Transformer monitoring device, method and equipment and readable storage medium

Abstract

The invention relates to a transformer monitoring device, method and equipment and a readable storage medium, and relates to the field of transformer monitoring. The operation state of the target transformer can be comprehensively monitored and analyzed to obtain a comprehensive monitoring result of the operation state of the target transformer, the problem that the target transformer has a fault risk due to a single monitoring result is avoided, and the comprehensiveness and accuracy of the monitoring result of the target transformer are improved. The transformer monitoring device comprises a signal acquisition module, a signal processing module and a judgment module, the signal acquisition module is used for acquiring a real-time signal of a target transformer, and the signal processing module is used for receiving the real-time signal and processing the real-time signal to generate a processed real-time signal; and the judgment module is used for comparing the size relationship between the processed real-time signal and the threshold data, judging whether the target transformer has a fault or not, and generating a judgment result.

Description

Technical Field

[0001] This application relates to the technical field of transformer monitoring, and particularly relates to a transformer monitoring device, method, equipment and readable storage medium. Background Art

[0002] With the increase of the operation years of transformers, the failure rate of transformers has increased significantly, and the frequency of fast-evolving faults has gradually increased. Transformer faults can evolve rapidly in a short time, resulting in damage to power equipment and even endangering the personal safety of operation and maintenance personnel during the fault troubleshooting process.

[0003] However, in traditional technologies, the monitoring means of existing transformer monitoring equipment are single, unable to comprehensively cover various operation state information of transformers, unable to effectively integrate and analyze all operation data of transformers, difficult to provide a comprehensive, fast and convenient evaluation and fault diagnosis for the operation state of transformers, and thus unable to perform timely fault repair on transformers, resulting in damage to power equipment. Summary of the Invention

[0004] The purpose of this application is to provide a transformer monitoring device, method, equipment and readable storage medium, which solves the problems of small transformer monitoring range and inability to effectively integrate and analyze all operation data of transformers, and can provide a comprehensive, fast and convenient evaluation and fault diagnosis result for the operation state of transformers. To achieve the purpose of this application, the following technical solutions are provided:

[0005] In the first aspect, this application provides a transformer monitoring device, including:

[0006] A signal acquisition module, configured to acquire real-time signals of a target transformer, where the real-time signals include at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high frequency partial discharge signals, grounding electrical signals, mechanical vibration signals and load electrical signals;

[0007] A signal processing module, the input end of the signal processing module is electrically connected to the output end of the signal acquisition module, and the signal processing module is configured to receive the real-time signals and process the real-time signals to generate the processed real-time signals;

[0008] A judgment module, the input end of the judgment module is electrically connected to the output end of the signal processing module, and the judgment module is configured to compare the size relationship between the processed real-time signals and threshold data, judge whether the target transformer has a fault, and generate a judgment result.

[0009] In one of the embodiments, the signal processing module includes:

[0010] A data cleaning module, the input end of the data cleaning module is electrically connected to the output end of the signal acquisition module, and the data cleaning module is used to clean at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, ultra-high frequency partial discharge signal and mechanical vibration signal by means of wavelet transform method.

[0011] In one embodiment, the signal processing module further includes:

[0012] A first data processing module, the input end of the first data processing module is electrically connected to the output end of the data cleaning module, and the output end of the first data processing module is electrically connected to the input end of the judgment module. The first data processing module is used to process at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, and ultra-high frequency partial discharge signal after cleaning by means of the PSO-SVM hybrid optimization algorithm.

[0013] In one embodiment, the signal processing module further includes:

[0014] A second data processing module, the input end of the second data processing module is electrically connected to the output end of the data cleaning module, and the output end of the first data processing module is electrically connected to the input end of the judgment module. The second data processing module is used to process the mechanical vibration signal after cleaning by means of the SVM optimization algorithm.

[0015] In one embodiment, it further includes:

[0016] A data storage module, the input end of the data storage module is electrically connected to the output end of the signal processing module, and also, the input end of the data storage module is electrically connected to the output end of the judgment module. The data storage module is used to receive and store the processed real-time signal and the judgment result.

[0017] In one embodiment, it further includes:

[0018] A communication module, the input end of the communication module is communicatively connected to the output end of the sensor connected to the target transformer, and the output end of the communication module is communicatively connected to the input end of the signal acquisition module. The communication module is used to send the real-time signal output by the sensor connected to the target transformer to the signal acquisition module.

[0019] In a second aspect, the present application provides a transformer monitoring method, including:

[0020] Collect real-time signals of the target transformer, where the real-time signals include at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high frequency partial discharge signals, grounding electrical signals, mechanical vibration signals, and load electrical signals;

[0021] Receive the real-time signals and process the real-time signals to generate the processed real-time signals;

[0022] Compare the magnitude relationship between the processed real-time signals and the threshold data, determine whether the target transformer has a fault, and generate a judgment result.

[0023] In a third aspect, the present application provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the transformer monitoring method described in any item of the second aspect are implemented.

[0024] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the transformer monitoring method described in any item of the second aspect are implemented.

[0025] In a fifth aspect, the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the transformer monitoring method described in any item of the second aspect are implemented.

[0026] The transformer monitoring device, method, equipment, and readable storage medium provided by the present application collect at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high frequency partial discharge signals, grounding electrical signals, mechanical vibration signals, and load electrical signals of the target transformer through a signal acquisition module. Furthermore, a judgment module can compare the acquired signals with threshold data to obtain the operating state of the target transformer, comprehensively monitor and analyze the operating state of the target transformer to obtain a comprehensive monitoring result of the operating state of the target transformer, avoid the problem that a single monitoring result poses a risk of faults in the target transformer, and improve the comprehensiveness and accuracy of the monitoring result of the target transformer. And through the signal processing module, the signals of the target transformer collected can be calculated and cleaned to obtain accurate data as a judgment basis for the judgment module, thereby improving the reliability of the judgment result. Description of the Drawings

[0027] To more clearly illustrate the technical solutions in the embodiments of the present disclosure or in the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0028] Figure 1 is a schematic structural diagram of a transformer monitoring device provided in an embodiment;

[0029] Figure 2 is a schematic structural diagram of a transformer monitoring device provided in another embodiment;

[0030] Figure 3 is a schematic structural diagram of a transformer monitoring device provided in yet another embodiment;

[0031] Figure 4 is a schematic structural diagram of a transformer monitoring device provided in still another embodiment;

[0032] Figure 5 is a schematic structural diagram of a transformer monitoring device provided in an embodiment;

[0033] Figure 6 is a schematic flowchart of a transformer monitoring method provided in an embodiment;

[0034] Figure 7 is a schematic structural diagram of a computer device provided in real time by this application;

[0035] Figure 8 is a schematic structural diagram of a computer-readable storage medium provided in real time by this application.

[0036] Description of the reference numerals

[0037] 10. Signal acquisition module; 20. Signal processing module; 201. Data cleaning module; 202. First data processing module; 203. Second data processing module; 30. Judgment module; 40. Data storage module; 50. Communication module. Detailed implementation manners

[0038] To facilitate the understanding of this application, the following will describe this application more comprehensively with reference to the relevant accompanying drawings. The preferred embodiments of this application are given in the accompanying drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of this application more thorough and comprehensive.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms used in the description of this application herein are for the purpose of describing specific embodiments only and are not intended to limit this application.

[0040] It should be understood that when an element or layer is referred to as being "on", "adjacent to", "connected to" or "coupled to" another element or layer, it can be directly on, adjacent to, connected or coupled to the other element or layer, or intervening elements or layers may be present. In contrast, when an element is referred to as being "directly on", "directly adjacent to", "directly connected to" or "directly coupled to" another element or layer, there are no intervening elements or layers. It should be understood that although the terms first, second, third, etc. may be used to describe various elements, components, regions, layers, doping types and / or portions, these elements, components, regions, layers, doping types and / or portions should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer, doping type or portion from another element, component, region, layer, doping type or portion. Thus, without departing from the teachings of the present invention, the first element, component, region, layer, doping type or portion discussed below may be referred to as a second element, component, region, layer or portion; for example, the first doping type may be referred to as the second doping type, and similarly, the second doping type may be referred to as the first doping type; the first doping type and the second doping type are different doping types. For example, the first doping type may be P-type and the second doping type may be N-type, or the first doping type may be N-type and the second doping type may be P-type.

[0041] Spatial relationship terms such as "under", "below", "beneath", "underneath", "above", "over", etc. may be used herein to describe the relationship of one element or feature shown in the figures to other elements or features. It should be understood that, in addition to the orientation shown in the figures, spatial relationship terms also include different orientations of the device in use and operation. For example, if the device in the figures is flipped, an element or feature described as "under" or "beneath" or "underneath" another element or feature will be oriented "over" the other element or feature. Thus, the exemplary terms "under" and "beneath" can include both an upper and a lower orientation. In addition, the device may also include additional orientations (such as rotating 90 degrees or other orientations), and the spatial descriptors used herein are to be interpreted accordingly.

[0042] As used herein, the singular forms "a", "an" and "the" may also include the plural forms unless the context clearly dictates otherwise. It should also be understood that when the terms "comprising" and / or "including" are used in this specification, the presence of the stated features, integers, steps, operations, elements and / or components can be determined, but one or more other features, integers, steps, operations, elements, components and / or groups are not precluded from being present or added. Also, as used herein, the term "and / or" includes any and all combinations of the associated listed items.

[0043] Embodiments of the invention are described herein with reference to cross-sectional views that are schematic illustrations of ideal embodiments (and intermediate structures) of the invention, such that variations in the shapes shown, for example, due to manufacturing techniques and / or tolerances, are to be expected. Accordingly, embodiments of the invention should not be construed as limited to the particular shapes of regions shown herein, but include shape deviations, for example, due to manufacturing techniques. For example, an implantation region shown as rectangular will typically have rounded or curved features at its edges and / or an implantation concentration gradient, rather than a binary change from the implanted region to the non-implanted region. Similarly, a buried region formed by implantation may result in some implantation in the region between the buried region and the surface through which the implantation takes place. Thus, the regions shown in the figures are substantially schematic, their shapes do not represent the actual shapes of regions of the device, and do not limit the scope of the invention.

[0044] As the operation years of the transformer increase, the failure rate of the transformer rises significantly, and the frequency of fast-evolving faults gradually increases. Transformer faults can evolve rapidly in a short time, thereby causing damage to power equipment and even endangering the personal safety of operation and maintenance personnel during the fault troubleshooting process.

[0045] However, in the traditional technology, the monitoring means of existing transformer monitoring devices are single, unable to comprehensively cover various operation state information of the transformer, unable to effectively integrate and analyze all operation data of the transformer, difficult to provide a comprehensive, fast and convenient evaluation and fault diagnosis for the operation state of the transformer, and most of the monitoring devices used in the traditional technology are wired connections, and there are problems such as complex wiring, limited use range and flexibility in actual applications. Existing monitoring devices are difficult to directly export and integrate the original data from the original on-line monitoring devices, unable to effectively integrate and analyze all operation data of the transformer, thus difficult to provide a comprehensive, fast and convenient evaluation and fault diagnosis for the operation state of the transformer, and the comprehensiveness and reliability of the monitoring results are low, resulting in damage to power equipment.

[0046] Embodiments of the present application provide a transformer monitoring device. Please refer to Figure 1 and Figure 2, including: a signal acquisition module 10, a signal processing module 20, and a judgment module 30. The signal acquisition module 10 is used to acquire the real-time signals of the target transformer, where the real-time signals include at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high frequency partial discharge signals, grounding electrical signals, mechanical vibration signals, and load electrical signals. The input end of the signal processing module 20 is electrically connected to the output end of the signal acquisition module 10. The signal processing module 20 is used to receive the real-time signals and process the real-time signals to generate processed real-time signals. The input end of the judgment module 30 is electrically connected to the output end of the signal processing module 20. The judgment module 30 is used to compare the size relationship between the processed real-time signals and the threshold data, judge whether the target transformer fails, and generate a judgment result.

[0047] Exemplarily, the signal processing module 20 may include but is not limited to performing data calculation and data cleaning on the real-time signals collected by the signal acquisition module 10. Data cleaning can preprocess the data, remove noise, correct errors, fill in missing values, etc., to improve the quality of the data. Data calculation can provide directional and accurate information and features for the judgment module 30, thereby improving the analysis efficiency, reducing errors and biases in the analysis results, and improving the accuracy of the analysis results.

[0048] Exemplarily, the judgment module 30 may adopt but is not limited to the method of carrying a model to complete functions such as threshold calculation, abnormal alarm, fault category identification, and intelligent identification of the target transformer, so as to generate a fault diagnosis result of the target transformer, and provide reasonable opinions and solutions for subsequent maintenance and operation.

[0049] It should be noted that the transformer monitoring device in the embodiment of the present application may further include an operation and maintenance tablet and a fault diagnosis software. The transformer monitoring device can display the abnormal data, spectrum data, fault type, and diagnosis result of the target transformer on the operation and maintenance tablet for viewing in the fault diagnosis software in the operation and maintenance tablet, thereby improving the intuitiveness and convenience of the monitoring result of the target transformer.

[0050] The transformer monitoring device provided by this application collects at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, ultra-high frequency partial discharge signal, grounding electrical signal, mechanical vibration signal, and load electrical signal of the target transformer through the signal acquisition module 10. Furthermore, the judgment module 30 can compare the collected signals with the threshold data to obtain the operating state of the target transformer, comprehensively monitor and analyze the operating state of the target transformer, so as to obtain a comprehensive monitoring result of the operating state of the target transformer, avoid the problem that the target transformer has a fault risk due to a single monitoring result, and improve the comprehensiveness and accuracy of the monitoring result of the target transformer. And through the signal processing module 20, the signals of the target transformer collected can be calculated and cleaned to obtain accurate data to provide a judgment basis for the judgment module 30, thereby improving the reliability of the judgment result.

[0051] In some embodiments, please refer to Figure 3 , the signal processing module 20 includes: a data cleaning module 201. The input end of the data cleaning module 201 is electrically connected to the output end of the signal acquisition module 10. The data cleaning module 201 is used to clean at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, ultra-high frequency partial discharge signal, and mechanical vibration signal by means of wavelet transform method.

[0052] Exemplarily, the ultrasonic partial discharge signal has the characteristics of non-stationarity and non-linearity and is easily affected by white noise and other interferences. The wavelet transform method can effectively remove these noises while retaining the characteristic information of the ultrasonic partial discharge signal. For example, by combining the improved wavelet threshold method with the complete ensemble empirical mode decomposition with adaptive noise, the signal-to-noise ratio of the signal can be significantly improved, thereby providing more accurate data for subsequent partial discharge pattern recognition and localization.

[0053] Exemplarily, the wavelet transform method can effectively remove white noise and periodic narrowband noise in the signal through multi-resolution analysis. For example, the denoising method based on the improved Protrugram and wavelet transform can identify the central frequency of the partial discharge signal in the frequency domain and remove redundant noise through adaptive threshold processing, so as to better retain the effective signal.

[0054] Exemplarily, the ultra-high frequency partial discharge signal usually has rapid frequency changes and complex time-frequency characteristics. The wavelet transform can provide good time-frequency localization ability and is suitable for the analysis of such non-stationary signals. By selecting an appropriate mother wavelet (such as the Complex Morlet wavelet), time-frequency analysis can be performed on the ultra-high frequency signal to extract the energy distribution characteristics of the signal, thereby realizing the identification of different defect types.

[0055] Exemplarily, mechanical vibration signals are interfered by background noise. The wavelet transform method can effectively extract fault features in vibration signals. By selecting appropriate mother wavelets and decomposition levels, the noise in the signals can be removed, making the fault features more prominent, so as to provide accurate data support for the judgment module 30.

[0056] In the transformer monitoring device according to the embodiment of the present application, by cleaning at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, ultra-high frequency partial discharge signal, and mechanical vibration signal through the wavelet transform method, the noise can be effectively removed and the characteristic information of the signal can be retained, thereby providing a reliable data basis for subsequent analysis and diagnosis, and further improving the accuracy and objectivity of the judgment result obtained by the judgment module 30.

[0057] In some embodiments, please refer to Figure 3 , the signal processing module 20 further includes: a first data processing module 202. The input end of the first data processing module 202 is electrically connected to the output end of the data cleaning module 201, and the output end of the first data processing module 202 is electrically connected to the input end of the judgment module 30. The first data processing module 202 is used to process at least one of the ultrasonic partial discharge signal, high-frequency partial discharge signal, and ultra-high frequency partial discharge signal after cleaning through the PSO-SVM hybrid optimization algorithm.

[0058] Exemplarily, the PSO-SVM hybrid optimization algorithm optimizes the parameters of the SVM through the PSO algorithm, such as the penalty parameter C and the kernel function parameter γ, so as to improve the classification accuracy and generalization ability of the model.

[0059] In the transformer monitoring device according to the embodiment of the present application, by processing the ultrasonic, high-frequency, and ultra-high frequency partial discharge signals through the PSO-SVM hybrid optimization algorithm, the accuracy of signal classification and the reliability of fault diagnosis can be effectively improved. The PSO algorithm can optimize the key parameters of the SVM, making the SVM model better adapt to different types of partial discharge signals, thereby improving the classification performance, and further improving the accuracy and objectivity of the judgment result obtained by the judgment module 30.

[0060] In some embodiments, please refer to Figure 3 , the signal processing module 20 further includes: a second data processing module 203. The input end of the second data processing module 203 is electrically connected to the output end of the data cleaning module 201, and the output end of the second data processing module 203 is electrically connected to the input end of the judgment module 30. The second data processing module 203 is used to process the mechanical vibration signal after cleaning through the SVM optimization algorithm.

[0061] Exemplarily, the SVM optimization algorithm can be used to process the cleaned mechanical vibration signals. The preprocessed vibration signals can be input into the trained SVM model for classification.

[0062] It should be noted that the SVM optimization algorithm is suitable for small-scale data sets or cases with a small parameter space and is easy to implement. Therefore, the mechanical vibration signals can be processed using the SVM optimization algorithm. The PSO-SVM hybrid optimization algorithm is suitable for large-scale data sets or cases with a large parameter space, has strong global search ability and high computational efficiency. Therefore, ultrasonic, high-frequency, and UHF partial discharge signals can be processed by the PSO-SVM hybrid optimization algorithm.

[0063] In the transformer monitoring device according to the embodiment of the present application, the SVM optimization algorithm is used to process the cleaned mechanical vibration signals, which can effectively classify the mechanical vibration signals. And through feature extraction and dimensionality reduction, the SVM can better capture the key information in the vibration signals, thereby improving the accuracy and objectivity of the judgment results obtained by the judgment module 30.

[0064] In some embodiments, please refer to Figure 4 The transformer monitoring device further includes: a data storage module 40. The input end of the data storage module 40 is electrically connected to the output end of the signal processing module 20, and the input end of the data storage module 40 is also electrically connected to the output end of the judgment module 30. The data storage module 40 is used to receive and store the processed real-time signals and judgment results.

[0065] Exemplarily, the data storage module 40 may include but is not limited to a database, such as a MySQL database. The data storage module 40 can store the processed real-time signals and judgment results, can centrally store the scattered data, and can support functions such as data mining, analysis, and report generation through the stored historical data.

[0066] It should be noted that the data storage module 40 can also store the historical detection data and historical spectrograms of the target transformer, so as to retrieve and display according to the time stamp in the case of monitoring the target transformer, and analyze the target transformer based on the historical detection data and detection results.

[0067] In the transformer monitoring device according to the embodiment of the present application, by receiving and storing the processed real-time signals and judgment results through the data storage module 40, the scattered data can be centrally stored, and the target transformer can be analyzed based on the historical detection data and detection results, thereby improving the applicability of the target transformer monitoring device.

[0068] In some embodiments, please refer to Figure 5, the transformer monitoring device further includes: a communication module 50. The input end of the communication module 50 is communicatively connected to the output end of the sensor connected to the target transformer, and the output end of the communication module 50 is communicatively connected to the input end of the signal acquisition module 10. The communication module 50 is configured to send the real-time signal output by the sensor connected to the target transformer to the signal acquisition module 10.

[0069] Exemplarily, the sensors connected to the target transformer may include but are not limited to partial discharge sensors, vibration sensors, core grounding current sensors, load voltage sensors, and load current sensors. The ultrasonic partial discharge signal, high-frequency partial discharge signal, and ultra-high frequency partial discharge signal of the target transformer are collected by the partial discharge sensor, the mechanical vibration signal of the target transformer is collected by the vibration sensor, and the load electrical signal of the target transformer is collected by the load voltage sensor and the load current sensor.

[0070] Exemplarily, the communication module 50 has a data interaction function. The communication module 50 may adopt but is not limited to forms such as Bluetooth, Wapi (Wireless LAN Authentication and Privacy Infrastructure), and NFC (Near Field Communication) to communicate with the sensors connected to the target transformer, so as to support the switching between multiple communication methods between the sensors and the transformer monitoring device according to the distance, and realize the communication between the sensors and the transformer monitoring device within 20 cm to 100 m. Among them, Bluetooth supports point-to-point communication between the transformer monitoring device and the sensor, Wapi supports long-distance connection within the station, and NFC is used to confirm the sensor tag to complete fast pairing. Among them, in the case where the real-time signal is a load electrical signal, a voltage sensor is used to receive voltage from the power distribution cabinet, a current sensor is used to receive current from the bus, and then the transformer monitoring device calculates the load information. The voltage sensor and the current sensor both directly use Wapi communication, so long-distance data transmission can be realized.

[0071] It should be noted that the transformer monitoring device provided in the embodiments of the present application can also communicate with other on-line monitoring devices of the transformer in the form of a network cable through IEC61850 (Communication Networks and Systems for Power Utility Automation), and convert the access communication protocol into the GOOSE protocol (Generic Object Oriented Substation Event) and the SV protocol (Sampled Values Protocol), so as to complete the internal data transmission.

[0072] It should be noted that the transformer monitoring device provided in the embodiments of the present application can also include the logical device and logical node modeling of oil chromatography, vibration equipment, and acoustic fingerprint equipment, and create virtual terminal configurations for each device.

[0073] In the transformer monitoring device in the embodiments of the present application, by setting the communication module 50, the transformer monitoring device can obtain the real-time signal of the target transformer in a timely manner, and there is no need to wire the target transformer, which improves the convenience and practicality of using the transformer monitoring device. In addition, through the communication module, other detection devices of the transformer monitoring device can be communicatively connected to obtain more comprehensive and comprehensive data, improving the reliability and practicality of the monitoring of the transformer monitoring device.

[0074] The embodiments of the present application also provide a transformer monitoring method. Please refer to Figure 6 , including:

[0075] S11: Collect the real-time signal of the target transformer, where the real-time signal includes at least one of an ultrasonic partial discharge signal, a high-frequency partial discharge signal, a very high-frequency partial discharge signal, a grounding electrical signal, a mechanical vibration signal, and a load electrical signal.

[0076] Exemplarily, but not limited to, the ultrasonic partial discharge signal, high-frequency partial discharge signal, and very high-frequency partial discharge signal of the target transformer can be obtained through a partial discharge sensor, the mechanical vibration signal of the target transformer can be obtained through a vibration sensor, and the load electrical signal of the target transformer can be obtained through a load voltage sensor and a load current sensor.

[0077] S12: Receive the real-time signal and process the real-time signal to generate a processed real-time signal.

[0078] Exemplarily, but not limited to, at least one of a wavelet transform method, a PSO-SVM hybrid optimization algorithm, and an SVM optimization algorithm can be used to process the real-time signal.

[0079] S13: Compare the processed real-time signal with the threshold data to determine whether the target transformer has a fault and generate a determination result.

[0080] In the transformer monitoring method according to the embodiments of the present application, by collecting at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high frequency partial discharge signals, grounding electrical signals, mechanical vibration signals, and load electrical signals of the target transformer, the collected signals can then be compared with the threshold data to obtain the operating state of the target transformer, comprehensively monitor and analyze the operating state of the target transformer to obtain a comprehensive monitoring result of the operating state of the target transformer, avoid the problem that the target transformer has a fault risk due to a single monitoring result, and improve the comprehensiveness and accuracy of the monitoring result of the target transformer. The signals of the target transformer collected can be calculated and cleaned to obtain accurate data, which can improve the reliability of the determination result.

[0081] Each step in the above transformer monitoring method can be implemented in whole or in part by software, hardware, and their combination. The above steps can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above respective modules.

[0082] Exemplarily, Figure 7 FIG. is a schematic structural diagram of a computer device provided by an embodiment of the present application. In the third aspect of the embodiments of the present application, a computer device is provided. The computer device can be a server, and its internal structural diagram can be as Figure 4 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the operation data of the power module. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a transformer monitoring method.

[0083] Exemplarily, Figure 8Schematic structural diagram of a computer-readable storage medium provided by an embodiment of the present application. The computer device may be a terminal, and its internal structural diagram may be as shown in Figure 8 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a transformer monitoring method.

[0084] In the fifth aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, it implements the steps of a transformer monitoring method as described in any one of the second aspects above.

[0085] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0086] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0087] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features of the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as falling within the scope described in this specification.

[0088] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the scope of the patented application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A transformer monitoring device, characterized in that: include: A signal acquisition module, used for acquiring real-time signals of a target transformer, wherein the real-time signals include at least one of ultrasonic partial discharge signals, high-frequency partial discharge signals, ultra-high-frequency partial discharge signals, grounding electrical signals, mechanical vibration signals and load electrical signals; A signal processing module, wherein an input end of the signal processing module is electrically connected to an output end of the signal acquisition module, and the signal processing module is used to receive the real-time signal and process the real-time signal to generate the processed real-time signal; A judgment module, wherein the input end of the judgment module is electrically connected to the output end of the signal processing module, and the judgment module is used to compare the size relationship between the processed real-time signal and the threshold data, judge whether the target transformer has a fault, and generate a judgment result.

2. The transformer monitoring device according to claim 1, characterized in that: The signal processing module comprises: A data cleaning module, wherein the input end of the data cleaning module is electrically connected to the output end of the signal acquisition module, and the data cleaning module is used to clean at least one of the ultrasonic partial discharge signal, the high-frequency partial discharge signal, the ultra-high frequency partial discharge signal and the mechanical vibration signal by a wavelet transformation method.

3. The transformer monitoring device according to claim 2, characterized in that: The signal processing module also includes: A first data processing module, wherein the input end of the first data processing module is electrically connected to the output end of the data cleaning module, the output end of the first data processing module is electrically connected to the input end of the judgment module, and the first data processing module is used to process at least one of the ultrasonic partial discharge signal, the high-frequency partial discharge signal, and the ultra-high frequency partial discharge signal after cleaning through a PSO-SVM hybrid optimization algorithm.

4. The transformer monitoring device according to claim 2, characterized in that: The signal processing module also includes: A second data processing module, wherein the input end of the second data processing module is electrically connected to the output end of the data cleaning module, the output end of the second data processing module is electrically connected to the input end of the judgment module, and the second data processing module is used to process the mechanical vibration signal after cleaning through an SVM optimization algorithm.

5. The transformer monitoring device according to claim 1, characterized in that: Also includes: A data storage module, wherein the input end of the data storage module is electrically connected to the output end of the signal processing module, and the input end of the data storage module is electrically connected to the output end of the judgment module, and the data storage module is used to receive and store the processed real-time signal and the judgment result.

6. The transformer monitoring device according to claim 1, characterized in that: Also includes: A communication module, wherein the input end of the communication module is communicatively connected to the output end of the sensor connected to the target transformer, the output end of the communication module is communicatively connected to the input end of the signal acquisition module, and the communication module is used to send a real-time signal output by the sensor connected to the target transformer to the signal acquisition module.

7. A transformer monitoring method, characterized in that: include: Collecting a real-time signal of a target transformer, wherein the real-time signal includes at least one of an ultrasonic partial discharge signal, a high-frequency partial discharge signal, an ultra-high-frequency partial discharge signal, a grounding electrical signal, a mechanical vibration signal, and a load electrical signal; Receiving the real-time signal, and processing the real-time signal to generate the processed real-time signal; The processed real-time signal is compared with the threshold data to determine whether the target transformer has a fault, and a determination result is generated.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the transformer monitoring method according to any one of claim 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the transformer monitoring method according to any one of claim 7 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the transformer monitoring method according to any one of claim 7 are implemented.

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