JP7693418B2 - Partial discharge diagnosis support device, diagnosis support method, and program - Google Patents

Description

Embodiments of the present invention relate to a partial discharge diagnostic support device, a diagnostic support method, and a program.

Conventionally, in electrical equipment such as switchgear, the insulating performance of the insulators on the surface or inside the electrical equipment can deteriorate over time. When the insulating performance deteriorates, partial discharge occurs from the point where the insulating performance has deteriorated. If the deterioration of the insulating performance progresses further, there is a possibility that the electrical equipment will suffer a dielectric breakdown.

Partial discharges can occur when the surrounding atmosphere causes a sudden halt to a continuous discharge, or conversely, when a concentrated discharge occurs in a short period of time. In addition, during actual operation, various types of environmental noise can be present during measurements. For this reason, it is not easy for inspection staff to diagnose the deterioration of the insulation in the switchgear from the partial discharge signal strength.

JP 2010-133746 A

The problem that this invention aims to solve is to provide a partial discharge diagnosis support device, a diagnosis support method, and a program that can assist workers in diagnosing the deterioration status of insulation parts.

The partial discharge diagnosis support device of the embodiment has an acquisition unit and an output processing unit. The acquisition unit acquires analysis results by time based on the signal strength of partial discharges occurring in an insulating part of an electrical device housed in a housing. The output processing unit displays the table representing the analysis results acquired by the acquisition unit, the table having a plurality of squares in which a first axis represents first information indicating a first period and a second axis represents second information different from the first information.

FIG. 1 is an explanatory diagram showing an example of a partial discharge diagnosis support system 1 according to an embodiment. FIG. 2 is an explanatory diagram showing an example of a box 10 and a measuring device 100 according to the embodiment. FIG. 2 is an explanatory diagram showing an example of a hardware configuration of a partial discharge diagnosis support device 120 according to the embodiment. FIG. 4 is an explanatory diagram showing an example of partial discharge waveform data 400 stored in a partial discharge waveform data storage unit 122 according to the embodiment. FIG. 5 is an explanatory diagram showing an example of partial discharge analysis data 500 stored in a partial discharge analysis data storage unit 123 according to the embodiment. FIG. 6 is an explanatory diagram showing an example of peripheral device information 600 stored in a related information storage unit 124 of the embodiment. FIG. 7 is an explanatory diagram showing an example of business establishment/employee information 700 stored in a related information storage unit 124 of the embodiment. FIG. 8 is an explanatory diagram showing an example of railway information 800 stored in a related information storage unit 124 of the embodiment. FIG. 9 is an explanatory diagram showing an example of weather-related information 900 stored in a related information storage unit 124 of the embodiment. FIG. 13 is an explanatory diagram showing an example of a screen showing an AI recognition result without a filter in an embodiment. FIG. 4 is an explanatory diagram illustrating an example of a screen of signal strength data according to the embodiment. FIG. 13 is an explanatory diagram showing an example of a screen showing the AI identification result when the exclusion filter of the embodiment is applied. FIG. 13 is an explanatory diagram showing an example of a screen showing an AI identification result when the extraction filter of the embodiment is applied. FIG. 4 is an explanatory diagram illustrating an example of a screen of signal strength data according to the embodiment. FIG. 15 is an explanatory diagram showing an example of a detailed display screen 1500 of various data of the square 1001 according to the embodiment. 5 is a flowchart showing an example of a diagnosis support process related to partial discharge performed by the partial discharge diagnosis support device 120 of the embodiment. FIG. 13 is an explanatory diagram showing an example of a screen relating to partial discharge, according to a first modified example, which is displayed on the display 307 of the embodiment.

The partial discharge diagnostic support device, diagnostic support method, and program of the embodiment will be described below with reference to the drawings.

Figure 1 is an explanatory diagram showing an example of a partial discharge diagnosis support system 1 according to an embodiment. In Figure 1, the partial discharge diagnosis support system 1 includes a box 10 and a measuring device 100 that are placed at a customer's site, and a partial discharge analyzer 110 and a partial discharge diagnosis support device 120 that are provided at a center (workplace) that diagnoses partial discharges.

The measuring device 100 and the partial discharge analyzer 110 are communicatively connected via the Internet 2. The partial discharge analyzer 110 and the partial discharge diagnosis support device 120 are communicatively connected, for example, via a LAN (Local Area Network). Each device is a computer device such as a personal computer or tablet terminal that includes a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), a communication unit, etc.

First, the box 10 and the measuring device 100 will be described with reference to FIG.
FIG. 2 is an explanatory diagram showing an example of the box body 10 and the measuring device 100 of the embodiment. As shown in FIG. 2, the boxes 10a, 10b, ..., 10n (n is an integer of 2 or more) which are an example of a housing are arranged side by side. The boxes 10a, 10b, ..., 10n are arranged in a substantially straight line. In addition, a predetermined power supply system that supplies power to the electrical equipment is provided in the boxes 10a, 10b, ..., 10n. In the following, when there is no need to distinguish which box is being used, the box body will be simply referred to as the box body 10. Each box body 10 is a box capable of storing electrical equipment such as a switch gear. The box body 10 stores electrical equipment such as a circuit breaker and a main circuit conductor. The electrical equipment has insulating equipment on the surface or inside. Partial discharge may occur in the electrical equipment due to deterioration over time. The measuring device 100 measures the signal strength of partial discharge generated in an insulating part of the electrical equipment stored in the box body 10.

Electrodes 40a, 40b, ..., 40n are fixed to the front of the box bodies 10a, 10b, ..., 10n so as to be in contact with each other. Hereinafter, when there is no need to distinguish between the electrodes, they will be simply referred to as electrodes 40. The electrodes 40 detect the surface potential of the box body 10. The electrodes 40 output the detected surface potential as an electrical signal to the measurement device 100. The electrodes 40 may be provided in a semi-permanent state, for example, in contact with the box body 10. The electrodes 40 may be provided in a form in which they temporarily contact the box body 10 only while, for example, a work staff member (inspector) or the like performs an operation to determine the presence or absence of partial discharge from the box body 10. In the configuration shown in FIG. 2, one electrode 40 is provided on the box body 10, but multiple electrodes 40 may be provided on one box body 10. By providing multiple electrodes 40 on one box body 10, the measurement device 100 can measure the surface potential of the box body 10 with higher accuracy.

A common ground busbar 20 is disposed at the bottom of the box 10. The ground busbar 20 is connected to a ground electrode 30. The box 10 is composed of a front panel, a ceiling panel, a rear panel, a floor panel, and side panels. These front panel, ceiling panel, rear panel, floor panel, and side panels are collectively referred to as the constituent panels that make up the box 10. In the example shown in FIG. 2, the electrode 40 is fixed in contact with the front panel, but the electrode 40 may also be fixed in contact with any of the other constituent panels. The constituent panels are connected to the ground busbar 20.

2 shows a method of measuring the surface potential by the electrode 40 as a method of measuring the partial discharge signal, but is not limited to the surface potential. For example, the measuring device 100 may measure electromagnetic waves instead of the surface potential. In this case, the measuring device 100 may acquire an electrical signal from an antenna instead of the electrode 40. The antenna measures electromagnetic waves. The antenna outputs an electrical signal to the measuring device 100 based on the measured electromagnetic waves. The measuring device 100 may also measure a ground current instead of the surface potential. In this case, the measuring device 100 acquires an electrical signal from a sensor such as a high-frequency CT (Current Transformer) instead of the electrode 40. The sensor measures the ground current. The sensor outputs an electrical signal to the measuring device 100 based on the measured ground current. The measuring device 100 may acquire any physical quantity as long as it is a physical quantity obtained based on partial discharge of an electrical device. The physical quantity is, for example, a ground potential, an electromagnetic wave, a ground line current, vibration, or sound.

The measuring device 100 measures partial discharge waveform data of partial discharge (surface potential) for each electrode 40 (40a to 40n). The diagnosis of partial discharge in one electrode 40 will be described below. The partial discharge waveform data includes the signal strength and applied voltage of partial discharge. The measuring device 100 also transmits the partial discharge waveform data obtained by measurement to the partial discharge analyzer 110 at a predetermined timing.

Returning to FIG. 1, the partial discharge analysis device 110 receives partial discharge waveform data from the measurement device 100. The partial discharge analysis device 110 includes an analysis unit 111 that performs analysis using the partial discharge waveform data. The analysis unit 111 determines the presence or absence of a defect (abnormality) based on the partial discharge waveform data. Furthermore, when a defect occurs, the analysis unit 111 obtains partial discharge analysis data (analysis results) including the defect type (cause of the abnormality) and clustering based on the partial discharge waveform data.

The analysis unit 111 performs various analyses using, for example, AI (artificial intelligence). Here, the analysis unit 111 will be described in detail. The analysis unit 111 includes a feature extraction unit 112, a defect type identification unit 113, and a clustering unit 114.

The feature extraction unit 112 extracts the measured waveform for each period of the power supply voltage to generate multiple sub-waveforms. At this time, the feature extraction unit 112 extracts the measured waveform at the zero-cross timing of the power supply voltage. This is because partial discharges have the characteristic of occurring depending on the phase of the power supply voltage.

The feature extraction unit 112 extracts features of the partial discharge signal based on the multiple sub-waveforms that have been extracted. For example, the feature extraction unit 112 extracts the average intensity, variance, average maximum value, average minimum value, average number of peaks, etc. of the partial discharge signal.

The defect type identification unit 113, for example, calculates the average waveform of the multiple extracted sub-waveforms and converts it into a frequency spectrum by performing a fast Fourier transform. The defect type identification unit 113 determines the defect type based on a combination of the spectrum intensity for each frequency and the power supply voltage frequency. The defect type identification unit 113 determines the defect type using a trained model obtained by machine learning, for example. Specifically, a trained model trained according to the following procedure can be used. As the machine learning model, for example, a neural network model can be used.

A partial discharge signal is obtained in advance from an apparatus in which a desired defect has occurred through an experiment, and a learning dataset is prepared in which a combination of the spectral intensity for each frequency of the partial discharge signal and the power supply voltage frequency is used as an input sample, and a one-hot vector indicating the defect type is used as an output sample. The one-hot vector is an N+1-dimensional vector indicating N defect types and one "no defect", with only one element being 1 and the other elements being 0. Using the above learning dataset, the parameters of the machine learning model are updated so that the value of the output sample is output when an input sample is input, thereby obtaining a trained model. The defect type identification unit 113 inputs the combination of the spectral intensity for each frequency and the power supply voltage frequency into the trained model, and outputs the defect type corresponding to the element with the largest value among the obtained vectors.

The clustering unit 114 classifies the waveforms into one of a predetermined number of clusters. For example, the clustering unit 114 converts the average waveform of multiple sub-waveforms obtained from all the waveforms into a frequency spectrum by performing a fast Fourier transform. The clustering unit 114 performs clustering of each waveform based on a combination of the spectral intensity for each frequency of the multiple average waveforms and the power supply voltage frequency. The number of clusters is set in advance by a designer or the like. The clustering is performed, for example, by the k-means method. Note that the clustering unit 114 may perform a clustering process using multiple waveforms in advance to identify the boundary surfaces of the clusters, and classify the average waveform into one of multiple clusters based on the boundary surfaces.

The other system DB 117 stores various information about the workplace. The various information includes information about each device set up in the workplace and information about employees.

The partial discharge diagnosis support device 120 includes a memory unit 121, an acquisition unit 131, a display processing unit 132, an output unit 133, an input unit 134, and a notification unit 135. The memory unit 121 includes a partial discharge waveform data storage unit 122, a partial discharge analysis data storage unit 123, and a related information storage unit 124. The display processing unit 132 is an example of an output processing unit.

The partial discharge waveform data storage unit 122 stores the partial discharge waveform data output from the partial discharge analyzer 110. The partial discharge analysis data storage unit 123 stores the partial discharge analysis data analyzed by the analysis unit 111.

The related information storage unit 124 stores related information from among the information stored in the other system DB 117. The related information includes information on conditions that promote partial discharge. The information on the conditions is, for example, weather-related information on the weather.

The related information also includes information indicating a plurality of factors related to the occurrence of partial discharge. The information indicating the plurality of factors is, for example, the following information.
Peripheral device information: Information regarding the operation of peripheral devices located around the electrical device.
- Workplace information: Information regarding the operation of the workplace where the electrical equipment is installed.
・Employee information: Information relating to employees' work at the workplace.
-Railway information: Information regarding the operation of railways that travel near the workplace.

The acquisition unit 131 acquires partial discharge analysis data (analysis results) stored in the partial discharge analysis data storage unit 123. The partial discharge analysis data is a time-based analysis result based on the signal strength of partial discharges generated in the insulating parts of the electrical equipment stored in the box 10. The partial discharge diagnosis support device 120 may acquire partial discharge waveform data and analyze the partial discharge waveform data to obtain the analysis results. The display processing unit 132 displays a table (hereinafter referred to as a "two-axis correspondence table") based on the partial discharge analysis data acquired by the acquisition unit 131. The correspondence table represents first information indicating a first period on the first axis and second information different from the first information on the second axis. The two-axis correspondence table has a grid.

The output unit 133 outputs the display data of the two-axis correspondence table to the display 307 (see FIG. 3). The display 307 displays the display data output from the output unit 133.

(Specific examples of two-axis correspondence tables)
In the two-axis correspondence table, the second information is information indicating a second period that divides the first period. The two-axis correspondence table is represented with the first period as the first axis and the second period as the second axis. Furthermore, the display processing unit 132 displays the analysis results in the squares of the two-axis correspondence table.

The first period is, for example, a period based on a day. In this embodiment, the first period is one day. The second period is, for example, a period based on a time period. In this embodiment, the second period is two hours.

(About weather conditions)
Partial discharge is likely to be accelerated under the first condition. The first condition is, for example, a condition related to weather, specifically, a condition related to weather, humidity, air pressure, temperature, sunshine hours, etc. More specifically, for example, the first condition is a condition in which humidity is a predetermined value (e.g., 80%) or more. The input unit 134 (an example of a first selection unit) accepts a selection of a weather-related condition (first condition) from an operator (work staff) via an input device 306 (see FIG. 3). In response to the operator's selection, the display processing unit 132 displays, among the multiple squares, a square for a period (time period) that satisfies the first condition in a manner (extracted manner) different from the other squares (see FIG. 13). For example, the display processing unit 132 displays the square for a period that satisfies the first condition so as to suggest that partial discharge is about to begin.

(Indication of defect types)
In this embodiment, the analysis result includes a plurality of factors (hereinafter referred to as "defect types") that caused the partial discharge. There are, for example, seven types of defect types. The display processing unit 132 displays the defect types in the squares of the two-axis correspondence table. That is, the display processing unit 132 displays the defect types in the squares corresponding to each time period of each day (see FIG. 10).

(Signal strength display)
Moreover, the acquiring unit 131 acquires partial discharge waveform data from the partial discharge waveform data storage unit 122. The partial discharge waveform data includes the signal strength of partial discharge. The input unit 134 accepts an input related to display switching from the operator via the input device 306. The display processing unit 132 displays the defect type and the signal strength in a switchable manner in the squares of the two-axis correspondence table in accordance with the operator's selection (see FIG. 11 ).

(Conditions that are prone to defect generation)
Moreover, each of the plurality of defect types is more likely to occur under a second condition. The second condition is a condition related to the occurrence of a noise signal, and includes, for example, the following conditions.
- Conditions concerning the operating status of peripheral devices placed around electrical equipment.
- Conditions concerning the operation status of the business premises in which the electrical equipment is installed.
- Conditions relating to employees' working conditions at the workplace.
- Conditions regarding the operation of railways passing near the workplace.

The input unit 134 (an example of a second selection unit) receives a second condition from the operator. The display processing unit 132 displays the squares of the period that satisfy the second condition (e.g., the condition that a railway is present) in a manner different from the other squares according to the selection of the operator (see FIG. 12). For example, the display processing unit 132 displays the squares of the period that satisfy the second condition (e.g., the condition that a railway is present) in a manner indicating that the squares do not correspond to the defect type (defect type that is likely to occur when a railway is present) (an excluded manner). Note that the number of conditions that the input unit 134 receives from the operator may be only one or may be multiple.

(Regarding the counting of defective types)
The display processing unit 132 displays the tabulated results obtained by tabulating each of the analysis results displayed in the squares of the two-axis correspondence table. For example, the display processing unit 132 displays the tabulated results according to the conditions received from the operator. For example, under conditions in which a defect type is likely to occur (for example, under conditions in which peripheral devices are operating), the display processing unit 132 displays the tabulated results excluding the occurrence of the defect type. Moreover, under conditions in which partial discharge is likely to occur (under conditions in which humidity is 80% or higher), the display processing unit 132 displays the tabulated results in which the occurrence of the defect type is emphasized (to suggest that partial discharge is about to begin).

(Regarding notification of defective species)
The notification unit 135 notifies the user of the cause (defect type) of the partial discharge based on the counted result displayed by the display processing unit 132. For example, the notification unit 135 notifies the user of the defect type that is most likely to have occurred among a plurality of types of defect types. The notification unit 135 notifies the user of the defect type according to whether the notification function is turned on or off.

(Detailed display of various data)
The receiving unit, which is the input device 306 (see FIG. 3), receives the selection of one square from among the squares displayed in the correspondence table. The input unit 134 inputs the information on the square received by the input device 306. The display processing unit 132 displays details of the analysis result corresponding to the square input to the input unit 134 (see FIG. 15).

(Hardware Configuration of Partial Discharge Diagnostic Support Device 120)
Fig. 3 is an explanatory diagram showing an example of a hardware configuration of the partial discharge diagnosis support device 120 according to the embodiment. In Fig. 3, the partial discharge diagnosis support device 120 includes a CPU 301, a ROM 302, a RAM 303, a memory 304, a communication I/F 305, an input device 306, and a display 307. Each part is connected to each other via a bus 320.

The CPU 301 controls the entire partial discharge diagnosis support device 120. The ROM 302 stores various programs. The RAM 303 is used as a work area for the CPU 301. That is, the CPU 301 controls the entire partial discharge diagnosis support device 120 by executing the various programs stored in the ROM 302 while using the RAM 303 as a work area.

The memory 304 stores various data. For example, a non-volatile recording medium (non-temporary recording medium) such as a flash memory or a hard disk drive (HDD) is used as the memory. The memory 304 stores various programs such as a partial discharge diagnosis support program.

The communication I/F 305 manages the interface between the network and the inside, and controls the input of data from an external device and the output of data to an external device. Specifically, the communication I/F 305 is an interface that is connected to the partial discharge analyzer 110 via a communication line. The communication I/F 305 is connected to a network such as the Internet. The communication I/F 305 may also be a wireless communication interface such as a mobile phone line (e.g., LTE (Long Term Evolution), PHS (Personal Handy-Phone System), etc.) or Bluetooth (registered trademark), or a wired communication interface such as a modem or LAN adapter may also be used.

The input device 306 is a touch panel that displays a plurality of touch keys for inputting characters, numbers, various instructions, etc., or a hard key, etc. The input device 306 also includes a microphone.
The display 307 is a display device that displays images. The display 307 may be a touch panel type. The partial discharge diagnosis support device 120 may include a speaker.

The storage unit 121 shown in FIG. 1 is realized by the memory 304. The acquisition unit 131, the display processing unit 132, the output unit 133, the input unit 134, and the notification unit 135 are realized by the CPU 301. That is, the CPU 301 executes the partial discharge diagnosis support program stored in the memory 304 to realize the functions of each unit. Note that some or all of the acquisition unit 131, the display processing unit 132, the output unit 133, the input unit 134, and the notification unit 135 may be realized using a custom LSI (Large Scale Integrated Circuit) such as an ASIC (Application Specific Integrated Circuit) or a PLD (Programmable Logic Device). Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). Such integrated circuits are also examples of processors.

(Example of partial discharge waveform data)
Fig. 4 is an explanatory diagram showing an example of partial discharge waveform data 400 stored in the partial discharge waveform data storage unit 122 of the embodiment. In Fig. 4, the partial discharge waveform data 400 includes a date and time 401 and a waveform 402. The date and time 401 indicates a two-hour interval. The waveform 402 indicates waveform data in each time period. The waveform 402 is, for example, an average of the waveform data in each time period. The waveform 402 includes an applied voltage waveform 411 indicating the waveform of the applied voltage, and a signal intensity waveform 412 indicating the waveform of the signal intensity.

(Example of partial discharge analysis data)
5 is an explanatory diagram showing an example of partial discharge analysis data 500 stored in the partial discharge analysis data storage unit 123 of the embodiment. In FIG. 5, the partial discharge analysis data 500 includes a date and time 501, a signal intensity 502, a variance value 503, an AI identification result 504, and a clustering result 505. The date and time 501 corresponds to the date and time 401 in the partial discharge waveform data 400 (see FIG. 4). The signal intensity 502 is a digitalized version of the signal intensity waveform 412 (see FIG. 4), and is, for example, the average value of the signal intensity waveform 412. The variance value 503 indicates the degree of dispersion of the data of the signal intensity 502. The AI identification result 504 indicates the presence or absence of a defect and the type of defect. The clustering result 505 indicates the result of grouping similar data.

(Example of peripheral device information)
When a device is placed around an electrical device, the device may generate noise when it is in operation. The measurement device 100 may detect the noise as partial discharge. Therefore, in this embodiment, it is possible to display the grid based on whether the peripheral device is in operation or not.

Figure 6 is an explanatory diagram showing an example of peripheral device information 600 stored in the related information storage unit 124 of the embodiment. In Figure 6, the peripheral device information 600 includes a date and time 601 and peripheral devices 602a and 602b. The date and time 601 corresponds to the date and time 401 in the partial discharge waveform data 400 (see Figure 4). The peripheral devices 602a and 602b indicate the operating status (operating or non-operating) of the peripheral devices present around the box 10 in each time period.

(Example of workplace and employee information)
For example, if there is an employee who performs welding, there is a risk that the measuring device 100 may detect discharge due to welding as partial discharge. Therefore, in this embodiment, it is possible to display the grid based on the presence or absence of operation of the workplace and the working status of employees.

Figure 7 is an explanatory diagram showing an example of workplace/employee information 700 stored in the related information storage unit 124 of the embodiment. In Figure 7, the workplace/employee information 700 includes date and time 701, workplace 702, and employees 703a, 703b, and 703c. Date and time 701 corresponds to date and time 401 in the partial discharge waveform data 400 (see Figure 4). The workplace 702 indicates the operation status (operating or not operating) of each time period of the workplace where the box 10 is located. In addition, employees 703a, 703b, and 703c indicate the working status (working or not working) of each employee working at the workplace 702 for each time period.

(Example of railway information)
When a train passes near a business site, noise may be generated. The measurement device 100 may detect the noise as partial discharge. Therefore, in this embodiment, it is possible to display the grid based on whether or not a train is running.

Figure 8 is an explanatory diagram showing an example of railway information 800 stored in the related information storage unit 124 of the embodiment. In Figure 8, railway information 800 includes date and time 801 and railways 802a and 802b. Date and time 801 corresponds to date and time 401 in partial discharge waveform data 400 (see Figure 4). Railways 802a and 802b show the operation status (suspended or operating) of railways traveling near the workplace in each time period. Note that the operation status shown for railways 802a and 802b is "operating" if at least one train travels in each time period, but it may also be "operating" if a certain number of times (e.g., three times) or more have traveled in each time period.

(Example of weather-related information)
Partial discharges may occur more easily depending on weather conditions. Therefore, even if the measuring device 100 does not normally detect partial discharges, it may detect partial discharges depending on weather conditions. Therefore, in this embodiment, it is possible to display the grid based on weather information.

9 is an explanatory diagram showing an example of weather-related information 900 stored in the related information storage unit 124 of the embodiment. In FIG. 9, the weather-related information 900 includes date and time 801, weather 902, humidity 903, air pressure 904, temperature 905, and sunshine hours 906. Date and time 901 corresponds to date and time 401 in the partial discharge waveform data 400 (see FIG. 4). Weather 902 indicates the weather in each time zone of the area where the business establishment is located, and specifically indicates one of clear, sunny, cloudy, rain, snow, thunder, etc. Humidity 903 indicates the humidity in each time zone of the area where the business establishment is located. Air pressure 904 indicates the air pressure in each time zone of the area where the business establishment is located. Temperature 905 indicates the temperature in each time zone of the area where the business establishment is located. Sunshine hours 906 indicates the sunshine hours in each time zone of the area where the business establishment is located.

(Example of a screen displayed on the display 307)
Next, examples of screens relating to partial discharge displayed on the display 307 will be described with reference to FIGS.

(Screen when no filter is applied)
10 is an explanatory diagram showing an example of a screen of an AI identification result without a filter according to an embodiment. As shown in FIG. 10, a two-axis correspondence table 1000, a summary result 1010, a display data selection area 1020, an exclusion filter selection area 1030, and an extraction filter selection area 1040 are displayed on the display 307.

The two-axis correspondence table 1000 shows the date on the vertical axis and the time period on the horizontal axis. Note that the vertical and horizontal axes may be interchanged in the two-axis correspondence table 1000, i.e., the vertical axis may show the time period and the horizontal axis may show the date. The two-axis correspondence table 1000 has squares 1001 (cells). The AI identification result is selected in the display data selection area 1020. Therefore, the two-axis correspondence table 1000 shows the AI identification result. Specifically, the squares 1001 in the two-axis correspondence table 1000 show the presence or absence of defects or the defect type in each time period. In the two-axis correspondence table 1000, "no defect", "defect type 1", "defect type 2", and "defect type 3" are displayed in different display modes. This allows the operator to grasp the tendency of "no defect" and defect type at a glance.

The tally result 1010 shows a tally of the squares 1001 for each defect type in the AI identification results in the two-axis correspondence table 1000. For example, the number of "no defect type" cases (the number of squares 1001) shows "36". The number of "voids" (= defect type 1) shows "27". The number of "creepage" (= defect type 2) shows "45". The number of "peeling" (= defect type 3) shows "12". This allows the operator to grasp at a glance the number of "no defects" and the number of defect types.

The display data selection area 1020 accepts selectable results from among AI identification results, signal strength, and clustering results. The exclusion filter selection area 1030 accepts selection of related information (exclusion filter) to be excluded from the defect types shown in the two-axis correspondence table 1000. The accepted exclusion filters are filters that exclude things that may cause defect types, such as the operation of peripheral devices, the operation of business establishments, the work of employees, and train operations.

The extraction filter selection area 1040 accepts the selection of related information (extraction filter) to be extracted from among the defect types shown in the two-axis correspondence table 1000. The extraction filter to be accepted is a filter that extracts things that may promote partial discharge, such as a specified humidity, a specified temperature, weather, a specified air pressure, or a specified number of hours of sunlight.

(Signal strength display screen)
When the display data selection area 1020 is selected on the screen shown in FIG. 10 and "signal strength" is selected from the selection items, the screen transitions to the screen shown in FIG.
Fig. 11 is an explanatory diagram showing an example of a screen of signal strength data in the embodiment. In Fig. 11, the value of the signal strength itself is displayed in the squares 1001 of the two-axis correspondence table 1100. Each signal strength shown in the two-axis correspondence table 1100 is displayed in a different display mode depending on the range of the value. Specifically, "0 or more to 0.1 or less", "more than 0.1 to 0.2 or less", "more than 0.2 to 0.3 or less", and "more than 0.3 to 0.4 or less" are displayed in different display modes. This allows the operator to grasp the range of the signal strength values at a glance.

The tally result 1110 also shows the tally for each range of signal strength in the two-axis correspondence table 1100. This allows the operator to grasp at a glance the number for each range of signal strength.

(Screen with exclusion filter applied)
Moreover, when the exclusion filter selection area 1030 is selected on the screen shown in FIG. 10 and then "peripheral device 1" is selected from the selection items, the screen transitions to the screen shown in FIG.
Fig. 12 is an explanatory diagram showing an example of a screen of the AI identification result when the exclusion filter of the embodiment is applied. In the two-axis correspondence table 1200 shown in Fig. 12, an exclusion area 1201 indicates a time period during which peripheral device 1 (see peripheral device 602a in Fig. 6) is operating. In the exclusion area 1201, "defect type 2" is displayed in large numbers. Therefore, the operator can diagnose that "defect type 2" has occurred due to the operation of peripheral device 1.

The tally result 1210 shows the tally for each defect type after applying the exclusion filter. Specifically, it shows "no defect type" and the number of each defect type in the portion of the two-axis correspondence table 1200 excluding the exclusion area 1201. This allows the operator to grasp at a glance the number of "no defects" and the number of defect types after applying the exclusion filter.

The notification image 1220 is an image based on the tally results 1010 and 1210. Specifically, when comparing the tally results 1010 and 1210, creepage (defect type 2) has decreased the most. Therefore, it can be presumed that "defect type 2" occurred as a result of peripheral device 1 being in operation. Therefore, the notification image 1220 indicates that "defect type 2" shown in the excluded area 1201 is not caused by deterioration of the insulation in the switchgear.

Note that such notifications are not limited to when peripheral device 1 is operating, but may also be issued in other cases (for example, when it is presumed that the cause is the operation of a train or that an employee who performs welding is at work). Also, if the notification function is off, notification image 1220 is not displayed.

(Screen with extraction filter applied)
Furthermore, when the extraction filter selection area 1040 is selected on the screen shown in FIG. 12 and then "humidity≧80%" is selected from the selection items, the screen transitions to the screen shown in FIG.
FIG. 13 is an explanatory diagram showing an example of a screen of an AI identification result when the extraction filter of the embodiment is applied. In the two-axis correspondence table 1300 shown in FIG. 13, an extraction area 1301 is displayed in addition to the exclusion area 1201. The extraction area 1301 shows a time period when the humidity is 80% or more (see humidity 903 in FIG. 9). In the extraction area 1301, many "defect type 1" are displayed. Therefore, the operator can diagnose that "defect type 1" is promoted when the humidity is 80% or more. In other words, the operator can diagnose that the "defect type 1" shown in the extraction area 1301 is starting to deteriorate the insulation part in the switchgear.

The tally result 1310 shows the tally for each defect type after applying the extraction filter. Specifically, in the two-axis correspondence table 1300, "no defect type" and the number of each defect type are shown in the portion of the extraction area 1301. This allows the operator to grasp at a glance the number of "no defects" and the number of defect types after applying the extraction filter.

The alarm image 1320 is an image based on the tally result 1310. Specifically, the tally result 1310 indicates that only voids (defect type 1) have occurred. It can be estimated that "defect type 1" is promoted when the humidity is 80% or higher. For this reason, the alarm image 1320 indicates that the insulation part is beginning to deteriorate for "defect type 1" shown in the extracted area 1301.

Note that such notifications are not limited to being based on humidity, but may be based on, for example, humidity, air pressure, temperature, or a combination of these. Also, if the notification function is off, the notification image 1320 is not displayed.

(Signal strength display screen)
When the display data selection area 1020 is selected on the screen shown in FIG. 13 and then "signal strength" is selected from the selection items, the screen transitions to the screen shown in FIG.
14 is an explanatory diagram showing an example of a screen of signal strength data according to an embodiment. A two-axis correspondence table 1400 shown in FIG 14 shows the value of the signal strength itself, and an exclusion area 1201 and an extraction area 1301 are displayed.

The tally result 1410 shows the tally for each range of signal strength after applying the extraction filter. This allows the operator to grasp at a glance the number for each range of signal strength after applying the extraction filter.

(Detailed display screen of square 1001)
When one square 1001 is selected in the two-axis correspondence tables 1000 to 1400 shown in FIGS. 10 to 14, a transition to a detailed display screen 1500 shown in FIG. 15 is made.
15 is an explanatory diagram showing an example of a detailed display screen 1500 of various data of the square 1001 according to the embodiment. The detailed display screen 1500 includes a partial discharge waveform data display area 1501 for a certain time period, a partial discharge analysis data display area 1502 for the same time period, and a related information display area 1503 for the same time period.

The partial discharge waveform data display area 1501 shows the partial discharge waveform data 400 for the same time period extracted from the partial discharge waveform data storage unit 122 (see FIG. 4). The partial discharge analysis data display area 1502 shows the partial discharge analysis data 500 for the same time period extracted from the partial discharge analysis data storage unit 123 (see FIG. 5). The related information display area 1503 shows peripheral device information 600, workplace and employee information 700, railway information 800, and weather-related information 900 for the same time period extracted from the related information storage unit 124 (see FIG. 6 to FIG. 9).

By displaying such a detailed display screen 1500, the operator can view various conditions during the target time period on a single screen. Therefore, the operator can efficiently analyze the partial discharge diagnosis during that time period.

Figure 16 is a flowchart showing an example of a diagnostic support process related to partial discharge performed by the partial discharge diagnostic support device 120 of the embodiment. In Figure 16, the partial discharge diagnostic support device 120 determines whether or not the start of diagnostic support has been accepted (step S1601). The start of diagnostic support is, for example, accepting the selection of a button to start diagnostic support.

The partial discharge diagnostic support device 120 waits until it receives a command to start diagnostic support (step S1601: NO). When it receives a command to start diagnostic support (step S1601: YES), the partial discharge diagnostic support device 120 acquires partial discharge waveform data 400 from the partial discharge waveform data storage unit 122 and acquires partial discharge analysis data 500 from the partial discharge analysis data storage unit 123 (step S1602).

Then, the partial discharge diagnosis support device 120 displays the two-axis correspondence table on the display 307 (step S1603). At this time, the partial discharge diagnosis support device 120 may display predetermined display data (e.g., defect type) in the two-axis correspondence table.

Then, the partial discharge diagnosis support device 120 judges whether or not a selection of display data based on an operation of the display data selection area 1020 (see FIG. 10) has been accepted (step S1604). If a selection of display data has not been accepted (step S1604: NO), the partial discharge diagnosis support device 120 proceeds to step S1606. If a selection of display data has been accepted (step S1604: YES), the partial discharge diagnosis support device 120 performs aggregation according to the accepted selection (AI identification results, signal strength, clustering results) and switches to a screen according to the selection (step S1605).

Next, the partial discharge diagnosis support device 120 determines whether or not a filter selection based on an operation of the exclusion filter selection area 1030 (see FIG. 10) or the extraction filter selection area 1040 has been accepted (step S1605). If a filter selection has not been accepted (step S1606: NO), the partial discharge diagnosis support device 120 proceeds to step S1609. If a filter selection has been accepted (step S1606: YES), the partial discharge diagnosis support device 120 acquires related information according to the selected filter and item from among the peripheral device information 600, the business establishment/employee information 700, the railway information 800, and the weather-related information 900 (step S1607).

Then, the partial discharge diagnosis support device 120 performs aggregation according to the received selection (e.g., "peripheral device 1" or "humidity ≧ 80%) and displays the area according to the selection (e.g., the excluded area 1201 in FIG. 12 or the extracted area 1301 in FIG. 13) (step S1608).

Next, the partial discharge diagnosis support device 120 determines whether the notification function is on (step S1609). If the notification function is off (step S1609: NO), the partial discharge diagnosis support device 120 proceeds to step S1611. If the notification function is on (step S1609: YES), the partial discharge diagnosis support device 120 issues a notification regarding the defect type based on the aggregation result (step S1610).

Then, the partial discharge diagnosis support device 120 judges whether or not the selection of the square 1001 of the two-axis correspondence table has been accepted (step S1611). If the selection of the square 1001 has not been accepted (step S1611: NO), the partial discharge diagnosis support device 120 proceeds to step S1614. If the selection of the square 1001 has been accepted (step S1611: YES), the partial discharge diagnosis support device 120 extracts data for the corresponding time from the partial discharge waveform data 400, partial discharge analysis data 500, peripheral device information 600, workplace/employee information 700, railway information 800, and weather-related information 900 (step S1612).

Then, the partial discharge diagnostic support device 120 displays the detailed display screen 1500 (see FIG. 15) (step S1613). Next, the partial discharge diagnostic support device 120 determines whether or not to end the diagnostic support (step S1614). Ending the diagnostic support is, for example, by accepting the selection of a button to end the diagnostic support.

If the partial discharge diagnosis support device 120 does not accept the end of the diagnosis support (step S1614: NO), the device returns to step S1604. On the other hand, if the partial discharge diagnosis support device 120 accepts the end of the diagnosis support (step S1614: YES), the device 120 ends the series of processes.

As described above, the partial discharge diagnosis support device 120 of the embodiment displays a two-axis correspondence table based on the partial discharge analysis data 500, in which the first information indicating the first period is taken on the first axis, and the second information different from the first information is taken on the second axis. This allows an operator such as a work staff member to easily grasp the analysis results related to partial discharge for each first period. Therefore, the partial discharge diagnosis support device 120 of the embodiment can support the operator in diagnosing the deterioration state of the insulation part.

In addition, in this embodiment, the second information is information indicating a second period that divides the first period. This makes it possible to divide the first period into second periods and display each analysis result in a square. Therefore, the analysis results can be displayed in an easier-to-read manner.

In addition, in this embodiment, the first period is a period based on days, and the second period is a period based on time periods. Therefore, the analysis results for each time period on each day can be displayed in a more easily viewable manner. Also, since the related information is information for each day and each time period, the two-axis correspondence table has two axes, one based on days and the other based on time periods, so that the related information can be effectively reflected.

In addition, in this embodiment, in response to the operator's selection, the squares in the period that meet the first condition for promoting partial discharge are displayed in a different manner from the other squares. This makes it possible to suggest that a partial discharge may be about to begin. Therefore, it is possible to support the early detection of partial discharge.

In addition, in this embodiment, the first condition is a weather-related condition. This allows the first condition to be the condition that is most likely to promote partial discharge. Therefore, it is possible to obtain an accurate diagnosis result that indicates that partial discharge may be about to begin.

In addition, in this embodiment, the defect type is displayed in the squares of the two-axis correspondence table. This helps the operator diagnose the cause of partial discharge.

In addition, in this embodiment, the partial discharge diagnosis support device 120 is configured to switch between displaying defect types and signal strengths in the squares of the two-axis correspondence table according to the operator's selection. This makes it possible to display not only defect types but also actual signal strengths. Therefore, the operator can more efficiently diagnose the cause of partial discharges, and obtain highly reliable diagnosis results.

In addition, in this embodiment, the partial discharge diagnosis support device 120 displays the squares of the period that satisfy the second condition related to the occurrence of a noise signal in a manner different from the other squares, according to the selection of the operator. Therefore, even if there is a defect type due to the occurrence of a noise signal, it is possible to display it in a manner that indicates that the defect type does not correspond to the second condition. This allows the operator to obtain a more reliable partial discharge diagnosis result.

In addition, in this embodiment, the second condition includes any of the following: a condition related to the operating status of peripheral devices, a condition related to the operating status of the workplace, a condition related to the working status of employees, and a condition related to the operating status of trains traveling near the workplace. This makes it possible to obtain the second condition under which a defect type is most likely to occur due to the generation of a noise signal. Therefore, even if a defect type exists, it is possible to prevent the defect type from occurring according to the condition. Therefore, the operator can accurately obtain a highly reliable diagnosis result.

In addition, in this embodiment, the partial discharge diagnosis support device 120 displays the results of tallying up the analysis results (defect types) displayed in the squares of the two-axis correspondence table. This allows the operator to grasp at a glance the number of "no defects" and the number of defect types. This makes it easier for the operator to grasp the presence or absence of partial discharge and its cause.

In addition, in this embodiment, the partial discharge diagnosis support device 120 displays details of the analysis results corresponding to the received squares in the two-axis correspondence table (see the detailed display screen 1500 in FIG. 15). This allows the operator to understand various situations during the period indicated by the squares. Therefore, the operator can efficiently perform analysis of the partial discharge diagnosis during that period.

In addition, in this embodiment, the partial discharge diagnosis support device 120 is configured to notify the operator of the cause (defect type) of the partial discharge occurrence based on the aggregation results. Therefore, it is possible to more efficiently support the operator in diagnosing the deterioration state of the insulation part.

(Modification of the embodiment)
Modifications of the embodiment will be described below. In each of the following modifications, the contents described in the above-mentioned embodiment will be omitted as appropriate. It is also possible to combine the configurations shown in the above-mentioned embodiment and each modification. Specifically, the configuration may include all of the above-mentioned embodiment and the following modifications, or the configuration may combine any of the above-mentioned embodiment and the following modifications.

(Variation 1)
First, a description will be given of Modification 1. In the above-described embodiment, the second axis in the two-axis correspondence table is set to information indicating a second period. In Modification 1, in addition to or instead of such a configuration, a description will be given of the second axis in the two-axis correspondence table being set to related information.

Figure 17 is an explanatory diagram showing an example of a screen of variant 1 regarding partial discharge displayed on the display 307 of the embodiment. As shown in Figure 17, the display 307 displays a two-axis correspondence table 1700, a date selection area 1710, and a defect type selection area 1720.

In the first modification, the partial discharge diagnosis support device 120 displays a two-axis correspondence table 1700 based on the partial discharge analysis data 500, in which the first information indicating the time period is shown on the first axis and the related information is shown on the second axis. Specifically, the two-axis correspondence table 1700 shows the related information on the vertical axis and the time period on the horizontal axis. Note that the horizontal axis may be any information indicating a period, and may be, for example, another period such as a date. Furthermore, in the two-axis correspondence table 1700, the vertical and horizontal axes may be interchanged, i.e., the time period may be shown on the vertical axis and the related information may be shown on the horizontal axis.

The date selection area 1710 is an area that accepts the selection of a date. The defect type selection area 1720 accepts the selection of the type of defect to be displayed in the two-axis correspondence table 1700. The two-axis correspondence table 1700 shows the relevant information for each time period in which defect type 1 occurred.

Even if the two-axis correspondence table 1700 according to the first modification is displayed, the operator can efficiently diagnose the cause of partial discharge, thereby obtaining highly reliable diagnosis results.

(Variation 2)
First, a description will be given of Modification 2. In the above-described embodiment, the description of each axis in the two-axis correspondence table is fixed. In Modification 1, in addition to or instead of such a configuration, a description will be given of making each axis in the two-axis correspondence table changeable.

In the two-axis correspondence table according to the second modification, the vertical axis may be changed to the order of days of the week. For example, using information for one month, data may be displayed in an order such that four data items are for Mondays, four data items are for Tuesdays, and so on. This allows the deterioration status of the insulation to be diagnosed for each day of the week.

In addition, in the two-axis correspondence table according to the second modification, the horizontal axis may be changed to display dates, and the vertical axis may be changed to display weeks. In addition, in the two-axis correspondence table according to the second modification, the horizontal axis may be changed to display weeks, and the vertical axis may be changed to display months. Even in this way, the operator can easily grasp the analysis results such as the deterioration status of the insulation part for each period.

At least a part of the functions of the partial discharge diagnosis support device 120 in the above-mentioned embodiment may be realized by a computer. In that case, a program for realizing this function may be recorded in a computer-readable recording medium. Also, the program recorded in this recording medium may be read into a computer system and executed to realize the function. The term "computer system" here includes hardware such as an OS and peripheral devices. Also, the term "computer-readable recording medium" refers to a storage device such as a hard disk built into the computer system. Storage devices also include portable media such as flexible disks, optical magnetic disks, ROMs, CD-ROMs, DVD-ROMs, and USB memories. Furthermore, the term "computer-readable recording medium" may be one that dynamically holds a program for a short period of time. Specifically, it is a communication line when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. Also, the term "computer-readable recording medium" may include one that holds a program for a certain period of time. Specifically, it is a volatile memory inside a computer system that is a server or a client. Also, the above-mentioned program may be one for realizing part of the above-mentioned functions. Furthermore, the above program may be capable of implementing the above-mentioned functions in combination with a program already stored in the computer system.

Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

100...Measuring device 110...Partial discharge analysis device 111...Analysis unit 120...Partial discharge diagnosis support device 121...Memory unit 122...Partial discharge waveform data storage unit 123...Partial discharge analysis data storage unit 124...Related information storage unit 131...Acquisition unit 132...Display processing unit 133...Output unit 134...Input unit 135...Notification unit 301...CPU 302...ROM 303...RAM 304...Memory 305...Communication I/F 306...Input device 307...Display

Claims (13)

an acquisition unit that acquires analysis results by time based on the signal strength of partial discharges generated in an insulating part of an electrical device housed in a housing;
an output processing unit that outputs a table representing the analysis result acquired by the acquisition unit, the table having a plurality of cells with a first axis representing first information indicating a first period and a second axis representing second information different from the first information;
Equipped with
The second information is information indicating a second period that divides the first period.
Partial discharge diagnostic support device. The first period is a period based on days,
The second period is a period based on a time period.
The partial discharge diagnosis support device according to claim 1 . a first selection unit that accepts a selection of a first condition under which partial discharge is promoted;
the output processing unit outputs, in response to a selection by an operator, a square among the plurality of squares for a period that satisfies the first condition in a display mode different from that of other squares;
The partial discharge diagnosis support device according to claim 1 or 2 . The first condition is a weather-related condition.
The partial discharge diagnosis support device according to claim 3 . The analysis result includes a plurality of factors related to the occurrence of the partial discharge,
the output processing unit outputs the factor to a cell in the table.
The partial discharge diagnosis support device according to claim 1 . The acquisition unit acquires the signal strength,
the output processing unit switchably outputs the factor and the signal intensity to a cell of the table in response to a selection by an operator;
The partial discharge diagnosis support device according to claim 5 . a second selection unit that accepts a second condition related to generation of a noise signal;
The output processing unit outputs a square for a period that satisfies the second condition in a display mode different from that of other squares in response to a selection by an operator.
The partial discharge diagnosis support device according to claim 1 . The second condition includes any one of a condition regarding the operation status of peripheral devices arranged around the electrical device, a condition regarding the operation status of a workplace where the electrical device is arranged, a condition regarding the working status of employees at the workplace, and a condition regarding the operation status of a railway traveling in the vicinity of the workplace.
The partial discharge diagnosis support device according to claim 7 . The output processing unit outputs a summary result obtained by summarizing the analysis results displayed in the cells of the table.
The partial discharge diagnosis support device according to any one of claims 1 to 8 . a notification unit that notifies a cause of the occurrence of the partial discharge based on the counting result;
The partial discharge diagnosis support device according to claim 9 . a reception unit for receiving a selection of any one of the squares of the table from an operator,
The output processing unit outputs details of the analysis result corresponding to the square accepted by the accepting unit.
The partial discharge diagnosis support device according to any one of claims 1 to 9 . A computer used in the partial discharge diagnosis support device,
An acquisition step of acquiring a time-based analysis result based on a signal strength of a partial discharge generated in an insulating portion of an electrical device housed in a housing;
an output processing step of outputting a table showing the analysis results obtained in the obtaining step, the table having a plurality of cells with a first axis representing first information indicating a first period and a second axis representing second information different from the first information;
Perform a process including
The second information is information indicating a second period that divides the first period.
Diagnostic aid methods. A computer used in the partial discharge diagnosis support device includes:
Obtaining analysis results by time based on the signal strength of partial discharges occurring in the insulating parts of electrical equipment housed in the housing;
outputting a table showing the obtained analysis results, the table having a plurality of cells with a first axis representing first information indicating a first period and a second axis representing second information different from the first information;
Execute the process ,
The second information is information indicating a second period that divides the first period.
program.

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