Patent Publication Number: US-2022221432-A1

Title: Analysis device, analysis system, and analysis method

Description:
CROSS-REFERENCE TO RELATED APPLICATION(S) 
     The present application claims priority to and incorporates by reference the entire contents of Japanese Patent Application No. 2021-003764 filed in Japan on Jan. 13, 2021. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present disclosure relates to an analysis device, an analysis system, and an analysis method. 
     2. Description of the Related Art 
     For diagnosis of the presence/absence of abnormality in a machine, a technology is known to detect a vibration generated during the operation of the machine, with a vibration sensor (e.g., JP 2009-020090 A). For calculation that is effective in monitoring and analyzing vibration of the machine, a peak value, effective value (root mean square value (RMS)), and overall value of acceleration, and a crest factor (CF) obtained by dividing the peak value by the effective value are used. In order to obtain these values, a maximum value of an absolute value, root mean square, quadratic mean of waveform data of vibration acquired by an acceleration sensor are used, and calculation for dividing the maximum value of the absolute value by the root mean square is performed. 
     Incidentally, the effective value and the overall value are average values. Therefore even if there is a variation in repeated measurement, a calculation result has a small margin of error. Meanwhile, the peak value is one point on the acquired waveform. Therefore, when there is a variation in repeated measurement, the calculation result may have a large margin of error. For example, a method of reducing the variation by taking an average of several top points from a maximum peak value is conceivable, but when the maximum peak value is significantly larger than the other values, the variation is large, and there is still a possibility that the margin of error in the calculation result may be large. The crest factor that is particularly important to monitor the state of the machine depends on the peak value, and when the margin of error in the peak value is large, there is a problem that monitoring the state of the machine is adversely affected. 
     An object of the present disclosure is to output a stable calculation result. 
     SUMMARY OF THE INVENTION 
     It is an object of the present invention to at least partially solve the problems in the conventional technology. 
     According to an aspect of the present invention, an analysis device comprises: a vibration sensor that detects vibration of a machine; a calculation unit that performs calculation to define a peak value based on a standard deviation of detection data of the vibration sensor; and a wireless communication device that transmits processed data output from the calculation performed by the calculation unit. 
     The above and other objects, features, advantages and technical and industrial significance of this invention will be better understood by reading the following detailed description of presently preferred embodiments of the invention, when considered in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a cross-sectional view schematically illustrating an analysis device according to a first embodiment. 
         FIG. 2  is a perspective view schematically illustrating a thermoelectric generation module according to the first embodiment. 
         FIG. 3  is a block diagram illustrating the analysis device according to the first embodiment. 
         FIG. 4  is a flowchart illustrating an analysis method according to the first embodiment. 
         FIG. 5  is a graph illustrating an example of detection data in the analysis method according to the first embodiment. 
         FIG. 6  is a diagram illustrating a histogram of  FIG. 5 . 
         FIG. 7  is a graph illustrating a method of defining a peak value in the analysis method according to the first embodiment. 
         FIG. 8  is a diagram schematically illustrating an analysis system according to a second embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Embodiments according to the present disclosure will be described below with reference to the drawings, but the present disclosure is not limited to the description. Component elements according to the embodiments described below may be appropriately combined with each other. Furthermore, some of the component elements are not used in some cases. 
     In the embodiments, an XYZ orthogonal coordinate system is set, and positional relationships between functional units will be described with reference to the XYZ orthogonal coordinate system. A direction parallel to an X-axis in a predetermined plane is represented as an X-axis direction, a direction parallel to a Y-axis orthogonal to the X-axis in the predetermined plane is represented as a Y-axis direction, and a direction parallel to a Z-axis orthogonal to the predetermined plane is represented as a Z-axis direction. An XY plane, including the X- and Y-axes, is parallel to the predetermined plane. 
     First Embodiment 
     Analysis Device 
       FIG. 1  is a cross-sectional view schematically illustrating an analysis device  1  according to the present embodiment. The analysis device  1  is installed on a machine B. The machine B is provided in an industrial facility such as a factory. An example of the machine B includes a rotary machine. An example of the rotary machine includes a motor that operates a pump. 
     As illustrated in  FIG. 1 , the analysis device  1  includes a heat reception portion  2 , a heat release portion  3 , a peripheral wall portion  4 , a thermoelectric generation module  5 , a vibration sensor  6 , a microcomputer  8 , a wireless communication device  9 , a heat transfer member  10 , a circuit board  11 , and a power storage unit  14 . 
     The heat reception portion  2  is installed on the machine B. The heat reception portion  2  is a plate-shaped member. The heat reception portion  2  is formed of a metal material such as aluminum or copper. The heat reception portion  2  receives heat from the machine B. The heat of the heat reception portion  2  is transferred to the thermoelectric generation module  5  via the heat transfer member  10 . 
     The heat release portion  3  is opposed to the heat reception portion  2  with a space therebetween. The heat release portion  3  is a plate-shaped member. The heat release portion  3  is formed of a metal material such as aluminum or copper. The heat release portion  3  receives heat from the thermoelectric generation module  5 . The heat of the heat release portion  3  is released into ambient air around the analysis device  1 . 
     The heat reception portion  2  has a heat reception surface  2 A that is opposed to a surface of the machine B and an inside surface  2 B that faces in a direction opposite to the heat reception surface  2 A. The heat reception surface  2 A faces in a −Z direction. The inside surface  2 B faces in a +Z direction. Each of the heat reception surface  2 A and the inside surface  2 B has a flat shape. Each of the heat reception surface  2 A and the inside surface  2 B is parallel to the XY plane. In the XY plane, the heat reception portion  2  has substantially a square outer shape. Note that the heat reception portion  2  may not have the square outer shape. The heat reception portion  2  may have a circular, elliptical, or any polygonal outer shape. 
     The heat release portion  3  has a heat release surface  3 A that faces the ambient air and an inside surface  3 B that faces in a direction opposite to the heat release surface  3 A. The heat release surface  3 A faces in the +Z direction. The inside surface  3 B faces in the −Z direction. Each of the heat release surface  3 A and the inside surface  3 B has a flat shape. Each of the heat release surface  3 A and the inside surface  3 B is parallel to the XY plane. In the XY plane, the heat release portion  3  has substantially a square outer shape. Note that the heat release portion  3  may not have the square outer shape. The heat release portion  3  may have a circular, elliptical, or any polygonal outer shape. 
     In the XY plane, the heat reception portion  2  and the heat release portion  3  are substantially equal in outer shape and size. Note that the outer shape and size of the heat reception portion  2  and the outer shape and size of the heat release portion  3  may be different from each other. 
     The peripheral wall portion  4  is arranged between a peripheral edge portion of the inside surface  2 B of the heat reception portion  2  and a peripheral edge portion of the inside surface  3 B of the heat release portion  3 . The peripheral wall portion  4  connects the heat reception portion  2  and the heat release portion  3 . The peripheral wall portion  4  is formed of a synthetic resin. 
     In the XY plane, the peripheral wall portion  4  has an annular shape. In the XY plane, the peripheral wall portion  4  has substantially a square outer shape. The heat reception portion  2 , the heat release portion  3 , and the peripheral wall portion  4  define an inner space  12  of the analysis device  1 . The peripheral wall portion  4  has an inside surface  4 B that faces the inner space  12 . The inside surface  2 B of the heat reception portion  2  faces the inner space  12 . The inside surface  3 B of the heat release portion  3  faces the inner space  12 . The outer space of the analysis device  1  is the ambient air around the analysis device  1 . 
     The heat reception portion  2 , the heat release portion  3 , and the peripheral wall portion  4  function as a housing of the analysis device  1  that defines the inner space  12 . In the following description, the heat reception portion  2 , the heat release portion  3 , and the peripheral wall portion  4  are collectively referred to as a housing  20  appropriately. 
     A sealing member  13 A is arranged between the peripheral edge portion of the inside surface  2 B of the heat reception portion  2  and an end surface on the −Z side of the peripheral wall portion  4 . A sealing member  13 B is arranged between the peripheral edge portion of the inside surface  3 B of the heat release portion  3  and an end surface on the +Z side of the peripheral wall portion  4 . Each of the sealing member  13 A and the sealing member  13 B includes, for example, an O-ring. The sealing member  13 A is arranged in a recess provided in the peripheral edge portion of the inside surface  2 B. The sealing member  13 B is arranged in a recess provided in the peripheral edge portion of the inside surface  3 B. The sealing member  13 A and the sealing member  13 B inhibit foreign matter in the outer space of the analysis device  1  from entering the inner space  12 . 
     The thermoelectric generation module  5  uses a Seebeck effect to generate power. The machine B functions as a heat source for the thermoelectric generation module  5 . The thermoelectric generation module  5  is arranged between the heat reception portion  2  and the heat release portion  3 . An end surface  51  on the −Z side of the thermoelectric generation module  5  is heated, a temperature difference is generated between the end surface  51  on the −Z side and an end surface  52  on the +Z side of the thermoelectric generation module  5 , and thereby the thermoelectric generation module  5  generates power. 
     The end surface  51  faces in the −Z direction. The end surface  52  faces in the +Z direction. Each of the end surface  51  and the end surface  52  has a flat shape. Each of the end surface  51  and the end surface  52  is parallel to the XY plane. In the XY plane, the thermoelectric generation module  5  has substantially a square outer shape. 
     The end surface  52  is opposed to the inside surface  3 B of the heat release portion  3 . The thermoelectric generation module  5  is fixed to the heat release portion  3 . The heat release portion  3  and the thermoelectric generation module  5  are bonded to each other, for example, by adhesive. 
     Note that in the example illustrated in  FIG. 1 , the thermoelectric generation module  5  is in contact with the heat release portion  3  but may be in contact with the heat reception portion  2 . 
     The vibration sensor  6  detects the vibration of the machine B. The vibration sensor  6  is driven by power generated by the thermoelectric generation module  5 . The vibration sensor  6  is arranged in the inner space  12 . In the present embodiment, the vibration sensor  6  is supported on the inside surface  2 B of the heat reception portion  2 . 
     An example of the vibration sensor  6  includes an acceleration sensor. Note that the vibration sensor  6  may be a speed sensor or a displacement sensor. In the present embodiment, the vibration sensor  6  is configured to detect the vibration of the machine B in three directions of the X-axis direction, Y-axis direction, and Z-axis direction. 
     The microcomputer  8  controls the analysis device  1 . The microcomputer  8  is driven by power generated by the thermoelectric generation module  5 . The microcomputer  8  is arranged in the inner space  12 . In the present embodiment, the microcomputer  8  is supported on the circuit board  11 . 
     The wireless communication device  9  communicates with a management computer  100  (see  FIG. 3 , etc.) being outside the analysis device  1 . The wireless communication device  9  is driven by power generated by the thermoelectric generation module  5 . The wireless communication device  9  is arranged in the inner space  12 . In the present embodiment, the wireless communication device  9  is supported on the circuit board  11 . 
     The heat transfer member  10  connects the heat reception portion  2  and the thermoelectric generation module  5 . The heat transfer member  10  transfers the heat of the heat reception portion  2  to the thermoelectric generation module  5 . The heat transfer member  10  is formed of a metal material such as aluminum or copper. The heat transfer member  10  is a rod-shaped member elongated in the Z-axis direction. The heat transfer member  10  is arranged in the inner space  12 . 
     The circuit board  11  includes a control board. The circuit board  11  is arranged in the inner space  12 . The circuit board  11  is connected to the heat reception portion  2  via a support member  11 A. The circuit board  11  is connected to the heat release portion  3  via a support member  11 B. The circuit board  11  is supported by the support member  11 A and the support member  11 B so as to be separated from each of the heat reception portion  2  and the heat release portion  3 . 
     The power storage unit  14  stores power generated by the thermoelectric generation module  5 . An example of the power storage unit  14  includes a capacitor or a secondary battery. 
     Thermoelectric Generation Module 
       FIG. 2  is a perspective view schematically illustrating the thermoelectric generation module  5  according to the present embodiment. As illustrated in  FIG. 2 , the thermoelectric generation module  5  includes p-type thermoelectric semiconductor devices  5 P, n-type thermoelectric semiconductor devices  5 N, first electrodes  53 , second electrodes  54 , a first substrate  51 S, and a second substrate  52 S. In the XY plane, the p-type thermoelectric semiconductor devices  5 P and the n-type thermoelectric semiconductor devices  5 N are arranged alternately. Each of the first electrodes  53  is connected to each of the p-type thermoelectric semiconductor devices  5 P and n-type thermoelectric semiconductor devices  5 N. Each of the second electrodes  54  is connected to each of the p-type thermoelectric semiconductor devices  5 P and the n-type thermoelectric semiconductor devices  5 N. A lower surface of each p-type thermoelectric semiconductor device  5 P and a lower surface of each n-type thermoelectric semiconductor device  5 N are connected to each first electrode  53 . An upper surface of each p-type thermoelectric semiconductor device  5 P and an upper surface of each n-type thermoelectric semiconductor device  5 N are connected to each second electrode  54 . The first electrode  53  is connected to the first substrate  51 S. The second electrode  54  is connected to the second substrate  52 S. 
     Each of the p-type thermoelectric semiconductor device  5 P and the n-type thermoelectric semiconductor device  5 N includes, for example, a BiTe-based thermoelectric material. Each of the first substrate  51 S and the second substrate  52 S is formed of an electrical insulating material such as ceramics or polyimide. 
     The first substrate  51 S has the end surface  51 . The second substrate  52 S has the end surface  52 . In response to heating the first substrate  51 S, a temperature difference is generated between end portions on the +Z side and −Z side of each p-type thermoelectric semiconductor device  5 P and n-type thermoelectric semiconductor device  5 N. In response to generation of the temperature difference between the end portions on the +Z side and −Z side of the p-type thermoelectric semiconductor device  5 P, holes move in the p-type thermoelectric semiconductor device  5 P. In response to generation of the temperature difference between the end portions on the +Z side and −Z side of the n-type thermoelectric semiconductor device  5 N, electrons move in the n-type thermoelectric semiconductor device  5 N. The p-type thermoelectric semiconductor device  5 P and the n-type thermoelectric semiconductor device  5 N are connected via the first electrode  53  and the second electrode  54 . A potential difference is generated between the first electrode  53  and the second electrode  54  due to the holes and the electrons. The thermoelectric generation module  5  generates power due to the potential difference between the first electrode  53  and the second electrode  54 . A lead wire  55  is connected to the first electrode  53 . The thermoelectric generation module  5  outputs power via the lead wire  55 . 
     Microcomputer 
       FIG. 3  is a block diagram illustrating the analysis device  1  according to the present embodiment. As illustrated in  FIG. 3 , the thermoelectric generation module  5 , the power storage unit  14 , the vibration sensor  6 , the microcomputer  8 , and the wireless communication device  9  are housed in one housing  20 . 
     The microcomputer  8  includes a detection data acquisition unit  81 , a calculation unit  82 , and a communication control unit  83 . 
     The detection data acquisition unit  81  acquires detection data of the vibration sensor  6  in a preset measurement time and at a preset sampling frequency (output data rate: ODR). The detection data of the vibration sensor  6  includes a vibration waveform. The measurement time and the sampling frequency need to be set within a range satisfying a condition such as that the sampling points do not exceed an upper limit value that depends on a memory capacity of the microcomputer  8 . 
     The calculation unit  82  causes each unit of the microcomputer  8  to execute a program stored in advance. The calculation unit  82  performs calculation processing on the basis of the detection data of the vibration sensor  6  acquired by the detection data acquisition unit  81 , outputting the processed data. The processed data refers to data generated by performing data processing on the detection data. 
     The calculation unit  82  is configured to process the detection data of the vibration sensor  6  on the basis of a vibration analysis method such as fast Fourier transform (FFT) and output the processed data. Before performing the FFT analysis, the calculation unit  82  may perform processing using high pass filter (HPF) and a low pass filter (LPF) as a band pass filter (BPF). 
     The processed data generated by the calculation unit  82  includes, for example, at least one of a peak value, effective value, frequency, overall value, and crest factor of the vibration of the machine B that are calculated on the basis of the detection data of the vibration sensor  6 . 
     The calculation unit  82  is configured to process the detection data of the vibration sensor  6  to calculate the peak value of the vibration of the machine B. The peak value of the vibration includes a maximum value and a minimum value of the vibration. The peak value of the vibration may be a peak value in the entire range of the vibration waveform or may be a peak value in each of a plurality of frequency ranges of the vibration waveform. The peak value of the vibration may be a peak value of acceleration, a peak value of velocity, or a peak value of displacement. 
     The calculation unit  82  calculates a standard deviation σ of the vibration waveform (e.g., acceleration data) acquired by the detection data acquisition unit  81 . The calculation unit  82  extracts accelerations at respective time points at which the accelerations have absolute values larger than a value nσ obtained by multiplying the standard deviation σ by a coefficient n, and calculates an average value of the absolute values of the extracted accelerations. The calculation unit  82  defines, as a peak value of the vibration the average value of accelerations having absolute values larger than the calculated value nσ. The coefficient n is set in advance. The coefficient n is set within a range of 2≤n≤3. The coefficient n is changeable as appropriate. The coefficient n may be set by an operator, for example, from the management computer  100  via wireless communication. 
     The calculation unit  82  is configured to process the detection data of the vibration sensor  6  to calculate the effective value (root mean square value: RMS) of the vibration of the machine B. Furthermore, the calculation unit  82  may divide the entire range of the vibration waveform detected by the vibration sensor  6  into a plurality of frequency ranges to calculate the effective value for each of the plurality of frequency ranges. The effective value of vibration may be an effective value of acceleration, an effective value of velocity, or an effective value of displacement. 
     The calculation unit  82  is configured to process the detection data of the vibration sensor  6  to calculate the frequency of the vibration of the machine B. Furthermore, the calculation unit  82  is configured to process the detection data of the vibration sensor  6  to calculate the overall value of the vibration. 
     The calculation unit  82  is configured to calculate the crest factor (CF) of the machine B, on the basis of the defined peak value and the calculated effective value. The crest factor refers to a ratio (peak value/effective value) of the peak value to the effective value. For example, in a case where a state of a bearing of the motor of the rotary machine is diagnosed, large crest factor indicates a tendency that the bearing is damaged and impact vibration occurs, and small crest factor indicates a tendency that a load of the motor increases due to poor lubrication of the bearing. 
     The communication control unit  83  causes the wireless communication device  9  to communicate with the management computer  100 . When the wireless communication device  9  receives setting data for setting the coefficient n defining the peak value, from the management computer  100 , the communication control unit  83  outputs the received setting data to the calculation unit  82 . 
     Furthermore, the communication control unit  83  controls the wireless communication device  9  so as to transmit the detection data of the vibration sensor  6  acquired by the detection data acquisition unit  81  to the management computer  100 . The wireless communication device  9  transmits the detection data of the vibration sensor  6  acquired by the detection data acquisition unit  81  to the management computer  100 . 
     Furthermore, when the processed data is output by the calculation unit  82 , the communication control unit  83  controls the wireless communication device  9  so as to transmit the processed data to the management computer  100 . The wireless communication device  9  transmits the processed data calculated by the calculation unit  82  to the management computer  100 . 
     Analysis Method 
       FIG. 4  is a flowchart illustrating an analysis method according to the present embodiment. The machine B on which the analysis device  1  is installed is the motor that is a kind of the rotary machine. The motor operates the pump. In the analysis method of the present embodiment, the peak value, effective value, overall value, and crest factor of the vibration are output as the processed data to diagnose the presence/absence of scratches on the bearing of the motor. 
     In the analysis device  1 , the calculation unit  82  sets the coefficient n for defining the peak value, on the basis of, for example, the setting data set from the management computer  100  via wireless communication (Step S 1 ). 
     The detection data acquisition unit  81  acquires raw data about the vibration waveform, as the detection data, from the vibration sensor  6 . The raw data about the vibration waveform is the acceleration data based on the measurement time and the sampling points sampled with the sampling frequency (ODR), which are set by the calculation unit  82  (Step S 2 ). 
       FIG. 5  is a graph illustrating an example of detection data in the analysis method according to the present embodiment. In  FIG. 5 , the vertical axis represents acceleration [m/s 2 ] detected by the vibration sensor  6 , and the horizontal axis represents time [msec]. 
     In Step S 2  illustrated in  FIG. 4 , the detection data acquisition unit  81  acquires waveform data of the acceleration as illustrated in  FIG. 5 . As illustrated in  FIG. 5 , in the acquired waveform data of the acceleration, the peaks vary in magnitude (maximum values Ph and minimum values Pl). In other words, when the acquired waveform data of the acceleration is processed directly, a calculation result may have a large margin of error. 
     The calculation unit  82  calculates the standard deviation σ of the acceleration data acquired by the detection data acquisition unit  81  in Step S 2  (Step S 3 ). 
       FIG. 6  is a diagram illustrating a histogram of  FIG. 5 . In  FIG. 6 , the vertical axis represents the sampling points, and the horizontal axis represents acceleration [m/s 2 ].  FIG. 7  is a graph illustrating a method of defining the peak value in the analysis method according to the present embodiment. In  FIG. 7 , the vertical axis represents acceleration [m/s 2 ] detected by the vibration sensor  6 , and the horizontal axis represents time [msec]. 
     As illustrated in  FIG. 6 , when the calculation unit  82  divides the acceleration data into a plurality of acceleration ranges and generates the histogram indicating the sampling points for each acceleration range, the histogram of the acceleration has a substantially normal distribution. Note that in the example illustrated in  FIG. 6 , one acceleration range is approximately 100 [m/s 2 ]. 
     The calculation unit  82  extracts accelerations having absolute values larger than the value nσ that is n times the standard deviation σ calculated in Step S 3 , and calculates the average value of the extracted accelerations (Step S 4 ). The calculation unit  82  calculates the average value of the absolute values of all extracted accelerations. The calculation unit  82  defines the average value of accelerations having absolute values larger than the calculated value nσ, as the peak value of the vibration (Step S 5 ). 
     For example, when n=2, the calculation unit  82  calculates the average value of the absolute values of the accelerations included in a portion Pha +2σ  outside a line B +2σ  of the normal distribution illustrated in  FIG. 6  and accelerations included in a portion Pla −2σ  outside a line B −2σ . Therefore, in the waveform data of the acceleration illustrated in  FIG. 7 , the calculation unit  82  defines, as the peak value of the vibration, the average value of the absolute values of the accelerations of points at which the values of the accelerations are B +2σ  or more and accelerations of points at which the values of the accelerations are B −2σ  or less. 
     For example, when n=2.5, the calculation unit  82  calculates the average value of the absolute values of the accelerations included in a portion Pha +2.5σ  outside a line B +2.5σ  of the normal distribution illustrated in  FIG. 6  and accelerations included in a portion Pla −2.5σ  outside a line B −2.5σ . Therefore, in the waveform data of the acceleration illustrated in  FIG. 7 , the calculation unit  82  defines, as the peak value of the vibration, the average value of the absolute values of the accelerations of points at which the values of the accelerations are B +2.5σ  or more and accelerations of points at which the values of the accelerations are B −2.5σ  or less. 
     For example, when n=3, the calculation unit  82  calculates the average value of the absolute values of the accelerations included in a portion Pha +3σ  outside a line B +3σ  of the normal distribution illustrated in  FIG. 6  and accelerations included in a portion Pla −3σ  outside a line B −3σ . Therefore, in the waveform data of the acceleration illustrated in  FIG. 7 , the calculation unit  82  defines, as the peak value of the vibration, the average value of the absolute values of the accelerations of points at which the values of the accelerations are B +3σ  or more and accelerations of points at which the values of the accelerations are B −3σ  or less. 
     The calculation unit  82  processes the detection data of the vibration sensor  6  to calculate the effective value. The calculation unit  82  processes the detection data of the vibration sensor  6  to calculate the overall value. The calculation unit  82  calculates the crest factor, on the basis of the peak value defined in Step S 5  and the calculated effective value (Step S 6 ). 
     The calculation unit  82  causes the wireless communication device  9  to transmit the calculated peak value, effective value, overall value, and crest factor, as the processed data. The wireless communication device  9  transmits the processed data to the management computer  100  (Step S 7 ). 
     The management computer  100  is configured to monitor and manage the state of the machine B, on the basis of the transmitted processed data. The management computer  100  is configured to diagnose the presence/absence of abnormality in the machine B, on the basis of the transmitted processed data. 
     Effects 
     As described above, according to the present embodiments, the vibration sensor  6  is installed on the machine B. The detection data of the vibration sensor  6  is output to the microcomputer  8 . The calculation unit  82  of the microcomputer  8  defines the peak value on the basis of the standard deviation σ of the detection data of the vibration sensor  6 . 
     As described above, defining the peak value from the average value of the range quantitatively extracted by the analysis method of the embodiment makes it possible to quantitatively calculate the peak value and reduce the margin of error of the calculation result. Therefore, even if a reduction in measurement points of the vibration waveform of the detection data or a reduction in measurement time due to the limitation of power or due to the capability of the microcomputer  8  causes a variation in the repeated measurement, a stable calculation result can be output, and the accuracy in monitoring the state of the machine B can be improved. 
     In the embodiment, the processed data output from the calculation performed by the calculation unit  82  is transmitted from the wireless communication device  9  to the management computer  100 . Therefore, the management computer  100  is configured to appropriately diagnose the machine B, on the basis of the peak value quantitatively calculated and each value calculated from the peak value. 
     In the embodiment, the calculation unit  82  defines, as the peak value, the average value of accelerations having the absolute values larger than the value nσ obtained by multiplying the standard deviation σ by the coefficient n, for the detection data of the vibration sensor  6 . The calculation unit  82  is configured to change the coefficient n. In other words, the peak value can be defined on the basis of the value that is coefficient n times the standard deviation σ, and thus, a definition range of the peak is readily changeable according to a diagnosis target or the like. 
     Second Embodiment 
     A second embodiment will be described. In the following description, component elements that are the same as or equivalent to those in the above first embodiment are denoted by the same reference numerals and symbols, and description thereof will be simplified or omitted. 
     Analysis System 
       FIG. 8  is a diagram schematically illustrating an analysis system  200  according to the present embodiment. As illustrated in  FIG. 8 , the analysis system  200  includes a plurality of analysis devices  1  installed on a machine B, a communication device  210 , and a repeater  220 . A plurality of the machines B is provided in the industrial facility. As described above, the example of the machine B includes the motor that operates the pump. The machine B may be installed in the basement. When the machine B operates, the machine B generates heat. The machine B functions as a heat source for the analysis devices  1 . 
     The communication device  210  receives detection data of the vibration sensor  6  transmitted from each of the plurality of analysis devices  1  and processed data output by the calculation unit  82 , via the repeater  220 , and transmits the data to the management computer  100 . The communication device  210  processes, for example, the detection data and the processed data transmitted from each of the plurality of analysis devices  1  into a predetermined format, and then transmits the data to the management computer  100 . The detection data and the processed data from the plurality of analysis devices  1  are aggregated by the communication device  210  and then transmitted to the management computer  100 . The communication device  210  and the management computer  100  may communicate with each other in a wireless manner or a wired manner. 
     The repeater  220  connects between the analysis device  1  and the communication device  210 . A plurality of the repeaters  220  is provided. Each of the repeaters  220  communicates with the communication device  210  in a wireless manner. 
     The management computer  100  is configured to monitor and manage the state of each of the plurality of machines B, on the basis of the detection data of the vibration sensor  6  transmitted from each of the plurality of analysis devices  1  and the processed data output by each calculation unit  82 . The management computer  100  is configured to diagnose the presence/absence of abnormality of each machine B, on the basis of the detection data of the vibration sensor  6  transmitted from each of the plurality of analysis devices  1  and the processed data output by each calculation unit  82 . 
     The plurality of analysis devices  1  is configured to transmit the detection data and the processed data independently. In other words, the analysis device  1  is configured to transmit the detection data and the processed data without being affected by another analysis device  1 . 
     For example, in a case where the machines B and the analysis devices  1  are located in the basement and the communication device  210  and the management computer  100  are located on the ground, the detection data and the processed data that are transmitted from the analysis devices  1  are smoothly transmitted to the management computer  100  due to providing the repeaters  220 . 
     Effects 
     As described above, in the present embodiment, the analysis system  200  includes the plurality of analysis devices  1  installed on the plurality of machines B, and the communication device  210  that receives the processed data transmitted from each of the plurality of analysis devices  1  and transmits the processed data to the management computer  100 . Therefore, the management computer  100  is allowed to monitor and manage the state of the plurality of machines B and diagnose the presence/absence of abnormality in the plurality of machines B. 
     Other Embodiments 
     Note that in the embodiments described above, the management computer  100  may include one computer or a plurality of computers. 
     In the embodiments described above, one housing  20  houses the thermoelectric generation module  5 , the vibration sensor  6 , the microcomputer  8 , and the wireless communication device  9 . The thermoelectric generation module  5  may be housed in a first housing, and the vibration sensor  6 , the microcomputer  8 , and the wireless communication device  9  may be housed in a second housing. The first housing and the second housing are separate housings. The power storage unit  14  may be arranged between the first housing and the second housing. 
     In the embodiments described above, the function of the calculation unit  82  may be provided in the management computer  100 . The detection data of the vibration sensor  6  may be transmitted to the management computer  100  via the wireless communication device  9  so that the management computer  100  may output the processed data. Furthermore, a function of the management computer  100  may be provided in the microcomputer  8 . For example, the calculation unit  82  may diagnose the presence/absence of the abnormality. 
     According to the present disclosure, it is possible to output a stable calculation result in vibration phenomenon following a normal distribution. 
     Although the invention has been described with respect to specific embodiments for a complete and clear disclosure, the appended claims are not to be thus limited but are to be construed as embodying all modifications and alternative constructions that may occur to one skilled in the art that fairly fall within the basic teaching herein set forth.