A safety protection method and system for high-voltage equipment debugging

Abstract

The present invention provides a safety protection method and device for high-voltage equipment debugging. Among them, the method includes: obtaining debugging project information, determining the high-voltage equipment to be debugged and several associated devices according to the debugging project information; performing power risk analysis on the high-voltage equipment to be debugged and several associated devices, obtaining a debugging risk coefficient, and determining a safety distance according to the risk coefficient; outputting the safety distance to the debugger, and giving an alarm when the debugger is within the safety distance. The solution of the present invention analyzes the debugging project information to automatically determine the high-voltage equipment to be debugged and associated devices, and analyzes the corresponding debugging risk coefficient, so that the targeted safety distance can be automatically determined, effectively protecting the personal safety of the debugger during high-voltage equipment debugging.

Description

Technical Field

[0001] The present invention relates to the technical field of high-voltage safety, and more specifically, to a safety protection device and method for debugging high-voltage equipment. Background Art

[0002] High-voltage equipment is an important part of the high-voltage power system, mainly including high-voltage power distribution equipment and high-voltage power transmission equipment. High-voltage power distribution equipment includes high-voltage incoming line isolation cabinets, high-voltage incoming line cabinets, metering cabinets, transformer cabinets, lightning protection equipment, grounding switches, relay protection devices, etc. High-voltage power transmission equipment includes transformers, circuit breakers, current transformers (CTs), voltage transformers (PTs), relay protection devices, etc. High-voltage equipment needs to be debugged before it can be used. To ensure safety, during the debugging process, staff need to keep a safe distance from the high-voltage equipment. However, for the determination of the safe distance, especially for newly recruited staff, it may not be clear, resulting in safety accidents easily occurring during the debugging of high-voltage equipment. Summary of the Invention

[0003] To solve the technical problems existing in the above background art, the present invention provides a safety protection method, system, electronic device, computer storage medium, and computer program product for debugging high-voltage equipment.

[0004] The present invention provides a safety protection method for debugging high-voltage equipment, the method comprising:

[0005] Obtaining debugging project information, and determining the high-voltage equipment to be debugged and several associated devices thereof according to the debugging project information;

[0006] Performing a power risk analysis on the high-voltage equipment to be debugged and several associated devices thereof to obtain a debugging risk coefficient, and determining a safe distance according to the risk coefficient; wherein, the safe distance is positively correlated with the debugging risk coefficient;

[0007] Outputting the safe distance to the debugger, and issuing an alarm when the debugger is within the safe distance.

[0008] Preferably, the determining the high-voltage equipment to be debugged and several associated devices thereof according to the debugging project information includes:

[0009] Parsing the debugging project information to obtain the high-voltage equipment to be debugged;

[0010] Retrieving the circuit wiring diagram of the main device where the high-voltage equipment to be debugged is installed, and determining several associated devices according to the circuit wiring diagram.

[0011] Preferably, the power risk analysis of the high-voltage equipment to be debugged and its several associated devices to obtain a debugging risk coefficient includes:

[0012] Determine the preliminary debugging risk coefficient based on the attribute information of the high-voltage equipment to be debugged and each of the associated devices;

[0013] Input the attribute information of the high-voltage equipment to be debugged, each of the associated devices, and the main device into a convolutional neural model, and predict the maximum layout distance between the high-voltage equipment to be debugged and each of the associated devices;

[0014] Calculate the debugging risk by using the maximum layout distance and the preliminary debugging risk coefficient

[0015] Preferably, the calculation of the debugging risk coefficient by using the maximum layout distance and the preliminary debugging risk coefficient includes:

[0016] Calculate an adjustment coefficient by using the maximum layout distance through a conversion function, and the calculation formula of the conversion function is as follows:

[0017]

[0018] Wherein, is the adjustment coefficient, is the maximum layout distance, is the average value of the predicted layout distances between the equipment to be debugged and each of the associated devices, is the number of the associated devices, is the weight coefficient, and ; is the conversion coefficient;

[0019] Multiply the preliminary debugging risk coefficient by the adjustment coefficient to obtain the debugging risk coefficient.

[0020] Preferably, the convolutional neural model includes a two-dimensional detection model and a three-dimensional convolutional neural model;

[0021] The two-dimensional detection model respectively extracts corresponding data features from the attribute information of the high-voltage equipment to be debugged, each of the associated devices, and the main device;

[0022] Perform convolutional fusion processing on each of the data features through the pre-trained three-dimensional convolutional neural model to obtain the layout distances between the high-voltage equipment to be debugged and each of the associated devices, and output the maximum value among them as the maximum layout distance.

[0023] Preferably, the depth of the three-dimensional convolutional neural model is adjustable, specifically adjusted according to the positive correlation with the number of the associated devices.

[0024] The present invention also provides an intelligent monitoring system for high-voltage cables. The system includes an acquisition module, a risk analysis module, and a warning module. Among them, the risk analysis module is electrically connected to the acquisition module and the warning module;

[0025] The acquisition module is used to acquire debugging project information, and determine the high-voltage equipment to be debugged and its several associated devices according to the debugging project information;

[0026] The risk analysis module is used to perform power risk analysis on the high-voltage equipment to be debugged and its several associated devices, obtain a debugging risk coefficient, and determine a safety distance according to the risk coefficient. Among them, the safety distance is positively correlated with the debugging risk coefficient;

[0027] The warning module is used to output the safety distance to the debugger, and issue an alarm when the debugger is within the safety distance.

[0028] The present invention also provides an electronic device, which includes: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory and executes the method described in any one of the above.

[0029] The present invention also provides a computer storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the method described in any one of the above.

[0030] The present invention also provides a computer program product, including a computer program stored on a non-transitory computer-readable medium, characterized in that: when the computer program is executed by a processor, it implements the method described in any one of the above.

[0031] The solution of the present invention analyzes the debugging project information to automatically determine the high-voltage equipment to be debugged and its associated devices, and analyzes the corresponding debugging risk coefficient, so as to automatically determine the targeted safety distance, which can effectively guarantee the personal safety of the debugger during the debugging of high-voltage equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0033] Figure 1It is a schematic flowchart of a safety protection method for high-voltage equipment debugging disclosed in an embodiment of the present invention;

[0034] Figure 2 It is a schematic structural diagram of a safety protection system for high-voltage equipment debugging disclosed in an embodiment of the present invention. Specific embodiments

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations.

[0036] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0037] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0038] In the description of the present invention, it should be noted that if terms such as "upper", "lower", "inner", "outer", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the present invention is usually placed during use. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation of the present invention.

[0039] In addition, if terms such as "first", "second", etc. are only used for distinguishing descriptions, they cannot be understood as indicating or implying relative importance.

[0040] Please refer to Figure 1 , an embodiment of the present invention discloses a safety protection method for high-voltage equipment debugging, and the method includes:

[0041] Obtain debugging project information, and determine the high-voltage equipment to be debugged and its several associated devices according to the debugging project information;

[0042] Perform a power risk analysis on the high-voltage equipment to be debugged and its several associated devices to obtain a debugging risk coefficient, and determine a safety distance according to the risk coefficient; wherein, the safety distance is positively correlated with the debugging risk coefficient;

[0043] Output the safety distance to the debugger, and issue an alarm when the debugger is within the safety distance.

[0044] The present invention analyzes the information of the current debugging project to determine the high-voltage equipment to be debugged involved in the current debugging and several associated devices associated with the equipment to be debugged. By using a suitable method to perform a power risk analysis on these devices, a corresponding debugging risk coefficient can be obtained, and then the size of the safety distance can be determined according to the obtained debugging risk coefficient and the corresponding positive correlation function. Finally, before the debugging starts, prompt the debugger to be outside the safety distance. If the debugger is still within the safety distance, an alarm is output.

[0045] Therefore, the solution of the present invention automatically determines the high-voltage equipment to be debugged and associated devices by analyzing the debugging project information, and analyzes and obtains the corresponding debugging risk coefficient, so that a targeted safety distance can be automatically determined, effectively ensuring the personal safety of the debugger during the debugging of high-voltage equipment.

[0046] The solution of the present invention can be applied to a special vehicle on which the debugger rides, and is equipped with an alarm system. Multiple pieces of debugging project information are stored in the alarm system. By performing the above analysis on the information of the current debugging project, the safety distance can be determined, and then the safety distance and alarm information are output to the debugger through an output device installed on the special vehicle. In fact, in addition to outputting the safety distance and alarming, the alarm system can also be used to connect to the background server to obtain multiple pieces of debugging project information, and can also receive relevant information related to the debugging project manually input by the debugger, such as the high-voltage equipment to be debugged, debugging results, etc.

[0047] Among them, the safety distance is positively correlated with the debugging risk coefficient, that is, the greater the debugging risk coefficient, the greater the safety distance. At this time, the debugger needs to perform debugging operations farther away; on the contrary, the smaller the debugging risk coefficient, the smaller the safety distance. At this time, the debugger can perform debugging operations closer. The present invention does not limit the calculation formula representing the positive correlation relationship between the safety distance and the debugging risk coefficient. For example, it can be: safety distance = a × debugging risk coefficient + b, where a is a weight coefficient greater than 1 and b is the basic distance.

[0048] Preferably, the determining the high-voltage equipment to be debugged and its several associated devices according to the debugging project information includes:

[0049] Parse the debugging project information to obtain the high-voltage equipment to be debugged;

[0050] Retrieve the circuit wiring diagram of the main device where the high-voltage device to be debugged is installed, and determine a number of associated devices according to the circuit wiring diagram.

[0051] In the embodiment of the present invention, the name, number, etc. of the high-voltage device to be debugged are directly recorded in the debugging project information. By directly parsing the debugging project information, the device to be debugged to be debugged this time can be determined. For associated devices, the circuit wiring diagram of the main device where the high-voltage device to be debugged is installed can be further retrieved. The main device can be a small transformer bank, and the device to be debugged can be a current transformer (CT) in the small transformer bank. According to the above circuit wiring diagram, a number of devices electrically connected to the device to be debugged can be determined. Then, according to the preset electrical rules, a number of devices affected by the device to be debugged can be determined. For example, some devices directly electrically connected to the device to be debugged are selected as associated devices, and some devices that are not directly electrically connected to the device to be debugged but are still indirectly affected by the current or voltage fluctuations of the device to be debugged will also be selected as associated devices.

[0052] It should be noted that when the device to be debugged is being debugged, large current and voltage fluctuations may occur, resulting in phenomena such as breakdown, fire, and arc excitation in the power equipment electrically connected to it. These phenomena will pose hazards to the debugging personnel; and when the above-mentioned directly electrically connected power equipment breaks down or catches fire, the equipment connected to these power equipment (i.e., the equipment indirectly connected to the device to be debugged) may also be affected, resulting in phenomena such as short circuit, fire, and arc excitation in these equipment. Therefore, it also needs to be used as an associated device.

[0053] Preferably, the power risk analysis of the high-voltage device to be debugged and its several associated devices to obtain a debugging risk coefficient includes:

[0054] Determine the preliminary debugging risk coefficient based on the attribute information of the high-voltage device to be debugged and each of the associated devices;

[0055] Input the attribute information of the high-voltage device to be debugged, each of the associated devices, and the main device into a convolutional neural model to predict the maximum layout distance between the high-voltage device to be debugged and each of the associated devices;

[0056] Calculate the debugging risk coefficient from the maximum layout distance and the preliminary debugging risk coefficient.

[0057] In the embodiments of the present invention, by analyzing the attribute information of high-voltage equipment, it is possible to determine the possible dangerous situations that may occur when the high-voltage equipment fails during debugging, such as the breakdown, fire, arc excitation, etc. mentioned above, and it is also possible to determine the maximum influence distance range of the above phenomena. Among them, the above dangerous situations and the maximum influence distance can be measured in advance. At the same time, the convolutional neural model can also select the maximum layout distance among the high-voltage equipment and the layout distances of these high-voltage equipment on the main device where they are installed, and accordingly reasonably adjust the preliminary debugging risk coefficient obtained above to obtain the final debugging risk coefficient. Among them, the attribute information of the high-voltage equipment to be debugged and the associated equipment mainly includes the equipment name, equipment model, electrical parameters, etc., and the attribute information of the main device mainly includes the device name, input / output voltage of the device, etc.

[0058] It should be noted that the installation and layout position relationship of high-voltage equipment on the main device is regular. For example, various cabinets are generally arranged below the main device, while circuit breakers, current transformers (CTs), voltage transformers (PTs), etc. are generally arranged above the main device. There are also some rules or regulations for the left-right and front-back layout of some high-voltage equipment. Through the above convolutional neural model, the maximum layout distance between the high-voltage equipment to be debugged and each associated equipment on a specific main device can be predicted based on the attribute information.

[0059] Preferably, the calculating the debugging risk coefficient from the maximum layout distance and the preliminary debugging risk coefficient includes:

[0060] Calculating an adjustment coefficient from the maximum layout distance through a conversion function, and the calculation formula of the conversion function is as follows:

[0061]

[0062] Wherein, is the adjustment coefficient, is the maximum layout distance, is the average value of the predicted layout distances between the equipment to be debugged and each associated equipment, is the number of associated equipment, is the weight coefficient, and ; is the conversion coefficient;

[0063] Multiplying the preliminary debugging risk coefficient by the adjustment coefficient to obtain the debugging risk coefficient.

[0064] In the embodiments of the present invention, the present invention designs the above conversion function to convert the maximum layout distance into an adjustment coefficient. Obviously, the larger the maximum layout distance, the larger the threat range. Correspondingly, a larger adjustment coefficient is set to increase the debugging risk coefficient, thereby reminding the debugging personnel to keep outside a larger safety distance. At the same time, the above conversion function also includes a fine-tuning part. When the deviation is larger, it indicates that the maximum layout distance mainly poses a threat to the debugging personnel, that is, the safety distance can be determined only based on the maximum layout distance; when the deviation is smaller, it means that the gap between the maximum layout distance and other layout distances is not large. At this time, more threats posed by other layout distances need to be considered, and the adjustment coefficient should be appropriately increased to ensure safety. In addition, is a value greater than 1, such as 1.3, 1.5, 1.8, while is a value less than 1, such as 0.8, 0.6, 0.5.

[0065] Preferably, the convolutional neural model includes a two-dimensional detection model and a three-dimensional convolutional neural model;

[0066] The two-dimensional detection model respectively extracts corresponding data features from the attribute information of the high-voltage equipment to be debugged, each of the associated devices, and the main device;

[0067] Through the pre-trained three-dimensional convolutional neural model, convolutional fusion processing is performed on each of the data features to obtain the layout distances between the high-voltage equipment to be debugged and each of the associated devices, and the maximum value among them is output as the maximum layout distance.

[0068] In the embodiments of the present invention, the convolutional neural model in the present invention includes two parts: a two-dimensional detection model and a three-dimensional convolutional neural model. The two-dimensional detection model is only used to extract useful information from the attribute information, such as the above-mentioned equipment name, equipment model, electrical parameters, device name, input / output voltage of the device, etc., and then perform feature processing on it to obtain corresponding data features, and fuse the data features to obtain a feature matrix. The three-dimensional convolutional neural model can then perform overall processing on the feature matrix that has fused the three types of attribute information, so as to predict the layout distances between the high-voltage equipment to be debugged and each of the associated devices on the main device, and output the maximum layout distance among them.

[0069] Among them, the three-dimensional convolutional neural model needs to be pre-trained sufficiently before it can be put into use. The training dataset should be [data features corresponding to the attributes of the first high-voltage device, data features corresponding to the attributes of the second high-voltage device, data features corresponding to the attributes of the main device, and marked data of the layout distance between the first high-voltage device and the second high-voltage device]. The first high-voltage device among them corresponds to the high-voltage device to be debugged in the present invention, and the second high-voltage device corresponds to the associated device. The marked data contains the corresponding layout distance, which can be either a specific distance value or a distance range.

[0070] The above two-dimensional detection model can be a two-dimensional convolutional neural model or any other model.

[0071] Preferably, the depth of the three-dimensional convolutional neural model is adjustable, specifically adjusted according to the positive correlation relationship with the number of the associated devices.

[0072] In the embodiment of the present invention, the three-dimensional convolutional neural model includes a convolutional layer, a batch normalization layer, and a pooling layer. Since when the number of associated devices is larger, the layout design of these devices on the main device is more complex, and the corresponding layout rules behind it are also more complex. In this regard, the three-dimensional convolutional neural model in the present invention is actually composed of multiple three-dimensional convolutional sub-neural models, and the depths of the respective three-dimensional convolutional sub-neural models are different, that is, the number of layers of the batch normalization layer is different, and the number of layers of the batch normalization layer is in a positive correlation relationship with the number of associated devices.

[0073] Please refer to Figure 2 , the embodiment of the present invention also discloses that the present invention also provides a high-voltage cable intelligent monitoring system, and the system includes an acquisition module, a risk analysis module, and a warning module; among them, the risk analysis module is electrically connected to the acquisition module and the warning module;

[0074] The acquisition module is used to acquire debugging project information and determine the high-voltage device to be debugged and its several associated devices according to the debugging project information;

[0075] The risk analysis module is used to perform power risk analysis on the high-voltage device to be debugged and its several associated devices, obtain a debugging risk coefficient, and determine a safety distance according to the risk coefficient;

[0076] The warning module is used to output the safety distance to the debugger and issue an alarm when the debugger is within the safety distance.

[0077] An embodiment of the present invention also discloses an electronic device, which includes: a memory storing executable program code; a processor coupled to the memory; and the processor calls the executable program code stored in the memory to execute the method described in the foregoing embodiment.

[0078] An embodiment of the present invention also discloses a computer storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the method described in the foregoing embodiment.

[0079] An embodiment of the present invention also discloses a computer program product, which includes a computer program that can be executed by a processor to implement the method described in the foregoing embodiment.

[0080] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0081] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0083] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims described above.

Claims

1. A safety protection method for high voltage equipment commissioning, characterized in that: The method comprises: Acquire debugging project information, and determine the high-voltage equipment to be debugged and several associated equipment thereof according to the debugging project information; Conducting power risk analysis on the high-voltage equipment to be debugged and several of its associated equipment to obtain a debugging risk coefficient, and determining a safe distance according to the debugging risk coefficient; Outputting the safety distance to a commissioning personnel, and issuing an alarm when the commissioning personnel is within the safety distance; The step of performing power risk analysis on the high-voltage equipment to be debugged and the associated equipment to obtain a debugging risk coefficient includes: Determine a preliminary debugging risk coefficient based on the attribute information of the high-voltage equipment to be debugged and each of the associated equipment; wherein the preliminary debugging risk coefficient is related to the maximum impact distance range corresponding to the dangerous situation that may occur when the high-voltage equipment to be debugged fails to debug; According to the attribute information of the high-voltage equipment to be debugged, each of the associated equipment and the main device, the convolutional neural model is input to predict the maximum layout distance between the high-voltage equipment to be debugged and each of the associated equipment; The debugging risk coefficient is calculated according to the maximum deployment distance and the preliminary debugging risk coefficient; The step of determining the high-voltage equipment to be debugged and several associated equipment thereof according to the debugging project information includes: Parsing the debugging project information to obtain the high-voltage equipment to be debugged; Retrieving a circuit wiring diagram of a main device in which the high-voltage equipment to be debugged is installed, and determining a number of associated equipment according to the circuit wiring diagram; The step of calculating the debugging risk coefficient according to the maximum deployment distance and the preliminary debugging risk coefficient includes: The maximum layout distance is calculated through a conversion function to obtain an adjustment coefficient, and the calculation formula of the conversion function is as follows: Among them, γ is the adjustment coefficient, d max is the maximum deployment distance, is the average value of the predicted layout distances between the device to be debugged and each of the associated devices, n is the number of the associated devices, p1 and p2 are weight coefficients, and p1>p2; α is the conversion coefficient; The debugging risk factor is obtained by multiplying the preliminary debugging risk factor by the adjustment factor.

2. A safety protection method for high voltage equipment commissioning according to claim 1, characterized in that: The convolutional neural model includes a two-dimensional detection model and a three-dimensional convolutional neural model; The two-dimensional detection model extracts corresponding data features from the attribute information of the high-voltage equipment to be debugged, each of the associated equipment and the main device; The pre-trained three-dimensional convolutional neural model is used to perform convolution fusion processing on each of the data features to obtain the layout distances between the high-voltage equipment to be debugged and each of the associated equipment, and the maximum value thereof is output as the maximum layout distance.

3. A safety protection method for high voltage equipment debugging according to claim 2, characterized in that: The depth of the three-dimensional convolutional neural model is adjustable, specifically, it is adjusted according to a positive correlation based on the number of associated devices.

4. A high voltage cable intelligent monitoring system, characterized in that: The system comprises an acquisition module, a risk analysis module and a warning module; wherein the risk analysis module is electrically connected to the acquisition module and the warning module; The acquisition module is used to acquire the debugging project information, and determine the high-voltage equipment to be debugged and several associated equipment thereof according to the debugging project information, including: Parsing the debugging project information to obtain the high-voltage equipment to be debugged; Retrieving a circuit wiring diagram of a main device in which the high-voltage equipment to be debugged is installed, and determining a number of associated equipment according to the circuit wiring diagram; The risk analysis module is used to perform power risk analysis on the high-voltage equipment to be debugged and several of its associated equipment to obtain a debugging risk coefficient, including: determining a preliminary debugging risk coefficient based on the attribute information of the high-voltage equipment to be debugged and each of the associated equipment; wherein the preliminary debugging risk coefficient is related to the maximum impact distance range corresponding to the dangerous situation that may occur when the high-voltage equipment to be debugged fails to debug; inputting the attribute information of the high-voltage equipment to be debugged, each of the associated equipment and the main device into the convolutional neural model to predict the maximum layout distance between the high-voltage equipment to be debugged and each of the associated equipment; calculating the debugging risk coefficient based on the maximum layout distance and the preliminary debugging risk coefficient, including: The maximum layout distance is calculated through a conversion function to obtain an adjustment coefficient, and the calculation formula of the conversion function is as follows: Among them, γ is the adjustment coefficient, d max is the maximum deployment distance, is the average value of the predicted layout distances between the device to be debugged and each of the associated devices, n is the number of the associated devices, p1 and p2 are weight coefficients, and p1>p2; α is the conversion coefficient; Multiplying the preliminary debugging risk coefficient by the adjustment coefficient to obtain the debugging risk coefficient; Determining a safety distance according to the risk coefficient; wherein the safety distance is positively correlated with the debugging risk coefficient; The warning module is used to output the safety distance to the debugging personnel and issue an alarm when the debugging personnel is within the safety distance.

5. An electronic device, comprising: A memory storing executable program code; A processor coupled to the memory; characterized in that: the processor calls the executable program code stored in the memory to execute the method according to any one of claims 1-3.

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

7. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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