a position where noise except the target noise is inhibited from entering the error microphone  55 . The noise except the target noise may include, for example, wind noise generated by the airflow directly hitting the error microphone  55 . Moreover, the error microphone  55  is situated at a position that can be considered as the canceling location. The control speaker  54  is arranged such that the phase of the artificial noise from the control speaker  54  is the same at the canceling location and at the position of the error microphone  55 . This results in an enhancement of the coherence between the reference signal x n  detected by the reference microphone  53  and the error signal e n  detected by the error microphone  55 , improving control accuracy in reducing the target noise. 
     [1-7. Influence of Error of Second Order System on Coefficients of Noise Control Filter] 
     The following describes principles of inhibiting a divergence by imposing a restriction on the noise control filter M 4  in response to a detection of a divergence tendency. 
     First, the significant influence of the second order system estimation error on the coefficients of the noise control filter M 4  will be described. 
     In  FIGS. 23 to 25 , P(z) represents a z-transform of the characteristics of the first order system. H(z) represents a z-transform of the characteristics of the noise control filter M 4 . C(z) represents a z-transform of the characteristics of the second order system. CH(z) represents a z-transform of the characteristics of the second order system filter M 5 . The characteristics of the second order system filter M 5  (specifically, the coefficient of each tap) are set prior to execution of ANC by estimating the characteristics C(z) of the second order system. The coefficient of each tap in the second order system filter M 5  is, for example, a fixed value as described above. N(z) represents a z-transform of the target noise. NLMS represents the coefficient updater M 6  according to the learning identification method. In this analysis, the feedback system from the control sound source M 2  to the reference sensor M 1  is assumed to be negligible. In this case, the structure of the feed-forward ANC (control model) is illustrated in  FIG. 23 . 
     In the case where the coefficients of the noise control filter M 4  are slowly updated by the coefficient updater M 6 , the noise control filter M 4  is assumed to be a linear filter. In this case, it is theoretically possible to reverse the connection order of the second order system and the noise control filter M 4  as illustrated in  FIG. 24 . 
     In this case, however, P(z) representing the characteristics of the first order system in  FIG. 23  is replaced with PD(z) expressed in Formula (5) as illustrated in  FIG. 24 . 
     
       
         
           
             
               
                 
                   
                     P 
                     ⁢ 
                     
                       D 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                   = 
                   
                     
                       P 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                     
                       C 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                 
               
               
                 
                   ( 
                   5 
                   ) 
                 
               
             
           
         
       
     
     In the structure illustrated in  FIG. 24 , assuming that the characteristics CH(z) of the second order system filter M 5  have no errors (specifically, CH(Z)=C(z)), the signal inputted to the first order system (the characteristics PD(z)), the signal inputted to the noise control filter M 4  (the characteristics H(z)), and the signal inputted from the second order system filter M 5  to the coefficient updater M 6  (NLMS) match one another. In this case, the characteristics  11 ( z ) of the noise control filter M 4  converge to the characteristics PD(z) of the first order system. As a result of the convergence of the characteristics  11 ( z ) to PD(z), the characteristics H(z) are adjusted to Hopt(z) expressed in Formula (6) (in other words, the characteristics H(z) converge to Hopt(z)). When the characteristics H(z) are adjusted to Hopt(z), the target noise is, in theory, completely canceled out by the artificial noise based on the control signal outputted from the adjusted characteristics H(z) (specifically, Hopt(z)). Hereinafter, Hopt(z) will be referred to as “characteristics of the optimum noise control filter”. 
     
       
         
           
             
               
                 
                   
                     
                       H 
                       opt 
                     
                     ( 
                     z 
                     ) 
                   
                   = 
                   
                     
                       P 
                       ⁢ 
                       
                         D 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                     
                     = 
                     
                       
                         P 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       
                         C 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   6 
                   ) 
                 
               
             
           
         
       
     
     In actual use (for example, when the control model in  FIG. 24  is implemented on the control circuit  441 ), the estimated value of the second order system (specifically, the characteristics of the second order system filter M 5 ) CH(z) includes a second order system estimation error Δ(z). The second order system estimation error Δ(z) corresponds to the difference between estimated characteristics CH(z) and the actual characteristics C(z) of the second order system. In this case, the characteristics CH(z) are expressed by Formula (7). 
         CH ( z )= C ( z )+Δ( z )  (7)
 
     In order to consider an influence of the second order system estimation error Δ(z), each of the two characteristics C(z) of the second order system in  FIG. 24  are replaced with the characteristics CH(z) of the second order system filter M 5 . In this case, the characteristics PD(z) of the first order system in  FIG. 24  are replaced with the characteristics PH(z) expressed in Formula (8) as illustrated in  FIG. 25 . 
     
       
         
           
             
               
                 
                   
                     P 
                     ⁢ 
                     
                       H 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                   = 
                   
                     
                       
                         P 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       
                         C 
                         ⁢ 
                         
                           H 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                       
                     
                     = 
                     
                       
                         P 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       
                         
                           C 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                         + 
                         
                           Δ 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   8 
                   ) 
                 
               
             
           
         
       
     
     As it can be seen from  FIG. 25 , when the characteristics H(z) of the noise control filter M 4  are adjusted to satisfy Formula (9), that is, when the characteristics H(z) of the noise control filter M 4  converge to Formula (10), the target noise is completely canceled out in theory. 
     
       
         
           
             
               
                 
                   
                     
                       
                         C 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       
                         C 
                         ⁢ 
                         
                           H 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                       
                     
                     · 
                     
                       H 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                   = 
                   
                     PH 
                     ⁡ 
                     ( 
                     z 
                     ) 
                   
                 
               
               
                 
                   ( 
                   9 
                   ) 
                 
               
             
           
         
       
       
         
           
             
               
                 
                   
                     H 
                     ⁡ 
                     ( 
                     z 
                     ) 
                   
                   = 
                   
                     
                       
                         PH 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       · 
                       
                         
                           C 
                           ⁢ 
                           
                             H 
                             ⁡ 
                             ( 
                             z 
                             ) 
                           
                         
                         
                           C 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                       
                     
                     = 
                     
                       
                         P 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                       
                         C 
                         ⁡ 
                         ( 
                         z 
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   10 
                   ) 
                 
               
             
           
         
       
     
     In reality, however, it is not possible in the noise control filter M 4  to handle the characteristics H(z) separately between a C(z)/CH(z) and PH(z). Accordingly, the characteristics of the noise control filter M 4  are updated such that the coefficients converge to HD(z) as expressed in Formula (11). AD(z) in Formula (11) is expressed by Formula (12). 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           HD 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                         = 
                           
                         
                           
                             
                               
                                 C 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               
                                 CH 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                             · 
                             
                               
                                 H 
                                 opt 
                               
                               ( 
                               z 
                               ) 
                             
                           
                           = 
                           
                             
                               
                                 
                                   C 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                                 
                                   CH 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                               · 
                               
                                 
                                   P 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                                 
                                   C 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                             
                             = 
                             
                               
                                 P 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               
                                 CH 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                         
                           
                             
                               P 
                               ⁡ 
                               ( 
                               z 
                               ) 
                             
                             
                               
                                 C 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               + 
                               
                                 Δ 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                           
                           = 
                           
                             
                               
                                 P 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               
                                 C 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                             · 
                             
                               1 
                               
                                 1 
                                 + 
                                 
                                   
                                     Δ 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                   
                                     C 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                 
                               
                             
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           · 
                           
                             1 
                             
                               1 
                               + 
                               
                                 Δ 
                                 ⁢ 
                                 
                                   D 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                             
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   11 
                   ) 
                 
               
             
           
         
       
       
         
           
             
               
                 
                   
                     Δ 
                     ⁢ 
                     
                       D 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                   = 
                   
                     
                       Δ 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                     
                       C 
                       ⁡ 
                       ( 
                       z 
                       ) 
                     
                   
                 
               
               
                 
                   ( 
                   12 
                   ) 
                 
               
             
           
         
       
     
     It is understood from Formulae (11) and (12) that the second order system estimation error Δ(z) does not deteriorate the noise reduction effect in a simple cumulative manner. Specifically, the second order system estimation error Δ(z) is incorporated in the characteristics HD(z) of the noise control filter M 4  as convolution with the characteristics Hopt(z) of the optimum noise control filter. The second order system estimation error Δ(z) is incorporated in the characteristics HD(z) as described above, thereby deteriorating the noise reduction effect. 
     The degree of deterioration in the noise reduction effect caused by this convolution is clarified. The difference between the characteristics Hopt(z) of the optimum noise control filter and the converged characteristics HD(z) of the noise control filter M 4  is expressed in Formula (13). 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           - 
                           
                             HD 
                             ⁡ 
                             ( 
                             z 
                             ) 
                           
                         
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           - 
                           
                             
                               
                                 H 
                                 opt 
                               
                               ( 
                               z 
                               ) 
                             
                             · 
                             
                               1 
                               
                                 1 
                                 + 
                                 
                                   Δ 
                                   ⁢ 
                                   
                                     D 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                 
                               
                             
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           · 
                           
                             
                               Δ 
                               ⁢ 
                               
                                 D 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                             
                               1 
                               + 
                               
                                 Δ 
                                 ⁢ 
                                 
                                   D 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                             
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   13 
                   ) 
                 
               
             
           
         
       
     
     It is understood from Formula (13) that, if ΔD(z) is sufficiently small, the difference between the converged characteristics HD(z) of the noise control filter M 4  and the characteristics Hopt(z) of the optimum noise control filter is convolution of Hopt(z) and ΔD(z). 
     As a result of a conversion of Formula (11), Formula (14) is obtained. 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           HD 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           · 
                           
                             1 
                             
                               1 
                               + 
                               
                                 Δ 
                                 ⁢ 
                                 
                                   D 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                             
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           [ 
                           
                             1 
                             + 
                             
                               { 
                               
                                 
                                   - 
                                   Δ 
                                 
                                 ⁢ 
                                 
                                   D 
                                   ⁡ 
                                   ( 
                                   z 
                                   ) 
                                 
                               
                               } 
                             
                             + 
                             
                               
                                 { 
                                 
                                   
                                     - 
                                     Δ 
                                   
                                   ⁢ 
                                   
                                     D 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                 
                                 } 
                               
                               2 
                             
                             + 
                             … 
                           
                               
                           ] 
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   14 
                   ) 
                 
               
             
           
         
       
     
     As described above, if the characteristics CH(z) of the second order system filter M 5  include an error from the actual characteristics C(z) of the second order system, the noise reduction effect of ANC is deteriorated. The second and subsequent terms on the right side of Formula (14) correspond to the degree of the deterioration in the noise reduction effect. 
     Next, a case is described where enough taps cannot be provided in the second order system filter M 5 , specifically where the number of taps in the second order system filter M 5  is smaller than the number corresponding to the length of time necessary for the impulse response of the second order system to sufficiently converge. 
     If the second order system filter M 5  cannot be provided with enough taps, the second order system estimation error Δ(z) increases. The characteristics CH(z) of the second order system filter M 5  are expressed by Formula (15) where “d” indicates the number of taps in the second order system filter M 5 . 
         CH ( z )= C ( z )−Δ( z )· z   −d   =C ( z ){1−Δ D ( z ) z   −d }  (15)
 
     In the formula, Δ(z)z −d  represents a z-transform of a portion of the impulse response in the second order system that is terminated (specifically removed) due to insufficiency of taps. For simplification of the description, the coefficient of each tap from the 1 st  tap to the d−1 th  tap is assumed to include no error. 
     In this case, the converged characteristics HD(z) of the noise control filter M 4  are expressed by Formula (16). In Formula (16), the difference between the converged characteristics HD(z) of the noise control filter M 4  and the characteristics Hopt(z) of the optimum noise control filter is expressed in the second and subsequent terms on the right side of the formula as in Formula (14). 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           HD 
                           ⁡ 
                           ( 
                           z 
                           ) 
                         
                         = 
                           
                         
                           
                             
                               P 
                               ⁡ 
                               ( 
                               z 
                               ) 
                             
                             
                               
                                 C 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               - 
                               
                                 Δ 
                                 ⁢ 
                                 
                                   ( 
                                   z 
                                   ) 
                                 
                                 ⁢ 
                                 
                                   z 
                                   
                                     - 
                                     d 
                                   
                                 
                               
                             
                           
                           = 
                           
                             
                               
                                 P 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                               
                                 C 
                                 ⁡ 
                                 ( 
                                 z 
                                 ) 
                               
                             
                             · 
                             
                               1 
                               
                                 1 
                                 - 
                                 
                                   Δ 
                                   ⁢ 
                                   
                                     D 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                   ⁢ 
                                   
                                     z 
                                     
                                       - 
                                       d 
                                     
                                   
                                 
                               
                             
                           
                         
                       
                     
                   
                   
                     
                       
                         = 
                           
                         
                           
                             
                               H 
                               opt 
                             
                             ( 
                             z 
                             ) 
                           
                           [ 
                           
                             1 
                             + 
                             
                               
                                 { 
                                 
                                   Δ 
                                   ⁢ 
                                   
                                     D 
                                     ⁡ 
                                     ( 
                                     z 
                                     ) 
                                   
                                 
                                 } 
                               
                               ⁢ 
                               
                                 z 
                                 
                                   - 
                                   d 
                                 
                               
                             
                             + 
                             
                               
                                 
                                   { 
                                   
                                     Δ 
                                     ⁢ 
                                     
                                       D 
                                       ⁡ 
                                       ( 
                                       z 
                                       ) 
                                     
                                   
                                   } 
                                 
                                 2 
                               
                               ⁢ 
                               
                                 z 
                                 
                                   
                                     - 
                                     2 
                                   
                                   ⁢ 
                                   d 
                                 
                               
                             
                             + 
                             … 
                           
                               
                           ] 
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   16 
                   ) 
                 
               
             
           
         
       
     
     It is understood from Formula (16) that the termination (removal) of the latter half of the impulse response in the second order system filter M 5  affects only the d th  and subsequent coefficients in the noise control filter M 4 . Accordingly, even if the second order system filter M 5  cannot be provided with enough taps, it is possible to achieve the noise reduction effect (specifically, to inhibit deterioration of the noise reduction effect) by adjusting the number of taps in the noise control filter M 4  to a number comparable to the number of taps (d taps) in the second order system filter M 5  or smaller. 
     2. Second Embodiment 
     [2-1. Differences from First Embodiment] 
     In a second embodiment, the basic configurations of the dust collector  1  are the same as in the first embodiment. Thus, the differences from the first embodiment will be described in the second embodiment. In the second embodiment, the same numeral references as in the first embodiment indicate the same configurations as those in the first embodiment, and the earlier descriptions of such configurations should be referred to. 
     In the first embodiment, the coefficients of the noise control filter M 4  are updated every processing cycle. In contrast, the coefficients of the noise control filter M 4  are updated every two or more processing cycles (hereinafter referred to as “block”) in the second embodiment. Furthermore, the number of updating of the coefficients of the noise control filter M 4  is also limited in the second embodiment. 
     [2-2. Process] 
     The control circuit  441  in the second embodiment executes a coefficient update process illustrated in  FIG. 15  in place of the coefficient update process illustrated in  FIG. 13 . In  FIG. 15 , the same processes as those illustrated in  FIG. 13  are given the same step numbers as in  FIG. 13 . Descriptions of the same processes as in  FIG. 13  will be not repeated here. The control circuit  441  includes an update number counter and a block calculation counter. In the following descriptions, the value of the update number counter will be referred to as “first counter value kc”, and the value of the block calculation counter will be referred to as “second counter value jc” The control circuit  441 , when being activated, initializes the first and second counter values kc, jc (for example, sets to zero). The control circuit  441 , when being activated, also initializes a first accumulated value SR and a second accumulated value SS (for example, sets to zero). 
     The control circuit  441  initiates the coefficient update process, and in S 200  determines whether the first counter value kc is smaller than Kmax. Kmax corresponds to the upper limit to the number of updating, that is, the upper limit to the number of times to update the coefficients. If the first counter value kc is at or above Kmax, the control circuit  441  terminates the coefficient update process. If the first counter value kc is smaller than Kmax, the control circuit  441  proceeds to S 210 . 
     The process of S 210  is the same as in the first embodiment. 
     In S 222 , the control circuit  441  calculates the normalized value R n  as in S 220  in  FIG. 13 . In S 222 , the control circuit  441  further calculates the first accumulated value SR. The first accumulated value SR corresponds to an accumulated value of the normalized value R n . The control circuit  441  cumulatively adds the normalized value R n  calculated in S 222  every time it executes the process of S 222 . 
     The process of S 230  is the same as in the first embodiment. 
     In S 242 , the control circuit  441  calculates the gradient vector S(n) as in S 240  in  FIG. 13 . In S 242 , the control circuit  441  further calculates the second accumulated value SS. The second accumulated value SS corresponds to an accumulated value SS of the gradient vector S(n). The control circuit  441  cumulatively adds the gradient vector S(n) calculated in S 242  every time it executes the process of S 242 . 
     In S 244 , the control circuit  441  increments the second counter value jc by one. 
     In S 246 , the control circuit  441  determines whether the second counter value jc is at or above J BK . J BK  corresponds to a block calculation number, that is, the number of processing cycles in one block. In response to a determination that the second counter value jc is smaller than J BK , the control circuit  441  terminates the coefficient update process. In response to a determination that the second counter value jc is at or above J BK , the control circuit  441  proceeds to S 250 . 
     The process of S 250  is the same as in the first embodiment. However, the first accumulated value SR is used in place of the normalized value R n , and the second accumulated value SS is used in the place of the gradient vector S(n) in Formula (4). 
     In S 260 , the control circuit  441  resets the second counter value jc to zero and increments the first counter value kc by one. After the process of S 260 , the control circuit  441  terminates the coefficient update process. 
     That is, the control circuit  441  updates the noise control filter M 4  every block (specifically, once in J BK  processing cycles) using the first and second accumulated values SR, SS calculated in that block. Update of the noise control filter M 4  ends in response to the noise control filter M 4  being updated Kmax times. 
     Each of the values J BK  and Kmax may be set to, for example, a value that renders the error signal e n  sufficiently small. The values J BK  and Kmax may be set based on experimental results of, for example, simulation. 
     [2-3. Correspondence of Terms] 
     In the second embodiment, the process of the coefficient update illustrated in  FIG. 15  except S 210  corresponds to one example of the characteristics adjustor of the present disclosure. 
     [2-4. Effects] 
     According to the second embodiment described in detail above, the following effects are achieved in addition to the effects (1a), (1b), and (1c) of the first embodiment. 
     (2a) In the second embodiment, the first and second accumulated values SR, SS are used for updating the coefficient vector w(n) of the noise control filter M 4 . Even if the normalized value R n  and/or the gradient vector S(n) momentarily indicate faulty values (or indicates a faulty value) due to a disturbance, this configuration limits the influence thereof, thereby improving the stability of the coefficient vectors w(n) that are updated. 
     (2b) In the second embodiment, the number of updating of coefficient vector w(n) of the noise control filter M 4  is limited to Kmax. This inhibits the updates of the coefficient vector w(n) from being continued unnecessarily after convergence of the values of the coefficient vector w(n). The coefficient vector w(n), however, may be updated any number of times without a limit. 
     3. Third Embodiment 
     [3-1. Differences from First Embodiment] 
     In a third embodiment, the basic configurations are the same as in the second embodiment. Thus, the differences from the second embodiment will be described in the third embodiment. In the third embodiment, the same numeral references as in the second embodiment indicate identical configurations to those in the second embodiment, and earlier descriptions should be referred to for such configurations. 
     In the first and second embodiments, the update step size μ used for updating the coefficient vector w(n) of the noise control filter M 4  is a fixed value, while, in the third embodiment, the update step size μ is variably set. Moreover, in the third embodiment a divergence tendency is determined based on variations in the update step size μ. 
     [3-2. Process] 
     [3-2-1. Coefficient Update Process] 
     The noise control circuit  10  in the third embodiment executes a coefficient update process illustrated in  FIG. 16  in place of the coefficient update process illustrated in  FIG. 15 . 
     As illustrated in  FIG. 16 , the control circuit  441  executes a coefficient/step size update process in S 252  in the coefficient update process of the third embodiment in place of S 250  (see  FIG. 15 ) in response to an affirmative determination in S 246 . 
     [3-2-2. Coefficient/Step Size Update Process] 
     Referring now to  FIG. 17 , details of the coefficient/step size update process in S 252  will be described. 
     In response to an initiation of the coefficient/step size update process in  FIG. 17 , the control circuit  441  calculates a disturbance power Q kc  and a signal power P kc  per block in S 410 . The disturbance power Q kc  corresponds to the power of noise except the target noise. The signal power P kc  corresponds to the power of the target noise. The disturbance power Q kc  may be, for example, a value obtained by accumulating (adding) the square of the error signal e n  of each processing cycle in one block. The signal power P kc  may be a value that is obtained by accumulating (adding) the sum of the squares of the reference signal x n  included in the reference vector x(n) of each processing cycle in one block. 
     In S 420 , the control circuit  441  updates an update step size μ kc  in accordance with Formula (17) where I TP  is the number of taps in the noise control filter M 4 , J BK  is a block length, and GX is a necessary value for an estimation error. An example of the estimation error is the second order system estimation error Δ(z). The necessary value GX is a parameter to determine the minimum accuracy in the estimation error. The necessary value GX may take a value of, for example, 1&gt;GX&gt;0. The initial value GX 0  of the necessary value GX is any given value. The initial value GX 0  is set to, for example, a value close to one (for example, 0.9). 
     
       
         
           
             
               
                 
                   
                     μ 
                     
                       k 
                       ⁢ 
                       c 
                     
                   
                   = 
                   
                     
                       2 
                       · 
                       GX 
                       · 
                       
                         P 
                         
                           k 
                           ⁢ 
                           c 
                         
                       
                       · 
                       
                         J 
                         BK 
                       
                     
                     
                       
                         
                           Q 
                           
                             k 
                             ⁢ 
                             c 
                           
                         
                         · 
                         
                           I 
                           TP 
                         
                       
                       + 
                       
                         
                           P 
                           
                             k 
                             ⁢ 
                             c 
                           
                         
                         · 
                         GX 
                       
                     
                   
                 
               
               
                 
                   ( 
                   17 
                   ) 
                 
               
             
           
         
       
     
     In S 430 , the control circuit  441  updates the coefficient vector w(kc) of the noise control filter M 4 . The difference between S 430  and S 250  (see  FIG. 13 ) is that μ kc , which is calculated in S 420 , is used as the update step size in place of the fixed value μ. 
     In S 440 , the control circuit  441  calculates a coefficient variation D kc . The coefficient variation D kc  corresponds to the change in the magnitude of the coefficient vector w(kc) of the noise control filter M 4  updated in S 430  (specifically, the change amount from the coefficient vector immediately before the change). The magnitude of the coefficient vector w(kc) may be, for example, the sum of the squares of all the elements of the coefficient vector w(kc), or may be the sum of the absolute values of all the elements. 
     In S 450 , the control circuit  441  determines whether the coefficient variation D kc  is above a specified determination threshold TH. If the coefficient variation D kc  is at or below the determination threshold TH, the control circuit  441  terminates the coefficient/step size update process. If the coefficient variation D kc  is above the determination threshold TH, the control circuit  441  proceeds to S 460 . 
     In S 460 , the control circuit  441  updates a necessary value GX and the determination threshold TH in accordance with Formulae (18) and (19). Each of the necessary value GX and the determination threshold TH is a parameter used for changing the update step size μ kc . 
         GX←a   GX   ·GX   (18)
 
         TH←b   TH   ·TH   (19)
 
     The term a GX  is a necessary value adjustment coefficient and is set to 1&gt;a GX &gt;0. The term b TH  is a threshold adjustment coefficient and is set to 1&gt;b TH &gt;0. The necessary value adjustment coefficient a GX  and the threshold adjustment coefficient b TH  are set such that changes in the necessary value GX and the determination threshold TH are small. Specifically, each of the necessary value adjustment coefficient a GX  and the threshold adjustment coefficient b TH  is set to, for example, a value close to one (such as 0.9). 
     As described above, in the coefficient/step size update process, the coefficient vector w(kc) of the noise control filter M 4  is updated. In the coefficient/step size update process, the update step size μ kc , which is used for calculating the coefficient vector w(kc), is also updated. Furthermore, the necessary value GX and the determination threshold TH, which are used for adjusting the update step size μ kc , are adjusted in the coefficient/step size update process. The necessary value GX and the determination threshold TH are used for adjusting the update step size μ kc . 
     Adjustment of the necessary value GX and the determination threshold TH is performed when the variation D kc  of the coefficient vector w(kc) is larger than the determination threshold TH (specifically, when the coefficient vector w(kc) indicates a divergence tendency). Specifically, for every affirmative determination in S 450 , the necessary value GX and the determination threshold TH are changed to values smaller than the respective present values. 
     As the necessary value GX becomes smaller, the update step size μ kc  to be obtained becomes smaller, rendering the variation D kc  in the coefficient vector w(kc) also smaller. This inhibits a divergence. However, a small variation D kc  hinders a detection of a divergence tendency. In this case, there is possibility that a divergence tendency cannot be detected despite a state where the divergence tendency continues. Thus, the necessary value GX and the determination threshold TH are adjusted in the third embodiment such that the determination threshold TH is decreased in response to a decrease in the necessary value GX. 
     [3-2-3. Divergence Determination Process] 
     Referring now to  FIG. 18 , the divergence determination process in S 140  (see  FIG. 12 ) executed by the control circuit  441  of the third embodiment will be described. The control circuit  441  of the third embodiment executes in S 140  the divergence determination process illustrated in  FIG. 18  in place of the divergence determination process in  FIG. 14 . 
     In response to an initiation of the divergence determination process illustrated in  FIG. 18 , the control circuit  441  determines in S 510  whether the number of enabled taps I TP  of the noise control filter M 4  is larger than a lower limit Tpmin of enabled taps. The number of enabled taps I TP  is the number of taps of the noise control filter M 4  to be updated by the coefficient updater M 6 . The lower limit Tpmin is set to, for example, the number of taps N of the second order system filter M 5  or smaller. However, the lower limit Tpmin may be set to a value larger than the number of taps N of the second order system filter M 5 . In response to a determination that the number of enabled taps I TP  is at or below the lower limit Tpmin, the control circuit  441  terminates the divergence determination process. In response to a determination that the number of enabled taps I TP  is larger than the lower limit Tpmin, the control circuit  441  proceeds to S 520 . 
     In S 520 , the control circuit  441  determines, as in S 330  (see  FIG. 14 ), whether the coefficients of the noise control filter M 4  indicate a divergence tendency. For determination in S 520 , the control circuit  441  may use, other than the first to third determination parameters, the coefficient variation D kc  calculated in S 440  and a variation in the update step size μ kc  (for example, the absolute value |μ kc −μ kc-1 | of the difference from the previous value) calculated in S 420 . In this case, the control circuit  441  may determine a divergence tendency in response to, for example, one of or both of the coefficient variation D kc  and the variation in the update step size μ kc  being larger than the respective tolerances. 
     In S 530 , the control circuit  441  reduces the number of enabled taps I TP  of the noise control filter M 4  by an adjustment amount ΔI Tp  (for example, 50). Specifically, for example, out of the enabled taps, the lowest-order tap and above are disabled as many as the number corresponding to the adjustment amount ΔI TP . After the process of S 530  is executed, the control circuit  441  terminates the divergence determination process. 
     In the noise control filter M 4  of the third embodiment, I TP  taps from the first to I TP   th  taps are enabled tap while L-I TP  taps from the I TP +1 th  to L th  taps are disabled. 
     In the noise control filter coefficient vector update process in S 430 , the coefficients of the enabled taps are updated and the coefficients of the disabled taps are set to fixed values. In the noise control filter process in S 120 , the disabled taps may be used for calculating the control signal u n , or the disabled taps do not have to be used for such calculation. 
     In the third embodiment, if the variation in the update step size μ kc  is larger than the tolerance, it is determined that the coefficient vector w(kc) of the noise control filter M 4  indicates a divergence tendency. In response to every determination of a divergence tendency, the number of enabled taps of the noise control filter M 4  is reduced by the adjustment amount ΔI TP  from the lower-order side in S 530 . 
     If the update step size μ kc  calculated in one process cycle is large, the coefficient vector w(kc) of the noise control filter M 4  is determined to indicate a divergence tendency. Thus, the error signal e kc  to be detected in the subsequent processing cycle is large. In this case, the update step size μ kc  to be calculated in the subsequent processing cycle is small as it can be understood from Formula (17). This suppresses the divergence. The same course will be repeated. In other words, a divergence tendency and suppression thereof will be repeated. This repetition causes fluctuation in the update step size μ kc , thereby making it possible to determine whether the system is in a divergence tendency based on the fluctuation in the update step size μ kc . 
     [3-3. Correspondence of Terms] 
     In the third embodiment, the process of the coefficient update illustrated in  FIG. 16  except S 210  and the process of S 530  correspond to one example of the characteristics adjustor of the present disclosure. The process of S 520  corresponds to one example of the divergence determiner of the present disclosure. 
     [3-4. Effects] 
     According to the third embodiment described in detail above, the following effects are achieved in addition to the effects (1a), (1b), and (1c) of the first embodiment and the effects (2a) and (2b) of the second embodiment. 
     (3a) In the third embodiment, the so-called step size control is used. Specifically, the update step size μ kc  is changed in accordance with the converging state of the coefficient vector w(kc) of the noise control filter M 4 . Accordingly, it is possible to decrease the estimation error of the coefficient vector w(kc) of the noise control filter M 4  to the necessary value GX or smaller, even under a situation where the disturbance power Q kc  is fluctuating. 
     (3b) In the third embodiment, if the variation in the update step size μ kc  exceeds the tolerance, the adjustment in the number of enabled taps of the noise control filter M 4  in S 530  (specifically, disabling taps by the adjustment amount ΔI TP ) is repeated until the update step size μ kc  stabilizes. Accordingly, it is possible to stably update the coefficient vector w(kc) of the noise control filter M 4  even under a situation where the disturbance power Q kc  is fluctuating. 
     (3c) In the third embodiment, the necessary value GX and the determination threshold TH are decreased in a step-by-step manner until the changes in the coefficient vector w(kc) converge and the coefficient vector w(kc) stabilizes. Accordingly, it is possible to converge the necessary value GX and thus the update step size μ kc  to respective appropriate values that enable the noise control filter M 4  to operate in a stable manner. 
     4. Fourth Embodiment 
     [4-1. Differences from First Embodiment] 
     The differences of the fourth embodiment from the first embodiment lie in the work machine to which the noise controller  10  is applied and the control model of ANC used in the noise control device  10 . 
     [4-2. Configuration of Cleaner] 
     A handheld vacuum cleaner  8 , which is another example of the electric powered work machine of the present disclosure, will be described. In the fourth embodiment, the noise controller  10  is installed in the handheld vacuum cleaner  8 . The handheld vacuum cleaner  8  is used while being held by a user of the handheld vacuum cleaner  8 . The handheld vacuum cleaner  8  is one embodiment of rechargeable electric cleaners. 
     For convenience of description, the direction (front, back, up, down, left, and right) with respect to the handheld vacuum cleaner  8  is defined as illustrated in  FIGS. 19 to 21  in the fourth embodiment. 
     As illustrated in  FIGS. 19 to 21 , the handheld vacuum cleaner  8  includes a main body housing  80 . The main body housing  80  includes a suction port  81 , a discharge port  82 , a handle  83 , a first and a second battery attachment portions  84 A,  84 B. 
     The suction port  81  is disposed in the front portion of the main body housing  80 . The suction port  81  has a cylindrical shape. The suction port  81  sucks external air. The discharge port  82  is provided in the lower rear portion of the main body housing  80 . The discharge port  82  has the shape of slits. The discharge port  82  discharges air with dust removed therefrom. The handle  83  is provided on the upper surface of the main body housing  80  and held by the user. The handle  83  is provided with an electronic switch  85 . The user can manipulate the electronic switch  85  while holding the handle  83 . The first and second battery attachment portions  84 A,  84 B are provided on the upper side of the back surface of the main body housing  80 . To the first battery attachment portion  84 A, a first battery pack  86 A is attached. To the second battery attachment portion  84 B, a second battery pack  86 B is attached. 
     Inside the main body housing  80 , a drive unit  90  and a control circuit board  91  are provided. 
     In the main body housing  80 , the drive unit  90  is provided between the suction port  81  and the discharge port  82 . The drive unit  90  is arranged to partition the internal space of the main body housing  80  into a first space  80   a  and a second space  80   b . In the first space  80   a , a dust bag (not illustrated) is placed. The main body housing  80  includes an inner wall  95  forming the second space  80   b  and a sound absorbing material  87 . The sound absorbing material  87  is provided on the inner wall  95 . The sound absorbing material  87  may be a sponge, for example. The main body housing  80  includes a control speaker  88  and an error microphone  89  that are arranged on top of the sound absorbing material  87 . 
     Each of the control speaker  88  and the error microphone  89  is mounted such that each of the control speaker  88  and the error microphone  89  is directional toward the second space  80   b , and is mounted facing the second space  80   b  with the sound absorbing material  87  provided therebetween. The error microphone  89  is situated such that the airflow does not reach the error microphone  89  inside the main body housing  80 . 
     The error microphone  89  is arranged at a position where an antinode of a standing wave of a noise generated in the internal space of the main body housing  80  is located. The position where the error microphone  89  is provided is the canceling location (or can be considered as the canceling location). The cross-sectional areas of the flow path of the airflow inside the main body housing  80  discontinuously vary (specifically, the flow path suddenly expands) at the discharge port  82 . The discontinuous variation in the cross-sectional areas of the flow path causes reflection of the noise at the discharge port  82 . The standing wave of the noise is produced due to the reflection. 
     Basically, the control speaker  88  has the same capacity of that of the control speaker  54  in the first embodiment, and the error microphone  89  has the same capacity of that of the error microphone  55  in the first embodiment. The control speaker  88  and the error microphone  89  are disposed based on the same idea as that for the disposition of the control speaker  54  and the error microphone  55  in the first embodiment. 
     As illustrated in  FIG. 20 , the drive unit  90  includes a motor housing  901 , a motor  902 , and a fan  903 . 
     The motor housing  901  is in contact with the inner wall of the main body housing  80 . The motor housing  901  has a cylindrical shape. The motor  902  is disposed almost at the center of the motor housing  901 . This arrangement provides a flow path  80   c  between the motor  902  and the motor housing  901 . The flow path  80   c  has an annular cross-section. 
     The motor  902  is driven in accordance with an instruction from the control circuit board  91 . The motor  902  in the fourth embodiment is a direct-current motor. 
     The fan  903  is fixed to the rotor of the motor  902 . 
     The drive unit  90  is situated such that the motor  902  faces the first space  80   a  and the fan  903  faces the second space  80   b  inside the main body housing  80 . The drive unit  90  generates airflow inside the main body housing  80 . The airflow is directed from the suction port  81  to the discharge port  82 . The airflow is generated by rotation of the fan  903  driven by the motor  902 . 
     Generation of the airflow by the drive unit  90  causes external air to be introduced into the internal space of the main body housing  80  through the suction port  81 . The introduced external air passes through the first space  80   a . In the first space  80   a , the external air passes through the dust bag, leaving grit and dust contained in the external air trapped and collected inside the dust bag. The air that passes through the dust bag flows through the flow path  80   c , then reaching the second space  80   b . The air that reaches the second space  80   b  is discharged from the discharge port  82 . 
     [4-3. Control Circuit Board] 
     The control circuit board  91  is operated in response to power supply from the first battery pack  86 A and/or the second battery pack  86 B. The control circuit board  91  includes a motor controller  911  and a noise controlling portion  912 . The motor controller  911  drives the motor  902  in response to manipulation of the electronic switch  85 . The noise controlling portion  912  reduces a target noise. The target noise in the fourth embodiment is the noise generated by operation of the motor  902 . 
     The motor controller  911  includes a configuration that corresponds to the dust collection circuit group  442  and the control circuit  441  illustrated in  FIG. 8 . 
     The handheld vacuum cleaner  8  includes a noise controller  100  (see  FIG. 22 ). The noise controller  100  includes the noise controlling portion  912 , the control speaker  88 , and the error microphone  89 . 
     The noise controlling portion  912  includes a configuration that corresponds to the second A/D converter  445 , the D/A converter  446 , and the control circuit  441  illustrated in  FIG. 8 . The noise controlling portion  912 , together with the control speaker  88  and the error microphone  89 , achieves feedback ANC. In other words, the noise controller  100  reduces the target noise by the feedback ANC as in the noise controller  10  in the first to third embodiments. 
     [4-4. ANC Model] 
     Referring now to  FIG. 22 , a feedback ANC model achieved by the noise controller  100  in the fourth embodiment will be described. The noise controller  100  can be represented by the control model illustrated in  FIG. 22 . Part of the feedback ANC model in the fourth embodiment is common to the feed-forward ANC model in the first embodiment illustrated in  FIG. 9 . Thus, the same configurations as in the first embodiment will be given the same reference numerals as in the first embodiment. 
     In comparison with the feed-forward ANC model, the feedback ANC model includes, as illustrated in  FIG. 22 , no reference sensor M 1  but additionally includes an arrival filter M 7  and an adder M 8 . The control sound source M 2  corresponds to the control speaker  88  and the D/A converter  446  (see  FIG. 8 ). The error sensor M 3  corresponds to the error microphone  89  and the second A/D converter  445  (see  FIG. 8 ). 
     The noise controlling portion  912  may include a microcomputer. In this case, the noise control filter M 4 , the second order system filter M 5 , the coefficient updater M 6 , the arrival filter M 7 , and the adder M 8  may be achieved by software processing by the microcomputer, or may be partly or entirely achieved by hardware. 
     The arrival filter M 7  includes the same configuration as that of the second order system filter M 5 . The arrival filter M 7  estimates an artificial noise arrival signal an from N control signals u n  (specifically, N-dimensional control vector u(n)) that are most recently calculated. The artificial noise arrival signal a n  indicates an artificial noise that has arrived at the error sensor M 3  from the control sound source M 2 . 
     The adder M 8  estimates the reference signal x n  indicating the target noise. 
     Specifically, the adder M 8  estimates (specifically, calculates) the reference signal x n  by subtracting the error signal e n  from the artificial noise arrival signal a n . 
     In other words, the estimated results based on the control signal u n  and the error signal e n  are used as the reference signal x n  in the feedback ANC, in place of the results of the detection by the reference sensor M 1 . 
     [4-5. Process] 
     The process executed by the noise controlling portion  912  is basically the same as the process described in any one of the first to third embodiments. 
     However, the process of S 110  in the noise reduction process (see  FIG. 12 ) is different in the fourth embodiment from the process in the first to third embodiments. Specifically, the artificial noise arrival signal a n  is generated by the arrival filter M 7  in S 110  in the fourth embodiment. Moreover, the error signal e n  is subtracted from the artificial noise arrival signal a n  to generate the reference signal x n  in S 110 . 
     [4-6. Correspondence of Terms] 
     In the fourth embodiment, the adder M 8  corresponds to one example of the adder in the present disclosure. 
     [4-7. Effects] 
     According to the fourth embodiment described in detail above, the following effects are achieved in addition to the effects (1a), (1b), and (1c) of the first embodiment, the effects (2a) and (2b) of the second embodiment, and the effects (3a), (3b), and (3c) of the third embodiment. 
     (4a) In the fourth embodiment, the feedback ANC is used. This allows omission of the reference sensor M 1 , thereby simplifying the configuration of the noise controller  100 . 
     [5. Other Embodiments] 
     (5-1) In the first to fourth embodiments, the number of taps L of the noise control filter M 4  is set larger than the number of taps N of the second order system filter M 5 . When a divergence tendency is detected, the taps whose coefficients are updated (enabled taps) are limited to M taps from the highest-order in the noise control filter M 4 . However, it is only one embodiment of the present disclosure to change the number of enabled taps in the noise control filter M 4  from L to M based on detection of a divergence tendency. For example, the number of taps in the noise control filter M 4  may be initially fixed to M. In this case, it is possible to omit the process to limit the number of enabled taps based on detection of a divergence tendency. It is also possible in this case to omit the divergence determination process in S 140  of the noise reduction process illustrated in  FIG. 12 . 
     (5-2) In the first to third embodiments, the signal detected by the reference microphone  53  is used as the reference signal x n  in the process of S 110 . However, the reference signal x n  is not limited to the signal detected by the reference microphone  53 . The reference signal x n  may be any signal that has a correlation with the target noise. The reference signal x n  may be, for example, a signal for driving the motor  432  (for example, a drive signal outputted from the control circuit  441  to the dust collection circuit group  442 ) or a signal corresponding or related to such a signal. 
     (5-3) The control speaker  54  and the error microphone  55  in the first to third embodiments are arranged such that they face the same direction and aligned with each other. However, the control speaker  54  and the error microphone  55  may be arranged in any specific manner. For example, the control speaker  54  and the error microphone  55  may be arranged facing each other. The control speaker  88  and the error microphone  89  in the fourth embodiment may also be arranged in any specific manner. 
     (5-4) In the third embodiment, the block length J BK  is constant. However, if fluctuations in the signal power P kc  are expected, the block length J BK  may be changed. In this case, a control may be performed to, for example, extend the block length J BK  until the signal power P kc  becomes a constant value. 
     (5-5) In the first to fourth embodiments, the dust collector  1  and the handheld vacuum cleaner  8  are described as examples of the electric powered work machine with the techniques of the present disclosure. However, the present disclosure may be applied not only to the dust collector  1  and the handheld vacuum cleaner  8 , but also to other electric powered work machines. The present disclosure may be applied to, for example, various jobsite electric apparatuses that are used at jobsites, such as do-it-yourself carpentry, manufacturing, gardening, and construction sites, and those that utilize airflow generated with a fan. Specifically, the techniques of the present disclosure may be applied to various electric powered work machines such as machinery for gardening and devices for creating pleasant jobsite environment. More specifically, the present disclosure may be applied to various electric powered work machines such as electric lawn mowers, electric lawn trimmers, electric bush/grass cutters, electric cleaners, electric blowers, electric sprayers, electric spreaders, and electric dust collectors. 
     (5-6) Functions of one component in the above-described embodiments may be achieved by two or more components, and a function of one component may be achieved by two or more components. Moreover, functions of two or more components may be achieved by one component, and a function achieved by two or more components may be achieved by one component. Some of the components of the above-described embodiments may be omitted. At least part of the configurations of the above-described embodiments may be added to or replaced with other configurations of the above-described embodiments.