Anti-interference protection method and system for lightning arrester detection device

Abstract

The invention discloses an anti-interference protection method and system for a lightning arrester detection device, and the method comprises the steps: obtaining a protection strategy table, a frequency spectrum heat map, multi-source environment data and multi-source detection data of the lightning arrester detection device, and enabling the protection strategy table to comprise a transient pulse protection strategy, a power frequency protection strategy and a high-frequency noise protection strategy; performing data fusion optimization on the multi-source detection data to obtain optimized data; performing strategy screening on the protection strategy table according to the frequency spectrum heat map, the multi-source environment data and the optimization data to obtain a target protection strategy; and performing anti-interference protection on the lightning arrester detection device according to the target protection strategy. According to the method, the anti-interference protection effect on the lightning arrester detection device can be effectively improved. The invention relates to the technical field of lightning arrester detection.

Description

Technical Field

[0001] This invention relates to the field of surge arrester testing technology, and in particular to an anti-interference protection method and system for surge arrester testing devices. Background Technology

[0002] Surge arrester testing devices are important equipment used to evaluate the performance and condition of surge arresters. In practical applications, because surge arrester testing devices are susceptible to interference, interference protection of surge arrester testing devices has become one of the concerns of relevant personnel.

[0003] Currently, the relevant technologies usually rely on electromagnetic shielding technology, which uses high shielding efficiency materials to universally shield the surge arrester testing device, thereby achieving anti-interference protection for the surge arrester testing device. However, the anti-interference protection effect of this method is not satisfactory.

[0004] Therefore, the problems with the relevant technologies still need to be solved and optimized. Summary of the Invention

[0005] The purpose of this invention is to at least partially solve one of the technical problems existing in the related art.

[0006] Therefore, one objective of this invention is to provide an anti-interference protection method and system for a surge arrester testing device, wherein the method can effectively improve the anti-interference protection effect of the surge arrester testing device.

[0007] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of this application include: In a first aspect, embodiments of this application provide an anti-interference protection method for a surge arrester detection device, including: The protection strategy table, spectrum heat map, and multi-source environmental data, as well as the multi-source detection data of the surge arrester detection device, are obtained. The protection strategy table includes transient pulse protection strategy, power frequency protection strategy, and high frequency noise protection strategy. The multi-source detection data is fused and optimized to obtain optimized data; Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, the protection strategy table is filtered to obtain the target protection strategy; According to the target protection strategy, the surge arrester detection device is protected against interference.

[0008] In addition, the method according to the above embodiments of this application may also have the following additional technical features: Furthermore, in one embodiment of this application, obtaining a spectral heatmap includes: Acquire full-band scanning signals; The full-band scanning signal is subjected to spectrum detection to obtain the target spectrum, which includes power frequency pulse information and electromagnetic pulse information; Based on the target spectrum, construct the spectrum heatmap.

[0009] Furthermore, in one embodiment of this application, the step of performing data fusion optimization on the multi-source detection data to obtain optimized data includes: Based on the multi-source detection data, leakage current data, ultrasonic data, and infrared thermal imaging data are obtained; The leakage current data, the ultrasonic data, and the infrared thermal image data are time-aligned to obtain aligned leakage current data, ultrasonic data, and infrared thermal image data; Evidence fusion is performed on the aligned leakage current data, ultrasonic data, and infrared thermographic data to obtain fused data; The fused data is then optimized to obtain the optimized data.

[0010] Furthermore, in one embodiment of this application, the step of fusing the aligned leakage current data, the ultrasonic data, and the infrared thermographic data to obtain fused data includes: Acquire a first basic probability set of the leakage current data, a second basic probability set of the ultrasonic data, and a third basic probability set of the infrared thermal image data; Based on the first basic probability set and the second basic probability set, factor analysis is performed on the third basic probability set to obtain the conflict factor; Based on the conflict factor, the first basic probability set, the second basic probability set, and the third basic probability set, the aligned leakage current data, the ultrasonic data, and the infrared thermal image data are fused to obtain the fused data.

[0011] Furthermore, in one embodiment of this application, the step of optimizing the fused data to obtain the optimized data includes: The fused data is input into a time series prediction network for prediction analysis to obtain time series prediction data. The optimized data is obtained by performing variational Kalman filtering on the time-series prediction data.

[0012] Furthermore, in one embodiment of this application, the step of filtering the protection strategy table based on the spectral heatmap, the multi-source environmental data, and the optimization data to obtain the target protection strategy includes: Based on the protection strategy table, obtain the protection strategy condition set, which includes environmental conditions, power frequency conditions, and pulse conditions. Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, the protection strategy condition set is determined to obtain strategy indication information. Based on the policy instruction information, the protection policy table is used to extract the policy to obtain the target protection policy.

[0013] Furthermore, in one embodiment of this application, the step of determining the protection strategy condition set based on the spectral heatmap, the multi-source environmental data, and the optimization data to obtain strategy indication information includes: Based on the multi-source environmental data, the environmental conditions are verified using a first condition, and the first condition verification result is obtained. Based on the power frequency pulse information in the spectrum heatmap and the optimized data, the power frequency condition is verified as a second condition to obtain the second condition verification result. If the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information and the optimized data meet the power frequency conditions, then strategy indication information indicating the high-frequency noise protection strategy and the power frequency protection strategy is generated; or, if the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information or the optimized data does not meet the power frequency conditions, then the pulse conditions are verified by a third condition based on the electromagnetic pulse information in the spectrum heatmap, and a third condition verification result is obtained. If the third condition verification result is that the electromagnetic pulse information satisfies the pulse condition, then strategy indication information is generated that indicates the high-frequency noise protection strategy and the transient pulse protection strategy.

[0014] Secondly, embodiments of this application provide an anti-interference protection system for a surge arrester testing device, comprising: The first processing unit is used to acquire a protection strategy table, a spectrum heat map, and multi-source environmental data, as well as multi-source detection data from a surge arrester detection device. The protection strategy table includes transient pulse protection strategy, power frequency protection strategy, and high-frequency noise protection strategy. The second processing unit is used to perform data fusion optimization on the multi-source detection data to obtain optimized data; The third processing unit is used to perform strategy filtering on the protection strategy table based on the spectrum heatmap, the multi-source environmental data and the optimization data to obtain the target protection strategy; The fourth processing unit is used to perform anti-interference protection on the surge arrester detection device according to the target protection strategy.

[0015] Thirdly, embodiments of this application also provide an electronic device, including: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor performs the method described above.

[0016] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a processor-executable program, which, when executed by the processor, is used to implement the above-described method.

[0017] The advantages and beneficial effects of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application: This application discloses an anti-interference protection method and system for a surge arrester testing device. The method acquires a protection strategy table, a spectrum heatmap, and multi-source environmental data, as well as multi-source detection data from the surge arrester testing device. The protection strategy table includes transient pulse protection strategies, power frequency protection strategies, and high-frequency noise protection strategies. The method performs data fusion optimization on the multi-source detection data to obtain optimized data. Based on the spectrum heatmap, the multi-source environmental data, and the optimized data, the method filters the protection strategy table to obtain a target protection strategy. Finally, the method performs anti-interference protection on the surge arrester testing device according to the target protection strategy. This method, based on the spectrum heatmap, multi-source environmental data, and optimized data, determines the target protection strategy from the protection strategy table, enabling targeted protection against interference threats to the surge arrester testing device and effectively improving the anti-interference protection effect. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following description is provided with accompanying drawings of the relevant technical solutions in the embodiments of this application or the prior art. It should be understood that the accompanying drawings described below are only for the purpose of clearly illustrating some embodiments of the technical solutions in this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 A schematic flowchart illustrating an anti-interference protection method for a surge arrester testing device provided in this application embodiment; Figure 2 A schematic diagram of the anti-interference protection system of a surge arrester testing device provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0021] 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 terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] Currently, relevant technologies typically rely on electromagnetic shielding, using high-shielding materials to provide general shielding for surge arrester testing devices, thereby achieving anti-interference protection. However, due to the complex operating environment of surge arrester testing devices and the diverse sources of interference affecting them, this method struggles to provide targeted anti-interference protection against different sources, resulting in unsatisfactory anti-interference effects. Furthermore, this method cannot effectively differentiate and process complex and varied interference sources, making it difficult to identify the interference threats posed to the surge arrester testing device, leading to low anti-interference protection effectiveness and ultimately unsatisfactory results.

[0023] It should be noted that the aforementioned related technologies are only used to assist in understanding the technical solutions of this application and do not mean that they belong to the publicly disclosed prior art.

[0024] In view of this, embodiments of this application provide an anti-interference protection method and system for a surge arrester testing device. The method optimizes multi-source detection data through data fusion, specifically by fusing evidence from multi-source detection data, thereby solving the problem that a single sensor is easily affected by environmental interference in traditional surge arrester testing. Then, through data optimization, specifically by performing time-series prediction and variational Kalman filtering on the fused data, it can achieve active prediction and dynamic filtering of interference modes, effectively solving the problem of poor stability of traditional filtering under non-Gaussian noise.

[0025] Furthermore, this method employs a multi-level protection strategy, specifically through multi-level condition verification using spectral heatmaps, multi-source environmental data, and optimized data, to determine the strategy indication information for the target protection strategy. It can combine the interference mode information obtained through proactive prediction to provide rapid response and targeted protection against interference threats to the surge arrester detection device in advance. Moreover, by combining multiple conditions for judgment, it can avoid the situation of false triggering by a single parameter, effectively improving the anti-interference protection effect and accuracy.

[0026] Reference Figure 1 In this embodiment of the application, an anti-interference protection method for a surge arrester detection device includes: Step 110: Obtain the protection strategy table, spectrum heat map, and multi-source environmental data, as well as the multi-source detection data of the surge arrester detection device; In this embodiment, the protection strategy table records transient pulse protection strategy, power frequency protection strategy, and high-frequency noise protection strategy. The transient pulse protection strategy can employ a transient voltage suppressor array to suppress transient voltages (such as electrostatic discharge), thereby achieving anti-interference protection against interference to the detection data collected by the surge arrester detection device. The power frequency protection strategy can first track the power grid frequency (50 / 60Hz ± 0.1Hz) using a phase-locked loop, and then adaptively adjust the notch filter parameters based on the tracked power grid frequency. The adjusted notch filter then eliminates power frequency interference. The system achieves anti-interference protection for the detection data collected by the surge arrester testing device; and the high-frequency noise protection strategy can be to shield high-frequency noise through a layered shielding cover to provide anti-interference protection for the surge arrester testing device. The layered shielding cover includes a first shielding cover, a second shielding cover, and a third shielding cover. The first shielding cover is used to isolate high-frequency interference signals of 1-3 GHz. The second shielding cover is activated in conjunction with the first shielding cover when noise greater than 40 dB is detected. The third shielding cover can be activated together with the first two shielding covers when an EMP event occurs in the surge arrester testing device.

[0027] It is understandable that a spectrum thermal map can be a spectrum diagram of radio frequency signals (such as electromagnetic wave signals) in the environment surrounding the surge arrester detection device; while multi-source environmental data can be a collection of different types of environmental data, which can be obtained by different types of sensors in the surge arrester detection device, such as temperature data collected by a temperature sensor, vibration data collected by a vibration sensor, and humidity data collected by a humidity sensor. Multi-source detection data can be leakage current data, ultrasonic data, and infrared thermal image data collected by the surge arrester detection device.

[0028] In some embodiments, obtaining a spectral heatmap includes: Acquire full-band scanning signals; The full-band scanning signal is subjected to spectrum detection to obtain the target spectrum, which includes power frequency pulse information and electromagnetic pulse information; Based on the target spectrum, construct the spectrum heatmap.

[0029] In this embodiment of the application, the environment around the surge arrester detection device can be scanned in the full frequency band by an SDR array to obtain a full frequency band scanning signal in the time domain; the spectrum detection can be based on the Fast Fourier Transform-Constant False Alarm Rate (FFT-CFAR) algorithm to identify abnormal spectrum of the full frequency band scanning signal, and the identified abnormal spectrum is recorded as the target spectrum, which includes power frequency harmonic information and electromagnetic pulse (EMP) information.

[0030] Understandably, after obtaining the target spectrum, a corresponding spectrum heatmap can be constructed based on heatmap technology, according to the power frequency pulse information and electromagnetic pulse information in the target spectrum.

[0031] Step 120: Perform data fusion optimization on the multi-source detection data to obtain optimized data; In this embodiment of the application, data fusion optimization can be achieved by fusing and optimizing signal data such as leakage current data, ultrasonic data and infrared thermal imaging data in multi-source detection data to obtain optimized signal data, which is denoted as optimized data.

[0032] In some embodiments, the step of performing data fusion optimization on the multi-source detection data to obtain optimized data includes: Based on the multi-source detection data, leakage current data, ultrasonic data, and infrared thermal imaging data are obtained; The leakage current data, the ultrasonic data, and the infrared thermal image data are time-aligned to obtain aligned leakage current data, ultrasonic data, and infrared thermal image data; In this embodiment of the application, when acquiring multi-source detection data, leakage current data, ultrasonic data, and infrared thermal image data with acquisition timestamps can be acquired; time alignment can be based on the acquisition timestamps and algorithms such as Dynamic Time Warping (DTW) can be used to align the leakage current data, ultrasonic data, and infrared thermal image data, thereby obtaining the timestamp-aligned leakage current data, ultrasonic data, and infrared thermal image data on the time axis.

[0033] Evidence fusion is performed on the aligned leakage current data, ultrasonic data, and infrared thermographic data to obtain fused data; Further, the evidence fusion of the aligned leakage current data, ultrasonic data, and infrared thermographic data to obtain fused data includes: Acquire a first basic probability set of the leakage current data, a second basic probability set of the ultrasonic data, and a third basic probability set of the infrared thermal image data; Based on the first basic probability set and the second basic probability set, factor analysis is performed on the third basic probability set to obtain the conflict factor; Based on the conflict factor, the first basic probability set, the second basic probability set, and the third basic probability set, the aligned leakage current data, the ultrasonic data, and the infrared thermal image data are fused to obtain the fused data.

[0034] In this embodiment, evidence fusion can be based on Dempster-Shafer evidence theory, determining a first fundamental probability set for leakage current data, a second fundamental probability set for ultrasonic data, and a third fundamental probability set for infrared thermographic data. Each fundamental probability set includes fundamental probability assignment functions for several events, where each event can be any one of all events supported by the leakage current data, ultrasonic data, or infrared thermographic data. Specifically, for the first fundamental probability set, the fundamental probability assignment function for any event supported by the leakage current data can be expressed as:

[0035] in, For leakage current data The basic probability assignment function for supported event A; For leakage current data The i-th data point in the dataset; For leakage current data The mean of all collected data points; For leakage current data Standard deviation of all collected data points; For leakage current data The total number of all collected data points.

[0036] It is understandable that the basic probability allocation functions for the remaining events in the first basic probability set, as well as the basic probability allocation functions in the second and third basic probability sets, are similar to those described above and can be easily deduced by analogy. Factor analysis can be based on all the basic probability allocation functions in the first, second, and third basic probability sets to calculate the conflict factor in the DS evidence theory; then, using the calculated conflict factor and all the basic probability allocation functions in each basic probability set, leakage current data, ultrasonic data, and infrared thermographic data from different sources are fused. Various specific fusion methods already exist, which will not be elaborated upon here.

[0037] The fused data is then optimized to obtain the optimized data.

[0038] Furthermore, the step of optimizing the fused data to obtain the optimized data includes: The fused data is input into a time series prediction network for prediction analysis to obtain time series prediction data. The optimized data is obtained by performing variational Kalman filtering on the time-series prediction data.

[0039] In this embodiment, data optimization can first involve inputting the data into a time-series prediction network, specifically a trained Long Short-Term Memory (LSTM) network. The trained LSTM network predicts future sequence data from the fused data, resulting in time-series prediction data output by the network. This time-series prediction data can include future sequence data from the fused data, and / or corresponding power frequency harmonic prediction sequence data and electromagnetic pulse prediction sequence data. Next, variational Kalman filtering is applied to the time-series prediction data. Specifically, the state estimate of the time-series prediction data is converged to a stable value through iteration, resulting in optimized data. This optimized data includes the stable value obtained after state estimation of the time-series prediction data, and the corresponding power frequency harmonic estimation data and / or electromagnetic pulse estimation data.

[0040] Step 130: Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, perform strategy filtering on the protection strategy table to obtain the target protection strategy; In this embodiment of the application, strategy selection can be based on spectrum heatmaps, multi-source environmental data and optimization data, to select several required protection strategies from transient pulse protection strategies, power frequency protection strategies and high frequency noise protection strategies in the protection strategy table, and the selected protection strategies are recorded as target protection strategies.

[0041] In some embodiments, the step of filtering the protection strategy table based on the spectral heatmap, the multi-source environmental data, and the optimization data to obtain a target protection strategy includes: Based on the protection strategy table, obtain the protection strategy condition set, which includes environmental conditions, power frequency conditions, and pulse conditions. In this application embodiment, the corresponding pulse conditions can be determined based on the transient pulse protection strategy in the protection strategy table, the corresponding power frequency conditions can be determined based on the power frequency protection strategy, and the environmental conditions can be determined based on the high frequency noise protection strategy and the preset environmental rules.

[0042] Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, the protection strategy condition set is determined to obtain strategy indication information. Further, the step of determining the protection strategy condition set based on the spectrum heatmap, the multi-source environmental data, and the optimization data to obtain strategy indication information includes: Based on the multi-source environmental data, the environmental conditions are verified using a first condition, and the first condition verification result is obtained. Based on the power frequency pulse information in the spectrum heatmap and the optimized data, the power frequency condition is verified as a second condition to obtain the second condition verification result. If the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information and the optimized data meet the power frequency conditions, then strategy indication information indicating the high-frequency noise protection strategy and the power frequency protection strategy is generated; or, if the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information or the optimized data does not meet the power frequency conditions, then the pulse conditions are verified by a third condition based on the electromagnetic pulse information in the spectrum heatmap, and a third condition verification result is obtained. If the third condition verification result is that the electromagnetic pulse information satisfies the pulse condition, then strategy indication information is generated that indicates the high-frequency noise protection strategy and the transient pulse protection strategy.

[0043] In this embodiment, the first condition verification can be to verify whether the multi-source environmental data meets environmental conditions. For example, it can be to verify whether the temperature data in the multi-source environmental data is greater than 85°C, or whether the humidity data in the multi-source environmental data is greater than 80%, thereby obtaining the first condition verification result. If the temperature data in the multi-source environmental data is less than or equal to 85°C, or the humidity data in the multi-source environmental data is less than or equal to 80%, a first condition verification result indicating that the multi-source environmental data does not meet the environmental conditions can be generated. At this time, strategy indication information indicating the activation of the first layer of shielding for high-frequency noise protection can be generated.

[0044] Understandably, the second condition verification can be used to verify whether the power frequency pulse information and the power frequency harmonic estimation data in the optimized data meet the power frequency conditions. For example, if the power frequency pulse information and the power frequency harmonic estimation data are greater than 30dBm, a second condition verification result can be generated indicating that the power frequency pulse information and the optimized data meet the power frequency conditions; while if the power frequency pulse information or the power frequency harmonic estimation data are not greater than 30dBm, a second condition verification result can be generated indicating that the power frequency pulse information or the optimized data does not meet the power frequency conditions.

[0045] Specifically, if the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information and the optimized data meet the power frequency conditions, then a strategy indication information is generated indicating that the high-frequency noise protection strategy should activate the first and second shielding layers, as well as the power frequency protection strategy. Alternatively, if the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information or the optimized data does not meet the power frequency conditions, then it is possible to verify whether the electromagnetic pulse information meets the pulse conditions, for example, to verify whether the electromagnetic pulse count in the electromagnetic pulse information is greater than 5 times / second, thereby obtaining the third condition verification result.

[0046] If the electromagnetic pulse count is greater than 5 times / second, a third condition verification result can be generated to indicate that the electromagnetic pulse information meets the pulse condition. At this time, policy indication information can be generated to enable all shielding covers for high-frequency noise protection and transient pulse protection. Alternatively, if the electromagnetic pulse count is less than or equal to 5 times / second, policy indication information can be generated to indicate that the first and second shielding covers for high-frequency noise protection and power frequency protection can be enabled.

[0047] It should be noted that the specific figures mentioned in the examples in this application are for ease of understanding only, and can be flexibly set in practical applications. For example, 30dBm in the power frequency condition can also be 40dBm or 45dBm; and 5 times / second in the pulse condition can also be 7 times / second, etc. This application does not impose any restrictions here.

[0048] Based on the policy instruction information, the protection policy table is used to extract the policy to obtain the target protection policy.

[0049] In this embodiment of the application, after obtaining the policy indication information, the corresponding protection policy can be extracted from the protection policy table based on the policy indication information, and the obtained target protection policy can be integrated.

[0050] Step 140: According to the target protection strategy, perform anti-interference protection on the surge arrester detection device.

[0051] In this embodiment of the application, anti-interference protection can be achieved by autonomously executing the target protection strategy through the surge arrester detection device after obtaining the target protection strategy, so as to achieve anti-interference protection against the interference source.

[0052] The following describes in detail, with reference to the accompanying drawings, an anti-interference protection system for a surge arrester testing device according to an embodiment of this application.

[0053] Reference Figure 2 The anti-interference protection system for a surge arrester testing device proposed in this application includes: The first processing unit 101 is used to acquire a protection strategy table, a spectrum heat map and multi-source environmental data, as well as multi-source detection data of the surge arrester detection device. The protection strategy table includes transient pulse protection strategy, power frequency protection strategy and high frequency noise protection strategy. The second processing unit 102 is used to perform data fusion optimization on the multi-source detection data to obtain optimized data; The third processing unit 103 is used to perform strategy filtering on the protection strategy table based on the spectrum heatmap, the multi-source environmental data and the optimization data to obtain the target protection strategy; The fourth processing unit 104 is used to perform anti-interference protection on the surge arrester detection device according to the target protection strategy.

[0054] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0055] Reference Figure 3 This application also provides an electronic device, including: At least one processor 201; At least one memory 202 is used to store at least one program; When the at least one program is executed by the at least one processor 201, the at least one processor 201 implements the method embodiment described above.

[0056] Similarly, it can be understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0057] This application also provides a computer-readable storage medium storing a program executable by a processor 201, which, when executed by the processor 201, is used to implement the above-described method embodiments.

[0058] Similarly, the content of the above method embodiments is applicable to the present computer-readable storage medium embodiments. The specific functions implemented by the present computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0059] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0060] Those skilled in the art will understand that all or part of the processes in 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. When the computer program is executed, it can include the processes of the embodiments of the above methods.

[0061] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0062] Furthermore, although this application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding this application. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional technology for an engineer. Therefore, those skilled in the art can implement the application set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of this application, which is determined by the full scope of the appended claims and their equivalents.

[0063] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0064] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0065] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0066] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0067] In the foregoing description of this specification, the references to terms such as "one embodiment," "another embodiment," or "some embodiments," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0068] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

[0069] The above is a detailed description of the preferred embodiments of this application, but this application is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. An anti-interference protection method for a surge arrester testing device, characterized in that, include: The protection strategy table, spectrum heat map, and multi-source environmental data, as well as the multi-source detection data of the surge arrester detection device, are obtained. The protection strategy table includes transient pulse protection strategy, power frequency protection strategy, and high frequency noise protection strategy. The multi-source detection data is fused and optimized to obtain optimized data; Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, the protection strategy table is filtered to obtain the target protection strategy; According to the target protection strategy, the surge arrester detection device is protected against interference.

2. The method according to claim 1, characterized in that, Obtain a spectral heatmap, including: Acquire full-band scanning signals; The full-band scanning signal is subjected to spectrum detection to obtain the target spectrum, which includes power frequency pulse information and electromagnetic pulse information; Based on the target spectrum, construct the spectrum heatmap.

3. The method according to claim 1, characterized in that, The process of fusing and optimizing the multi-source detection data to obtain optimized data includes: Based on the multi-source detection data, leakage current data, ultrasonic data, and infrared thermal imaging data are obtained; The leakage current data, the ultrasonic data, and the infrared thermal image data are time-aligned to obtain aligned leakage current data, ultrasonic data, and infrared thermal image data; Evidence fusion is performed on the aligned leakage current data, ultrasonic data, and infrared thermographic data to obtain fused data; The fused data is then optimized to obtain the optimized data.

4. The method according to claim 3, characterized in that, The process of fusing the aligned leakage current data, ultrasonic data, and infrared thermographic data to obtain fused data includes: Acquire a first basic probability set of the leakage current data, a second basic probability set of the ultrasonic data, and a third basic probability set of the infrared thermal image data; Based on the first basic probability set and the second basic probability set, factor analysis is performed on the third basic probability set to obtain the conflict factor; Based on the conflict factor, the first basic probability set, the second basic probability set, and the third basic probability set, the aligned leakage current data, the ultrasonic data, and the infrared thermal image data are fused to obtain the fused data.

5. The method according to claim 3, characterized in that, The step of optimizing the fused data to obtain the optimized data includes: The fused data is input into a time series prediction network for prediction analysis to obtain time series prediction data. The optimized data is obtained by performing variational Kalman filtering on the time-series prediction data.

6. The method according to any one of claims 1-5, characterized in that, The step of filtering the protection strategy table based on the spectrum heatmap, the multi-source environmental data, and the optimization data to obtain the target protection strategy includes: Based on the protection strategy table, obtain the protection strategy condition set, which includes environmental conditions, power frequency conditions, and pulse conditions. Based on the spectrum heatmap, the multi-source environmental data, and the optimization data, the protection strategy condition set is determined to obtain strategy indication information. Based on the policy instruction information, the protection policy table is used to extract the policy to obtain the target protection policy.

7. The method according to claim 6, characterized in that, The step of determining the protection strategy condition set based on the spectrum heatmap, the multi-source environmental data, and the optimization data to obtain strategy indication information includes: Based on the multi-source environmental data, the environmental conditions are verified using a first condition, and the first condition verification result is obtained. Based on the power frequency pulse information in the spectrum heatmap and the optimized data, the power frequency condition is verified as a second condition to obtain the second condition verification result. If the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information and the optimized data meet the power frequency conditions, then strategy indication information indicating the high-frequency noise protection strategy and the power frequency protection strategy is generated; or, if the first condition verification result is that the multi-source environmental data does not meet the environmental conditions, and the second condition verification result is that the power frequency pulse information or the optimized data does not meet the power frequency conditions, then the pulse conditions are verified by a third condition based on the electromagnetic pulse information in the spectrum heatmap, and a third condition verification result is obtained. If the third condition verification result is that the electromagnetic pulse information satisfies the pulse condition, then strategy indication information is generated that indicates the high-frequency noise protection strategy and the transient pulse protection strategy.

8. An anti-interference protection system for a surge arrester testing device, characterized in that, include: The first processing unit is used to acquire a protection strategy table, a spectrum heat map, and multi-source environmental data, as well as multi-source detection data from a surge arrester detection device. The protection strategy table includes transient pulse protection strategy, power frequency protection strategy, and high-frequency noise protection strategy. The second processing unit is used to perform data fusion optimization on the multi-source detection data to obtain optimized data; The third processing unit is used to perform strategy filtering on the protection strategy table based on the spectrum heatmap, the multi-source environmental data and the optimization data to obtain the target protection strategy; The fourth processing unit is used to perform anti-interference protection on the surge arrester detection device according to the target protection strategy.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor performs the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to implement the method as described in any one of claims 1-7.

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