Sensor fault detection methods, devices, computer equipment and software products

Abstract

This application relates to a sensor fault detection method, apparatus, computer equipment, computer-readable storage medium, and computer program product. The method includes: acquiring a transformer defect simulation device, a transformer bushing defect sample, and real-time humidity and temperature of the current environment; calculating the sample amplitude of the sensor under test under the current environment; connecting the transformer defect simulation device to the transformer bushing defect sample, and, under the condition that a discharge signal from a standard calibration pulse is injected at the defect location of the transformer bushing defect sample, acquiring the measured amplitude detected by the sensor under test at each preset angle position; calculating the average amplitude of the sensor under test based on a preset number of angles; and determining that the sensor under test is faulty if the difference between the average amplitude and the sample amplitude exceeds a preset level. This method can improve the accuracy of sensor fault detection results.

Description

Technical Field

[0001] This application relates to the field of partial discharge verification technology, and in particular to a sensor fault detection method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] Transformer bushings are crucial components of transformers. Defects within the bushings can easily lead to partial discharges during transformer operation, potentially causing unplanned shutdowns, fires, and explosions. Ultra-high frequency (UHF) detection technology, due to its high sensitivity and strong anti-interference capabilities, has been widely used for online monitoring of partial discharges in transformer bushings. However, over long-term operation, the performance of UHF sensors degrades due to aging, corrosion, and physical damage, resulting in a decrease in sensitivity.

[0003] In related technologies, existing sensor calibration methods, such as offline calibration or laboratory verification, require disassembling the sensor from the equipment, which is cumbersome and costly. More importantly, these methods cannot simulate the real working conditions of the sensor in complex field environments. Some field verification methods lack consideration for environmental factors (such as temperature and humidity), leading to deviations between calibration results and actual conditions. This results in an inaccurate assessment of the sensor's true performance and ultimately, less precise fault detection results. Summary of the Invention

[0004] Therefore, it is necessary to provide a sensor fault detection method, device, computer equipment, computer-readable storage medium, and computer program product that can improve the accuracy of sensor fault diagnosis in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a sensor fault detection method, including:

[0006] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0007] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0008] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0009] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0010] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0011] In one embodiment, the formula for calculating the sample amplitude is:

[0012] ;

[0013] Where U is the sample amplitude and H is the preset height of the sensor under test. As environmental factors, Where is the absolute dielectric constant, Q is the injected equivalent charge, r is the propagation distance of the verification signal, and α is the attenuation coefficient; wherein, the environmental factor is calculated from the real-time humidity and the real-time temperature.

[0014] In one embodiment, the attenuation coefficient is calculated using the following formula:

[0015] ;

[0016] Where tanδ is the dielectric loss, c is the speed of light in vacuum, f is the frequency component of the standard calibration pulse, and ε is the relative dielectric constant.

[0017] In one embodiment, the formula for calculating the environmental factors is:

[0018] ;

[0019] Where p is the temperature index, q is the humidity index, and RH N To obtain the real-time humidity, T K The measured real-time temperature is RH0, where RH0 is the relative humidity and T0 is the relative temperature.

[0020] In one embodiment, the preset angle includes 0 degrees, 90 degrees, 180 degrees, and 270 degrees.

[0021] In one embodiment, the method further includes:

[0022] High-resistance conductive paint was sprayed onto the inner surface of the lower porcelain bushing of the defective transformer bushing sample.

[0023] Secondly, this application also provides a sensor fault detection device, comprising:

[0024] The acquisition module is used to acquire real-time humidity and temperature of the transformer defect simulation device, transformer bushing defect sample, and the current environment.

[0025] The calculation module is used to calculate the sample amplitude of the sensor under test in the current environment based on the real-time humidity and the real-time temperature.

[0026] The acquisition module is also used to connect the transformer defect simulation device to the transformer bushing defect sample, and when there is a discharge signal injected by a standard calibration pulse at the defect of the transformer bushing defect sample, acquire the measured amplitude value detected by the sensor under test at each preset angle position.

[0027] The calculation module is also used to perform a weighted average of the measured amplitude based on the number of preset angles to calculate the average amplitude of the sensor under test.

[0028] The determination module is used to determine that the sensor under test is faulty when the difference between the average amplitude and the sample amplitude is greater than a preset level.

[0029] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0030] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0031] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0032] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0033] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0034] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0035] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0036] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0037] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0038] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0039] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0040] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0041] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0042] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0043] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0044] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0045] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0046] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0047] The aforementioned sensor fault detection method, apparatus, computer equipment, computer-readable storage medium, and computer program product first acquire real-time humidity and temperature data from a transformer defect simulation device, a transformer bushing defect sample, and the current environment. Based on the real-time humidity and temperature, the sample amplitude of the sensor under test in the current environment is calculated. The transformer defect simulation device is connected to the transformer bushing defect sample. With a discharge signal from a standard calibration pulse injected at the defect location of the transformer bushing defect sample, the measured amplitude detected by the sensor under test at each preset angle is acquired. Based on the number of preset angles, a weighted average of the measured amplitudes is calculated to obtain the average amplitude of the sensor under test. If the difference between the average amplitude and the sample amplitude exceeds a preset level, a fault is determined in the sensor under test. Thus, by introducing environmental factors and considering the influence of temperature and humidity on sensor performance, and by calculating environmental factors and correcting the sensor's sample amplitude, the performance of the sensor in actual operating environments can be more accurately evaluated, avoiding calibration deviations caused by environmental changes and improving the accuracy of sensor fault detection. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is an application environment diagram of a sensor fault detection method in one embodiment;

[0050] Figure 2 This is a flowchart illustrating a sensor fault detection method in one embodiment;

[0051] Figure 3 This is a schematic diagram showing the connection between the transformer defect simulation device and the transformer bushing defect sample structure in one embodiment;

[0052] Figure 4 This is a structural block diagram of a sensor fault detection device in one embodiment;

[0053] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0056] The sensor fault detection method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located on the cloud or other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0057] In one exemplary embodiment, such as Figure 2 As shown, a sensor fault detection method is provided, which can be applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps 202 to 210. Wherein:

[0058] Step 202: Obtain the real-time humidity and temperature of the transformer defect simulation device, the transformer bushing defect sample, and the current environment.

[0059] For example, a transformer defect simulation device and a transformer bushing defect sample are obtained, and a temperature and humidity sensor is placed on the outer wall of the transformer bushing defect sample to collect the real-time humidity and real-time temperature of the current environment.

[0060] The transformer defect simulation device includes a sensor under test 301, an oil tank 302, and a discharge detector 303. The specific connection structure between the transformer defect simulation device and the transformer bushing defect sample 304 is as follows: Figure 3As shown.

[0061] The sensor under test is an ultra-high frequency sensor, or other sensors with the same function. The discharge detector is an ultra-high frequency local discharge detector, or other discharge detectors with the same function. This application does not limit the specific type of detector.

[0062] Step 204: Calculate the sample amplitude of the sensor under test in the current environment based on real-time humidity and real-time temperature.

[0063] Optionally, based on the obtained real-time humidity and real-time temperature, the sample amplitude of the sensor under test in the current environment is calculated.

[0064] Step 206: Connect the transformer defect simulation device to the transformer bushing defect sample. When there is a discharge signal injected by the standard calibration pulse at the defect of the transformer bushing defect sample, obtain the measured amplitude value detected by the sensor under test at each preset angle position.

[0065] For example, a sensor to be tested is installed at the connection gap between the bushing flange and the tank cover plate of the defective sample of the transformer bushing. A standard calibration pulse generator is used to inject a discharge signal at the defect of the defective sample of the transformer bushing. The partial discharge signal data received by the sensor to be tested is acquired at each preset angle position to determine the measured amplitude.

[0066] The discharge signal can be an amplitude equivalent to 20pC of charge, or it can be a charge of other magnitudes. It can be adaptively adjusted according to the user's needs, and this application embodiment does not limit it.

[0067] Step 208: Based on the preset number of angles, perform a weighted average of the measured amplitudes to calculate the average amplitude of the sensor under test.

[0068] Optionally, a weighted average is performed based on the number of preset angles and each measured amplitude to obtain the average amplitude of the sensor under test.

[0069] Step 210: If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0070] For example, the average amplitude of the sensor under test is compared with the sample amplitude. If the difference between the two is greater than a preset level, it is determined that the sensor under test is faulty.

[0071] In one embodiment, when the average amplitude of the sensor under test is less than the sample amplitude, it is determined that the sensor under test may be faulty and further testing is required.

[0072] In the aforementioned sensor fault detection method, real-time humidity and temperature of the transformer defect simulation device, transformer bushing defect sample, and the current environment are acquired. Based on the real-time humidity and temperature, the sample amplitude of the sensor under test in the current environment is calculated. The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of a standard calibration pulse is injected at the defect location of the transformer bushing defect sample, the measured amplitude detected by the sensor under test at each preset angle is acquired. Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test. If the difference between the average amplitude and the sample amplitude is greater than a preset level, the sensor under test is determined to be faulty. Thus, by introducing environmental factors and considering the influence of temperature and humidity on sensor performance, and by calculating environmental factors and correcting the sensor's sample amplitude, the performance of the sensor in the actual operating environment can be more accurately evaluated, avoiding calibration deviations caused by environmental changes and improving the accuracy of sensor fault detection.

[0073] In an exemplary embodiment, the formula for calculating the sample amplitude is as shown in (1):

[0074] (1)

[0075] Where U is the sample amplitude and H is the preset height of the sensor under test. As environmental factors, denoted as the absolute dielectric constant, Q as the injected equivalent charge, r as the propagation distance of the verification signal, and α as the attenuation coefficient; the environmental factors are calculated from real-time humidity and real-time temperature.

[0076] The preset height of the sensor under test is usually the effective height of the sensor (e.g., 8.0 mm), but it can also be other heights. This application embodiment does not limit this.

[0077] In the above embodiments, by calculating the sample amplitude and comparing it with the measured amplitude, changes in sensor performance can be detected in a timely manner. If the measured amplitude is lower than the sample amplitude, it indicates that the sensor's sensitivity may have decreased, indicating a performance failure. This early warning mechanism helps to promptly identify and address potential sensor problems, avoiding misjudgments or missed judgments due to sensor malfunctions, thereby improving the reliability of the monitoring system.

[0078] In an exemplary embodiment, the attenuation coefficient is calculated using the formula (2):

[0079] (2)

[0080] Where tanδ is the dielectric loss, c is the speed of light in vacuum, f is the frequency component of the standard calibration pulse, and ε is the relative dielectric constant.

[0081] In the above embodiments, by accurately calculating the attenuation coefficient, the signal loss during propagation can be assessed more accurately, thereby improving the reliability of the monitoring system.

[0082] In an exemplary embodiment, the formula for calculating environmental factors is shown in formula (3):

[0083] (3)

[0084] Where p is the temperature index, typically -0.3, q is the humidity index, typically -0.2, and RH N To obtain the real-time humidity, T K The measured real-time temperature is RH0, which is the relative humidity, typically 30%, and T0, which is the relative temperature, typically 20°C.

[0085] In the above embodiments, traditional verification methods often neglect the impact of environmental factors on sensor performance, leading to deviations between the verification results and the actual situation. This application reduces such deviations and lowers the possibility of misjudgment by calculating and correcting environmental factors.

[0086] In one exemplary embodiment, the preset angles include 0 degrees, 90 degrees, 180 degrees, and 270 degrees.

[0087] In practice, a sensor to be tested is installed at the connection gap between the bushing flange and the top cover of the oil tank of the defective bushing sample. A standard calibration pulse generator is used to inject a discharge signal at the defect of the defective bushing sample. The partial discharge signal data received by the sensor to be tested are acquired at positions of 0 degrees, 90 degrees, 180 degrees and 270 degrees respectively, and the measured amplitude is determined.

[0088] In the above embodiments, the propagation characteristics of partial discharge signals may be different in different directions. By measuring from multiple angles, it can be ensured that the sensor can accurately detect the signal in all directions, thereby more comprehensively evaluating the performance of the sensor.

[0089] In one exemplary embodiment, the sensor fault detection method further includes: spraying a high-resistivity conductive paint onto the inner surface of the lower ceramic bushing of a transformer bushing defect sample.

[0090] In practice, before injecting a discharge signal at the defect location of the transformer bushing defect sample using a standard calibration pulse generator, a high-resistance conductive paint is sprayed onto the inner surface of the lower porcelain bushing of the transformer bushing defect sample.

[0091] In the above embodiments, an anti-conductive paint is sprayed onto the inner surface of the lower porcelain bushing of the transformer bushing to form a surface discharge channel. The high-impedance conductive paint has good coating adhesion and can firmly adhere to the inner surface of the transformer bushing. This not only improves the durability of the coating but also ensures the stability of the conductive layer, avoiding detection errors caused by coating peeling.

[0092] To illustrate the sensor fault detection method in this application in detail, an embodiment is described below. For example, this application describes a sensor fault detection method in a specific scenario.

[0093] First, a transformer defect simulation device and a transformer bushing defect sample are obtained. A temperature and humidity sensor is placed on the outer wall of the transformer bushing defect sample to collect the real-time humidity and temperature of the current environment.

[0094] Based on the obtained real-time humidity and real-time temperature, calculate the sample amplitude of the sensor under test in the current environment.

[0095] A sensor to be tested is installed at the connection gap between the bushing flange and the tank cover plate of the defective transformer bushing sample. A standard calibration pulse generator is used to inject a discharge signal at the defect of the defective transformer bushing sample. The partial discharge signal data received by the sensor to be tested is acquired at each preset angle position to determine the measured amplitude.

[0096] Based on the preset number of angles and each measured amplitude, a weighted average is calculated to obtain the average amplitude of the sensor under test. The average amplitude of the sensor under test is compared with the sample amplitude. If the difference between the two is greater than a preset level, the sensor under test is determined to be faulty.

[0097] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0098] Based on the same inventive concept, this application also provides a sensor fault detection device for implementing the sensor fault detection method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more sensor fault detection device embodiments provided below can be found in the limitations of the sensor fault detection method described above, and will not be repeated here.

[0099] In one exemplary embodiment, such as Figure 4 As shown, a sensor fault detection device is provided, comprising: an acquisition module 401, a calculation module 402, and a determination module 403, wherein:

[0100] The acquisition module is used to acquire real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0101] The calculation module is used to calculate the sample amplitude of the sensor under test in the current environment based on the real-time humidity and the real-time temperature.

[0102] The acquisition module is also used to connect the transformer defect simulation device to the transformer bushing defect sample, and when there is a discharge signal injected by a standard calibration pulse at the defect of the transformer bushing defect sample, acquire the measured amplitude value detected by the sensor under test at each preset angle position.

[0103] The calculation module is also used to perform a weighted average of the measured amplitude based on the number of preset angles to calculate the average amplitude of the sensor under test.

[0104] The determination module is used to determine that the sensor under test is faulty when the difference between the average amplitude and the sample amplitude is greater than a preset level.

[0105] In one exemplary embodiment, the above-described calculation module is further configured to calculate the sample amplitude:

[0106] ;

[0107] Where U is the sample amplitude and H is the preset height of the sensor under test. As environmental factors, Where is the absolute dielectric constant, Q is the injected equivalent charge, r is the propagation distance of the verification signal, and α is the attenuation coefficient; wherein, the environmental factor is calculated from the real-time humidity and the real-time temperature.

[0108] In one exemplary embodiment, the above-described calculation module is further configured to calculate the attenuation coefficient:

[0109] ;

[0110] Where tanδ is the dielectric loss, c is the speed of light in vacuum, f is the frequency component of the standard calibration pulse, and ε is the relative dielectric constant.

[0111] In one exemplary embodiment, the above-described calculation module is further configured to calculate environmental factors:

[0112] ;

[0113] Where p is the temperature index, q is the humidity index, and RH N To obtain the real-time humidity, T K The measured real-time temperature is RH0, where RH0 is the relative humidity and T0 is the relative temperature.

[0114] In one exemplary embodiment, the preset angles include 0 degrees, 90 degrees, 180 degrees, and 270 degrees.

[0115] In one exemplary embodiment, the sensor fault detection device further includes: spraying a high-resistance conductive paint onto the inner surface of the lower ceramic bushing of the transformer bushing defect sample.

[0116] Each module in the aforementioned sensor fault detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0117] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output interfaces (I / O), a communication interface, a display unit, and input devices. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface, display unit, and input devices are also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores amplitude data acquired by the sensor. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a sensor fault detection method.

[0118] The display unit of this computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of this computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad set on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0119] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0120] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0121] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0122] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0123] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0124] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0125] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0126] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0127] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0128] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0129] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0130] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0131] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0132] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0133] The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment.

[0134] Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment;

[0135] The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained.

[0136] Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test.

[0137] If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

[0138] 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 used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this 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), magnetic 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 take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0141] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A sensor fault detection method, characterized in that, The method includes: The system acquires real-time humidity and temperature data from the transformer defect simulation device, transformer bushing defect samples, and the current environment. Based on the real-time humidity and the real-time temperature, calculate the sample amplitude of the sensor under test in the current environment; The formula for calculating the sample amplitude is as follows: ； Where U is the sample amplitude and H is the preset height of the sensor under test. As environmental factors, denoted as the absolute dielectric constant, Q as the injected equivalent charge, r as the propagation distance of the verification signal, and α as the attenuation coefficient. The formula for calculating the attenuation coefficient is: ； Where tanδ is the dielectric loss, c is the speed of light in vacuum, f is the frequency component of the standard calibration pulse, and ε is the relative dielectric constant. The formula for calculating the environmental factors is as follows: ； Where p is the temperature index, q is the humidity index, and RH N To obtain the real-time humidity, T K The measured real-time temperature is RH0, where RH0 is the relative humidity and T0 is the relative temperature. The transformer defect simulation device is connected to the transformer bushing defect sample. When a discharge signal of standard calibration pulse injection is present at the defect of the transformer bushing defect sample, the measured amplitude value detected by the sensor under test at each preset angle is obtained. Based on the number of preset angles, the measured amplitudes are weighted and averaged to calculate the average amplitude of the sensor under test. If the difference between the average amplitude and the sample amplitude is greater than a preset level, it is determined that the sensor under test is faulty.

2. The method according to claim 1, characterized in that, The preset angles include 0 degrees, 90 degrees, 180 degrees, and 270 degrees.

3. The method according to claim 1, characterized in that, The method further includes: High-resistance conductive paint was sprayed onto the inner surface of the lower porcelain bushing of the defective transformer bushing sample.

4. A sensor fault detection device, characterized in that, The device includes: The acquisition module is used to acquire real-time humidity and temperature of the transformer defect simulation device, transformer bushing defect sample, and the current environment. The calculation module is used to calculate the sample amplitude of the sensor under test in the current environment based on the real-time humidity and the real-time temperature; wherein, the formula for calculating the sample amplitude is: Where U is the sample amplitude and H is the preset height of the sensor under test. As environmental factors, Let be the absolute dielectric constant, Q be the injected equivalent charge, r be the propagation distance of the verification signal, and α be the attenuation coefficient; the formula for calculating the attenuation coefficient is: Where tanδ is the dielectric loss, c is the speed of light in vacuum, f is the frequency component of the standard calibration pulse, and ε is the relative dielectric constant; the formula for calculating the environmental factor is: Where p is the temperature index, q is the humidity index, and RH is the relative humidity. N To obtain the real-time humidity, T K The measured real-time temperature is RH0, where RH0 is the relative humidity and T0 is the relative temperature. The acquisition module is also used to connect the transformer defect simulation device to the transformer bushing defect sample, and when there is a discharge signal injected by a standard calibration pulse at the defect of the transformer bushing defect sample, acquire the measured amplitude value detected by the sensor under test at each preset angle position. The calculation module is also used to perform a weighted average of the measured amplitude based on the number of preset angles to calculate the average amplitude of the sensor under test. The determination module is used to determine that the sensor under test is faulty when the difference between the average amplitude and the sample amplitude is greater than a preset level.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

7. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

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