Patent Description:
An electromagnetic noise (EM noise) such as electromagnetic radiation noise and conduction noise emitted from an electronic circuit or the like is required to be suppressed within a range of a predetermined regulation value. When the electromagnetic noise exceeds the range of regulation value, such electromagnetic noise may affect an operation of another surrounding circuit. Therefore, there is a demand for a technique for identifying a noise source that generates an electromagnetic noise exceeding a predetermined regulation value.

In the related art, as a measurement method for identifying a noise source, a method for obtaining a frequency spectrum by frequency domain measurement or a method for obtaining a frequency spectrum by performing time domain measurement and performing short-time Fourier transform (ST-FFT) is known. It is easy to identify a high-frequency noise source (for example, noise from a clock signal circuit or a communication circuit, or the like) from a frequency spectrum.

However, an inverter circuit and a high-output circuit that performs high-speed switching at a low modulation frequency (for example, kHz band) are noise sources capable of generating a wide-band electromagnetic noise. When the noise source of the wide-band electromagnetic noise is identified, a long time is required in the measurement method for identifying the noise source in the related art.

PTL <NUM>: <CIT> <CIT> discloses a noise detection apparatus with the features in the preamble of present claim <NUM>. Another conventional noise detecting system is described in <CIT> (<CIT>).

From a viewpoint of improving electromagnetic compatibility (EMC), a technique for accurately identifying not only a high-frequency noise source but also a noise source capable of generating a wide-band electromagnetic noise is required. The invention has been made in view of the above problem, and an object of the invention is to provide a noise source identification method and an information processing system capable of easily identifying a noise source that generates a wide-band electromagnetic noise even when the noise source is present.

To solve the above problem, an information processing system according to the invention includes the features defined in claim <NUM>.

In addition, a noise source identification method according to the invention includes the features defined in claim <NUM>.

According to the invention, it is possible to provide the noise source identification method and the information processing system capable of easily identifying the noise source that generates the wide-band electromagnetic noise even when the noise source is present. Problems, configurations, and effects other than those described above are clear from the following description of embodiments.

Hereinafter, examples and an embodiment of the invention will be described with reference to drawings. The examples are not covered by the scope of the claims but nevertheless useful to understand the invention. The embodiment is an example for describing the invention, and omission and simplification are appropriately made for clarification of the description. The invention can be implemented in various other forms. The number of constituent elements may be singular or plural, unless otherwise specified.

In order to facilitate understanding of the invention, a position, a size, a shape, a range, and the like of each constituent element shown in the drawings may not represent an actual position, size, shape, range, and the like. Therefore, the invention is not necessarily limited to the position, size, shape, range, or the like disclosed in the drawings. Examples of various types of information may be described by expressions such as "table", "list", "queue", "data", and "graph", but the various types of information may be expressed by a data structure other than these expressions. For example, the various types of information such as "XX table", "XX list", and "XX queue" may be "XX information". When identification information is described, expressions such as "identification information", "identifier", "name", "ID", and "number" are used, but these expressions may be replaced with each other. When there are a plurality of constituent elements having the same or similar functions, different subscripts may be attached to the same reference numeral. In addition, when it is not necessary to distinguish the plurality of constituent elements from each other, a description will be given by omitting the subscript.

In the embodiment, a processing performed by executing a program may be described. Here, a computer executes the program by a processor (for example, a CPU or a GPU), and performs the processing defined by the program using a storage resource (for example, a memory), an interface device (for example, a communication port), or the like. Therefore, a subject of the processing performed by executing the program may be the processor. Similarly, the subject of the processing performed by executing the program may be a controller, a device, a system, a computer, or a node including the processor. The subject of the processing performed by executing the program may be a calculation unit, and may include a dedicated circuit that performs a specific processing. Here, the dedicated circuit is, for example, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a complex programmable logic device (CPLD), and the like.

The program may be installed on the computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is the program distribution server, the program distribution server may include the processor and the storage resource that stores a program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to another computer. In addition, in the embodiment, two or more programs may be implemented as one program, or one program may be implemented as two or more programs.

First, a noise source identification device (information processing system) and a noise source identification method according to a first example not covered by the present independent claims will be described with reference to <FIG>. <FIG> is a block diagram illustrating an example of a configuration of a noise source identification device <NUM> according to the first example. As illustrated in <FIG>, as an example, the noise source identification device <NUM> of the first example includes a measuring unit <NUM>, a calculation processing unit <NUM>, a storage device <NUM> that stores a noise source database <NUM>, an I/O interface <NUM>, and a display <NUM>.

As schematically shown in the lower left of <FIG>, in an environment in which there are a plurality of devices S1 to Sn suspected to be noise sources that generate an electromagnetic noise (hereinafter referred to as "suspected noise source devices") and a device V that receives a noise due to radiation or conduction of such electromagnetic noise (hereinafter referred to as "target device"), this noise source identification device <NUM> identifies, from among the suspected noise source devices S1 to Sn, a device that applies an electromagnetic noise EMs equal to or greater than a predetermined reference to the target device V.

Here, the electromagnetic noise (EM noise) is, for example, an electromagnetic radiation noise or a conduction noise emitted from an electronic circuit or the like. In addition, an example of the suspected noise source device is a device including, for example, an electronic circuit, and may be simply referred to as a noise source device.

Although not illustrated, the measuring unit <NUM> includes, for example, a well-known antenna, an amplifier, an A/D converter, and the like, and is configured to measure an electromagnetic noise. A target to be measured of the measuring unit <NUM> includes the suspected noise source devices S1 to Sn and the target device V. The measuring unit <NUM> that measures each of the suspected noise source devices S1 to Sn and the target device V may be separate devices or may be the same device.

The calculation processing unit <NUM> is configured to generate data indicating a time change of the electromagnetic noise according to a measurement result of the measuring unit <NUM>, and generate frequency spectrum data and modulation frequency data of the electromagnetic noise. Specifically, the calculation processing unit <NUM> can be configured by, for example, a general-purpose computer, and generates the time change data, the frequency spectrum data, the modulation frequency data of the electromagnetic noise, and the like by performing a predetermined calculation processing on measurement data as digital data input from the measuring unit <NUM>. The frequency spectrum data of the electromagnetic noise can be generated by applying a well-known short-time Fourier transform (ST-FFT) to the time change data of the electromagnetic noise, for example.

In addition, as will be described later, the calculation processing unit <NUM> has a function of generating a graph based on the modulation frequency data of the plurality of suspected noise source devices S1 to Sn stored in the noise source database <NUM> and the modulation frequency data of the electromagnetic noise received by the target device V measured by the measuring unit <NUM>. This graph is displayed on the display <NUM> and presented to a user. The user compares this graph and identifies a device (for example, S2), which is a noise source of electromagnetic noise equal to or greater than a predetermined reference value, from among the plurality of suspected noise source devices S1 to Sn according to a result of comparison.

The storage device <NUM> includes a storage device that stores the noise source database <NUM>. The noise source database <NUM> is a database that stores frequency spectrum data of electromagnetic noise measured in the vicinity of the suspected noise source devices S1 to Sn and modulation frequency data of electromagnetic noise from the suspected noise source devices S1 to Sn for each suspected noise source device. The frequency spectrum data and the modulation frequency data of the suspected noise source devices S1 to Sn can be generated based on the measurement result in the measuring unit <NUM>, but can also be generated by computer simulation for the suspected noise source devices S1 to Sn instead of or in addition to the actual measurement in the measuring unit <NUM> and stored in the storage device <NUM> of the noise source database. In the computer simulation, for example, specification data related to a frequency, such as specifications of the suspected noise source devices S1 to Sn, may be used.

The I/O interface <NUM> is an interface for outputting data obtained by the calculation processing unit <NUM> to the display <NUM> and another external device and for receiving data from the external device. The display <NUM> is configured to display, for example, modulation frequency data of an electromagnetic noise stored in the noise source database <NUM> and frequency spectrum data measured by the measuring unit <NUM>. The external device may be, for example, an input device (for example, a keyboard, a mouse, and the like) for a user to input a command (instruction), an external storage device, or a management device connected via a network.

A part or all of the noise source identification device <NUM> can be configured as an information processing system. The information processing system includes, for example, a measuring unit, a calculation unit, and an output unit. The measuring unit measures an electromagnetic noise received by the target device. The calculation unit calculates, from measurement data of the electromagnetic noise, modulation frequency data in which a frequency of the electromagnetic noise, a modulation frequency of the electromagnetic noise, and an intensity of the electromagnetic noise are associated with each other. The output unit outputs the calculated modulation frequency data.

In addition, the information processing system may further include, for example, a storage unit. The storage unit stores modulation frequency data in which a frequency of an electromagnetic noise generated by one or more devices different from the target device, a modulation frequency of the electromagnetic noise, and an intensity of the electromagnetic noise are associated with each other. Then, the output unit outputs the modulation frequency data calculated for the electromagnetic noise received by the target device and the modulation frequency data calculated for the electromagnetic noise generated by the one or more devices different from the target device.

In addition, the measuring unit may measure the electromagnetic noise generated by the one or more devices different from the target device. Then, the calculation unit may calculate the modulation frequency data from the measurement data of the electromagnetic noise and store the modulation frequency data in the storage unit.

In addition, the storage unit may store information on characteristics of the one or more devices different from the target device. The calculation unit may calculate the modulation frequency data of the electromagnetic noise generated by the one or more devices different from the target device from the information on those characteristics and store the modulation frequency data in the storage unit. Here, the information on the characteristics may be, for example, the specification data related to the frequency such as specifications of the suspected noise source devices S1 to Sn, or a device characteristic information database 13A. From the information on those characteristics, the modulation frequency data of the electromagnetic noise generated by the device may be calculated, for example, by the computer simulation.

Here, for example, the measuring unit may be configured by a measuring device that operates as the measuring unit <NUM>, the calculation unit may be configured by a calculation device that operates as the calculation processing unit <NUM>, and the output unit may be configured by an output device such as the calculation processing unit <NUM> or the I/O interface <NUM>. The calculation device may be configured with a processor such as a central processing unit (CPU) or a graphics processing unit (GPU), or may include a dedicated circuit that performs a specific processing. Here, the dedicated circuit is, for example, FPGA, ASIC, CPLD, and the like. In addition, the storage device <NUM> is, for example, a memory and constitutes the storage unit.

Next, a noise source identification method that can be executed by the noise source identification device <NUM> of the first example will be described with reference to <FIG>. <FIG> is a flowchart illustrating a procedure of this method, and <FIG> and <FIG> illustrate an example of modulation frequency data (graph) generated by this method.

As shown in <FIG>, this method is roughly divided into a procedure of generating the noise source database <NUM> (steps S11 to S13), a procedure of measuring an electromagnetic noise in the target device V (steps S14 to S15), and a specific procedure of a noise source (step S16).

In the step S11, the measuring unit <NUM> measures an electromagnetic noise from the suspected noise source devices S1 to Sn in a time domain. For example, the measuring unit <NUM> is arranged in the vicinity of any of the suspected noise source devices S1 to Sn, and measures the electromagnetic noise at that position in the time domain. The electromagnetic noise from the suspected noise source devices S1 to Sn is an electromagnetic noise emitted or conducted from the suspected noise source devices S1 to Sn, and may include, for example, an electromagnetic noise generated by the suspected noise source devices S1 to Sn. In addition, the electromagnetic noise from the suspected noise source devices S1 to Sn may be, for example, an electromagnetic noise measured in the vicinity of the suspected noise source devices or inside the suspected noise source devices S1 to Sn, or may be an electromagnetic noise at positions of the suspected noise source devices S1 to Sn.

In step S12, the calculation processing unit <NUM> applies modulation frequency analysis to a measuring signal (digital value) of the electromagnetic noise in the time domain and calculates modulation frequency data of the electromagnetic noise from the suspected noise source devices S1 to Sn. Here, the modulation frequency data of the electromagnetic noise is information in which a frequency of the electromagnetic noise, a modulation frequency of the electromagnetic noise, and an intensity of the electromagnetic noise are associated with each other.

In the step S13, the calculation processing unit <NUM> stores the modulation frequency data of the electromagnetic noise from the suspected noise source device in the noise source database <NUM>. The calculation processing unit <NUM> generates or updates the noise source database <NUM>. The information processing system executes steps S11 to S13 for the suspected noise source devices S1 to Sn, thereby acquiring the modulation frequency data for each suspected noise source device and storing the modulation frequency data in the noise source database <NUM>.

As shown in an upper figure of <FIG> as an example, in a spectrogram of an electromagnetic noise in a time domain, for example, in a graph in which a vertical axis represents time and a horizontal axis represents a frequency of an electromagnetic noise, an intensity of an electromagnetic noise (electromagnetic intensity) can be expressed by brightness or color of the graph. By applying the modulation frequency analysis to the electromagnetic noise data in this time domain, a graph of the modulation frequency data of the electromagnetic noise can be obtained.

In the graph of the modulation frequency data, for example, in a graph in which a vertical axis represents a modulation frequency and a horizontal axis represents a frequency of an electromagnetic noise (electromagnetic frequency), an intensity of an electromagnetic noise (electromagnetic intensity) can be expressed by brightness or color. The graph of the modulation frequency data acquired here is modulation frequency data in which the frequency of the electromagnetic noise of the suspected noise source device, the modulation frequency of the electromagnetic noise of the suspected noise source device, and the intensity of the electromagnetic noise of the suspected noise source device are associated with each other.

The graph of the modulation frequency data illustrated as an example in a lower diagram of <FIG> is characterized in that there are periodically high brightness portions in a vertical direction in a frequency region where an electromagnetic noise is present. It is estimated that this corresponds to a fundamental frequency of the electromagnetic noise output by the suspected noise source device and a harmonic thereof. As will be described later, according to such a characteristic, it is possible to identify a suspected noise source device that emits or conducts an electromagnetic noise equal to or higher than a predetermined regulation value to the target device V.

Returning to <FIG>, the steps S14 to S15 will be described. In the step S14, the measuring unit <NUM> measures an electromagnetic noise received by the target device V in the time domain. For example, the measuring unit <NUM> is arranged in the vicinity of the target device V, and measures an electromagnetic noise at a position of the target device V in the time domain. The electromagnetic noise received by the target device V may be, for example, an electromagnetic noise measured in the vicinity of the target device V or the electromagnetic noise at the position of the target device V.

In the step S15, the calculation processing unit <NUM> applies the modulation frequency analysis to the measuring signal (digital value) of the electromagnetic noise in the time domain and calculates the modulation frequency data of the electromagnetic noise received by the target device V. The graph of the modulation frequency data calculated here is modulation frequency data in which the frequency of the electromagnetic noise of the target device V, the modulation frequency of the electromagnetic noise of the target device V, and the intensity of the electromagnetic noise of the target device V are associated with each other. The calculation processing unit <NUM> may store the modulation frequency data of the electromagnetic noise received by the target device V in the noise source database <NUM>.

In the step S16, the calculation processing unit <NUM> outputs the modulation frequency data of the electromagnetic noise received by the target device V (a result obtained by the modulation frequency analysis in step S15) and the modulation frequency data of the electromagnetic noise from the suspected noise source devices S1 to Sn stored in the noise source database <NUM> (a result obtained by the modulation frequency analysis in step <NUM>) to a storage device, the display <NUM>, an external device, and the like included in the information processing system via the I/O interface <NUM>. For example, when the calculation processing unit <NUM> outputs the modulation frequency data to the display <NUM>, the modulation frequency data of the electromagnetic noise at the position of the target device V and the modulation frequency data of the suspected noise source devices S1 to Sn may be displayed simultaneously or separately. An instruction of a user may be received from the I/O interface <NUM>, and the calculation processing unit <NUM> may output the modulation frequency data by an output destination or an output method (for example, a display method) specified by the instruction of the user. Accordingly, the user can compare the modulation frequency data of the electromagnetic noise at the position of the target device V with the modulation frequency data of the suspected noise source devices S1 to Sn on a display screen of the display <NUM> or the like, and can specify a device that is a generation source (noise source) of the electromagnetic noise received by the target device V among the suspected noise source devices. For example, when the target device V receives an electromagnetic noise exceeding a predetermined reference, such as a regulation value of the electromagnetic noise in the target device V, it is possible to specify the device that is the noise source of the electromagnetic noise, and it is possible to perform a noise countermeasure.

As shown in <FIG>, the calculation processing unit <NUM> converts the modulation frequency data of the electromagnetic noise at the position of the target device V and the modulation frequency data of the suspected noise source devices S1 to Sn stored in the noise source database <NUM> into graphs and displays the graphs on the screen of the display <NUM>. The user looks at this screen, compares the graph of the modulation frequency data for the plurality of suspected noise source devices S1 to Sn with the graph of the modulation frequency data for the target device V, and finds a graph having a most approximate characteristic. In this way, a suspected noise source device corresponding to an identified graph is identified as a noise source affecting the target device V. In addition, the user confirms the characteristic in the graph of the modulation frequency data of the electromagnetic noise at the position of the target device V with respect to a part of the electromagnetic noise such as the electromagnetic noise exceeding the predetermined reference among the electromagnetic noise received by the target device V. Then, if characteristics same as or similar to this characteristic can be confirmed in a graph of modulation frequency data of a certain suspected noise source device, the suspected noise source device can be identified as a noise source of a part of the electromagnetic noise.

As described above, according to the noise source identification method of the first example, by acquiring the modulation frequency data of the electromagnetic noise for the suspected noise source devices S1 to Sn, storing the modulation frequency data in the noise source database <NUM>, and comparing the data with the modulation frequency data of the electromagnetic noise received by the target device V, it is possible to identify the noise source that emits the electromagnetic noise equal to or greater than the predetermined reference value.

In the case of the measuring signal of the electromagnetic noise in the time domain, if the electromagnetic noise is in a wide band, amplitude of the noise may be flat over a wide range, and it may be difficult to specify the noise source. However, in the noise source identification device and method of the first example, the modulation frequency analysis can be performed on the electromagnetic noise from the suspected noise source devices S1 to Sn and the electromagnetic noise received by the target device V to acquire and compare the modulation frequency data. Therefore, according to the first example, even if there is a noise source that generates a wide band electromagnetic noise, it is possible to easily identify the noise source.

Next, a noise source identification device (information processing system) and a noise source identification method according to a second example not covered by the present independent claims will be described with reference to <FIG>. <FIG> is a block diagram illustrating an example of a configuration of a noise source identification device 1A according to the second example. Since the same configurations as those in the first example are denoted by the same reference numerals as those in <FIG>, a duplicate description will be omitted below. A storage device <NUM> of this noise source identification device 1A has a device characteristic information database 13A instead of or in addition to the noise source database <NUM>.

The device characteristic information database 13A stores information (characteristic information) on a characteristic of a device, such as product specifications of suspected noise source devices S1 to Sn, for each suspected noise source device. For example, when the suspected noise source device is an inverter circuit, as an example, a rated output, a capacitance, a rated input voltage, a rated output voltage, an output frequency range, a control method, and the like of the device are stored as data. The calculation processing unit <NUM> compares the data (characteristic information) on this device characteristic with modulation frequency data obtained for the target device V, and identifies a suspected noise source device that outputs an electromagnetic noise exceeding a predetermined regulation value according to this comparison result.

With reference to a flowchart of <FIG>, the noise source identification method that can be executed by the noise source identification device 1A of the second example will be described. A description will be given on the assumption that that the device characteristic information database 13A has already registered the data on the device characteristics of the suspected noise source devices S1 to Sn.

Steps S14A and S15A of <FIG> are the same as the steps S14 and S15 of <FIG>. In step S16A, modulation frequency data (a result of modulation frequency analysis) of an electromagnetic noise at a position of the target device V obtained in the step S15A is compared with data of device characteristic (characteristic information) stored in the device characteristic information database 13A, and a suspected noise source device estimated to radiate an electromagnetic noise exceeding a regulation value is identified. It is also possible to estimate the modulation frequency data of the electromagnetic noise output from the suspected noise source devices S1 to Sn from the device characteristic data stored in the device characteristic information database 13A, and by comparing with this estimation result, it is possible to identify a suspected noise source device that has the greatest influence on the target device V, as in the first example.

A part or all of the noise source identification device 1A can be configured as the information processing system. The information processing system includes, for example, a measuring unit, a calculation unit, and an output unit. The measuring unit measures an electromagnetic noise received by the target device. The calculation unit calculates, from measurement data of the electromagnetic noise, modulation frequency data in which a frequency of the electromagnetic noise, a modulation frequency of the electromagnetic noise, and an intensity of the electromagnetic noise are associated with each other. The output unit outputs the calculated modulation frequency data.

In addition, the information processing system may further include, for example, a storage unit. The storage unit stores characteristic information on characteristics of one or more devices different from the target device. Then, the output unit outputs the modulation frequency data and the characteristic information.

In addition, the calculation unit compares the characteristic information with the modulation frequency data, and identifies a device that generates at least a part of the electromagnetic noise received by the target device from the one or more devices.

Here, for example, the measuring unit may be configured by a measuring device that operates as the measuring unit <NUM>, the calculation unit may be configured by a calculation device that operates as the calculation processing unit <NUM>, and the output unit may be configured by an output device such as the calculation processing unit <NUM> or the I/O interface <NUM>. In addition, the storage device <NUM> is, for example, a memory and constitutes the storage unit. The characteristic information on the characteristic of the one or more devices different from the target device may be, for example, information on characteristic of a device stored in the device characteristic information database 13A for each suspected noise source device.

Next, a noise source identification device (information processing system) and a noise source identification method according to a third example not covered by the present independent claims will be described with reference to <FIG>. Since a configuration of the noise source identification device according to the third example can be the same as the configuration of the first example, a duplicate description will be omitted below.

In the first example, the modulation frequency data of the suspected noise source devices S1 to Sn and the modulation frequency data of the target device V are acquired, and the comparison between both data is visually performed by the user based on the graph of the modulation frequency data displayed on the screen of the display <NUM>. In the third example, the calculation processing unit <NUM> performs comparison in accordance with a characteristic amount (a matching index) of both data to identify a noise source. Therefore, in the device of the third example, it is not necessary to display the graph of the modulation frequency data on the screen of the display <NUM> (it is possible to use the display on the display <NUM> together). As an example, a calculation processing in the calculation processing unit <NUM> can be a calculation processing using a well-known search algorithm, an expert system, a neural network, and the like.

Next, the noise source identification method that can be executed by the noise source identification device of the third example will be described with reference to a flowchart of <FIG>. A procedure of generating the noise source database <NUM> (steps S11B to S13B) and a procedure of measuring an electromagnetic noise in the target device V (steps S14B to S15B) are the same as steps S11 to S13 and S14 to S15 of the first example (<FIG>).

In step S16B, the calculation processing unit <NUM> compares modulation frequency data of an electromagnetic noise received by the target device V (a result obtained by the modulation frequency analysis of step S15B) with modulation frequency data of an electromagnetic noise from the suspected noise source devices S1 to Sn stored in the noise source database <NUM> (a result obtained by the modulation frequency analysis of step 12B) based on an extracted matching index. Then, based on this comparison result, a suspected noise source device that is estimated to generate an electromagnetic noise exceeding the regulation value is identified. Information on the identified suspected noise source device is displayed on the display <NUM>. Thereby, as in the above examples, the suspected noise source device that has the greatest influence on the target device V can be identified.

The calculation processing unit <NUM> compares a graph of modulation frequency data of an electromagnetic noise from a plurality of suspected noise source devices S1 to Sn with a graph of the modulation frequency data of the electromagnetic noise received by the target device V, and finds a graph having a most approximate characteristic. For example, the calculation processing unit <NUM> calculates a degree of similarity between images of both graphs, and identifies a graph of modulation frequency data of an electromagnetic noise from a suspected noise source device having a high degree of similarity to the graph of the modulation frequency data of the electromagnetic noise received by the target device V. The calculation processing unit <NUM> identifies or estimates that the suspected noise source device corresponding to the graph identified in this manner is the noise source affecting the target device V.

In addition, the calculation processing unit <NUM> identifies the characteristic in the graph of the modulation frequency data of the electromagnetic noise received by the target device V with respect to a part of the electromagnetic noise such as an electromagnetic noise exceeding the predetermined reference among the electromagnetic noise received by the target device V. Then, the calculation processing unit <NUM> determines whether the characteristic same as or similar to the identified characteristic is in the graph of the modulation frequency data of the electromagnetic noise from the suspected noise source devices S1 to Sn. As a result of the determination, when a graph of modulation frequency data of an electromagnetic noise from a certain suspected noise source device has the characteristic same as or similar to the above identified characteristic, the suspected noise source device can be identified or estimated as the noise source of a part of the electromagnetic noise.

A part or all of the noise source identification device <NUM> can be configured as the information processing system. The information processing system includes, for example, a measuring unit, a calculation unit, and an output unit. The measuring unit measures an electromagnetic noise received by the target device. The calculation unit calculates, from measurement data of the electromagnetic noise, modulation frequency data in which a frequency of the electromagnetic noise, a modulation frequency of the electromagnetic noise, and an intensity of the electromagnetic noise are associated with each other. The output unit outputs the calculated modulation frequency data.

In addition, the information processing system may further include, for example, a storage unit. The storage unit stores information on one or more devices different from the target device. Then, the calculation unit compares the information on the one or more devices with the modulation frequency data, and identifies a device that generates at least a part of the electromagnetic noise from among the one or more devices. The information on the one or more devices may be information on the electromagnetic noise generated by the one or more devices.

Here, for example, the measuring unit may be configured by a measuring device that operates as the measuring unit <NUM>, the calculation unit may be configured by a calculation device that operates as the calculation processing unit <NUM>, and the output unit may be configured by an output device such as the calculation processing unit <NUM> or the I/O interface <NUM>. In addition, the storage device <NUM> is, for example, a memory and constitutes the storage unit. The information on the electromagnetic noise generated by the one or more devices may be, for example, the modulation frequency data of the electromagnetic noise from the suspected noise source devices S1 to Sn stored in the noise source database <NUM>.

Next, a noise source identification device (information processing system) and a noise source identification method according to an embodiment will be described with reference to <FIG>. Since a configuration of the noise source identification device according to the embodiment can be the same as the configuration of the first example, a duplicate description will be omitted below. However, in the embodiment, the noise source database <NUM> stores different modulation frequency data for different time frames for each of a plurality of suspected noise source devices S1 to Sn. Then, the calculation processing unit <NUM> calculates a matching index between the modulation frequency data of the noise source database <NUM> and the modulation frequency data of the target device V for each of the different time frames, and identifies a noise source.

An operation of this noise source identification device will be described with reference to a flowchart of <FIG>. A procedure of generating the noise source database <NUM> in step S21 (<FIG>) is the same as the steps S11 to S13 of the first example. <FIG> is a schematic diagram illustrating the modulation frequency data for the different time frames obtained for each of the suspected noise source devices S1 to Sn. The measuring unit <NUM> measures the electromagnetic noise from each of the suspected noise source devices S1 to Sn separately for each of different time frames Time1, Time2,. The measurement data of the electromagnetic noise from the suspected noise source devices S1 to Sn is measurement data obtained by measuring the electromagnetic noise from the suspected noise source devices S1 to Sn for each of a plurality of time frames. The calculation processing unit <NUM> applies modulation frequency analysis for each of the time frames to a measuring signal (digital value) of an electromagnetic noise in a time domain, and calculates the modulation frequency data of an electromagnetic noise from the suspected noise source devices. As a result, the calculation processing unit <NUM> acquires data of a frequency spectrum for each of the different time frames, and stores the data in the noise source database <NUM>.

Thereafter, in step S22 (<FIG>), the measuring unit <NUM> measures an electromagnetic noise received by the target device V for each of the plurality of time frames. The calculation processing unit <NUM> applies the modulation frequency analysis to a measurement result, acquires the modulation frequency data for each of the plurality of time frames, and stores the modulation frequency data in the noise source database <NUM>. In step S23 (<FIG>), the calculation processing unit <NUM> compares the modulation frequency data of the target device V (a result of the modulation frequency analysis) with the modulation frequency data of the suspected noise source devices S1 to Sn (a result of the modulation frequency analysis) for each time frame, and identifies or estimates a device that generates at least a part of the electromagnetic noise received by the target device V from among the suspected noise source devices S1 to Sn. Here, as illustrated in <FIG>, for each of the suspected noise source devices S1 to Sn, the matching index for each time frame may be calculated and output.

In addition, in the step S22 (<FIG>), it is not necessary for the measuring unit <NUM> to measure the electromagnetic noise received by the target device V for each of the plurality of time frames. In this case, the calculation processing unit <NUM> applies the modulation frequency analysis to the measurement result, acquires the modulation frequency data, and stores the modulation frequency data in the noise source database <NUM>. In the step S23 (<FIG>), the calculation processing unit <NUM> compares the modulation frequency data of the target device V (the result of the modulation frequency analysis) with the modulation frequency data of the suspected noise source devices S1 to Sn for each time frame (the result of the modulation frequency analysis), and identifies or estimates the device that generates at least a part of the electromagnetic noise received by the target device V from among the suspected noise source devices S1 to Sn.

According to the fourth embodiment, since each of the suspected noise source devices S1 to Sn holds different modulation frequency data depending on a time zone, it is possible to identify a more precise noise source in consideration of a difference in time. As described above, the modulation frequency data of the suspected noise source devices S1 to Sn can be stored in a database before the modulation frequency data of the target device V is acquired, and as illustrated in <FIG>, the measurement of the target device V (the step S22) and the measurement of the suspected noise source devices S1 to Sn (the step S21) can be performed in parallel.

Claim 1:
An information processing system (<NUM>), comprising:
a measuring unit (<NUM>) configured to measure a first electromagnetic noise received by a target device (V);
a calculation unit (<NUM>) configured to calculate, from measurement data of the first electromagnetic noise, first modulation frequency data as a graph in which a frequency of the first electromagnetic noise, a modulation frequency of the first electromagnetic noise, and an intensity of the first electromagnetic noise are associated with each other, the frequency of the first electromagnetic noise being shown as a first axis, while the modulation frequency of the first electromagnetic noise being shown as a second axis;
an output unit (<NUM>, <NUM>) configured to output the first modulation frequency data; and
a storage unit (<NUM>) configured to store second modulation frequency data in which a frequency of a second electromagnetic noise generated by one or more devices (S1-Sn) different from the target device (V) is shown as a first axis, while a modulation frequency of the second electromagnetic noise is shown as a second axis, and the frequency of the second electromagnetic noise, the modulation frequency of the second electromagnetic noise, and an intensity of the second electromagnetic noise are associated with each other,
wherein
the measuring unit (<NUM>) is configured to measure the second electromagnetic noise, and
the calculation unit (<NUM>) is configured to calculate the second modulation frequency data from measurement data of the second electromagnetic noise and store the second modulation frequency data in the storage unit (<NUM>),
the calculation unit (<NUM>) is configured to compare the second modulation frequency data with the first modulation frequency and identify a device (S1-Sn) that generates at least a part of the first electromagnetic noise from among the one or more devices (S1-Sn),
characterised in that the measurement data of the second electromagnetic noise is measurement data obtained by measuring the second electromagnetic noise for each of a plurality of time frames.