Defect detection method and device of insulation monitoring device, computer equipment and program product

Abstract

The invention relates to a defect detection method and device for an insulation monitoring device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: responding to a detection request of an insulation monitoring device, and connecting the insulation monitoring device; simulating a preset fault on the insulation monitoring device through the automatic test platform, and collecting an impedance measurement value and an early warning response duration generated by the insulation monitoring device in a preset fault generation process; calculating a difference value between the impedance measurement value and a theoretical impedance value corresponding to a preset fault, and taking a quotient of the difference value and the theoretical impedance value as an impedance error value; and determining the defect of the insulation monitoring device based on the early warning response duration and the impedance error value. By adopting the method, the defect detection efficiency of the insulation monitoring device can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of device detection technology, and in particular to a defect detection method, device, computer equipment, computer-readable storage medium, and computer program product for an insulation monitoring device. Background Art

[0002] With the continuous development of the power system, the safe operation of power equipment such as substations is of vital importance. As one of the key equipment to ensure the safe operation of the power system, the reliability of the performance of the insulation monitoring device is directly related to the stability and safety of the power system.

[0003] In the related art, when a fault occurs in an insulation monitoring device, testers can only rely on performing complex operations around the high-voltage electrical equipment and checking each function of the device one by one. This method is inefficient in detecting defects. Summary of the Invention

[0004] Based on this, it is necessary to provide a defect detection method, device, computer equipment, computer-readable storage medium and computer program product for an insulation monitoring device that can improve defect detection efficiency in response to the above technical problems.

[0005] In a first aspect, the present application provides a defect detection method for an insulation monitoring device, comprising:

[0006] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0007] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0008] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0009] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0010] In one embodiment, determining a defect of the insulation monitoring device based on the warning response time and the impedance error value includes:

[0011] When the impedance error value is not greater than the first impedance threshold and the warning response time is greater than the time threshold, determining that a software defect occurs in the insulation monitoring device;

[0012] When the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, determining that a hardware defect occurs in the insulation monitoring device;

[0013] When the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, it is determined that both the software and the hardware in the insulation monitoring device are defective;

[0014] When the impedance error value is greater than the first impedance threshold and not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

[0015] In one embodiment, the method further comprises:

[0016] Calculating a first difference between the impedance measurement value and a theoretical impedance value corresponding to a preset insulation monitoring device standard, and using the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard as a standard adaptation deviation of the impedance;

[0017] Calculating a second difference between the warning response time and a theoretical response time corresponding to a preset insulation monitoring device standard, and taking the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard as a standard adaptation deviation of the response time;

[0018] When both the standard adaptation deviation of the impedance and the standard adaptation deviation of the response time are greater than preset standard values, it is determined that the insulation monitoring device has a compatibility defect with the preset standard.

[0019] In one embodiment, the preset faults include: ground fault, ring network fault, AC inrush fault and system capacitor fault.

[0020] In one embodiment, the method further comprises:

[0021] If, during multiple detections of the insulation monitoring device, it is detected that the previous defect has been resolved each time and the impedance error value detected each time is greater than the second impedance threshold, it is determined that a topological structure of the insulation monitoring device has a defect.

[0022] In one embodiment, the method further comprises:

[0023] After the insulation monitoring device is inspected, the defect location and corresponding improvement plan of the insulation monitoring device are determined based on a preset defect feature comparison library, and an inspection report of the insulation monitoring device is output; the inspection report includes the defect location, inspection time point, impedance error value, warning response time and the corresponding improvement plan.

[0024] In a second aspect, the present application further provides a defect detection device for an insulation monitoring device, comprising:

[0025] a connection module, configured to respond to a detection request from the insulation monitoring device and connect to the insulation monitoring device;

[0026] an acquisition module, configured to simulate a preset fault on the insulation monitoring device through an automatic test platform, and acquire an impedance measurement value and an early warning response duration generated by the insulation monitoring device during the occurrence of the preset fault;

[0027] a calculation module for calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0028] A determination module is used to determine a defect of the insulation monitoring device based on the early warning response time and the impedance error value.

[0029] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0031] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0032] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0033] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0035] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0036] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0037] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0038] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0039] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0040] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0041] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0042] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0043] Based on the warning response time and the impedance error value, the defect of the insulation monitoring device is determined. The above-mentioned insulation monitoring device defect detection method, device, computer equipment, computer-readable storage medium and computer program product first respond to the detection request of the insulation monitoring device and connect the insulation monitoring device; simulate a preset fault on the insulation monitoring device through an automatic testing platform, and collect the impedance measurement value and warning response time generated by the insulation monitoring device during the occurrence of the preset fault; calculate the difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault, and use the quotient of the difference and the theoretical impedance value as the impedance error value; based on the warning response time and the impedance error value, determine the defect of the insulation monitoring device. In this way, through the automatic testing platform, automated testing of the insulation monitoring device is achieved, manual operations are reduced, and the corresponding missing items are directly determined through the quantified data impedance error value and the warning response time, thereby improving the efficiency of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A schematic diagram of the connection structure of an automatic test platform in one embodiment;

[0046] Figure 2 1 is a flow chart of a defect detection method for an insulation monitoring device according to an embodiment;

[0047] Figure 3 is a flow chart of a defect detection method for an insulation monitoring device in another embodiment;

[0048] Figure 4 is a structural block diagram of a defect detection device of an insulation monitoring device in one embodiment;

[0049] Figure 5 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0051] It should be noted that the terms "first", "second", etc. used in this application may 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 "including" and "having" used in this application and any variations thereof are intended to cover non-exclusive inclusions. The term "plurality" used in this application refers to two or more. The term "and / or" used in this application refers to one of the solutions or any combination of multiple solutions.

[0052] The defect detection method of the insulation monitoring device provided in the embodiment of the present application can be applied to Figure 1 The connection structure on the automatic test platform shown in the figure. The embodiments of the present application can simulate the occurrence of various preset faults through the automatic test platform, thereby detecting defects in the insulation monitoring device. R1 and R2 are resistors, K1, K2, K3, K4, K5, and K6 are switches, C1 and C2 are capacitors, and PE is the protective ground wire.

[0053] In an exemplary embodiment, Figure 2 As shown, a detection method for an insulation monitoring device is provided, which is described by taking the application of the method to an automatic test platform as an example, and includes the following steps 202 to 208.

[0054] Step 202: respond to a detection request from the insulation monitoring device and connect to the insulation monitoring device.

[0055] Exemplarily, the automatic test platform responds to a detection request for the insulation monitoring device and connects the automatic test platform to the insulation monitoring device.

[0056] Among them, the automatic testing platform is a testing platform with automatic control and data analysis functions.

[0057] Step 204 : Simulate a preset fault on the insulation monitoring device through the automatic test platform, and collect impedance measurement values ​​and warning response duration generated by the insulation monitoring device during the occurrence of the preset fault.

[0058] Optionally, by changing the connection relationship between the various components on the automatic test platform, ground faults, ring network faults, AC inrush faults and system capacitance faults are simulated, and the impedance measurement values ​​and early warning response times generated by the insulation monitoring device during various faults are collected.

[0059] Step 206 : Calculate the difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault, and use the quotient of the difference and the theoretical impedance value as the impedance error value.

[0060] Exemplarily, the difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault is calculated, and the quotient of the difference and the theoretical impedance value is taken as the impedance error value. The specific calculation formula is shown in (1).

[0061] (1)

[0062] in, is the impedance measurement value, is the theoretical impedance value corresponding to the preset fault, and δZ is the impedance error value.

[0063] Step 208: Determine the defect of the insulation monitoring device based on the warning response time and the impedance error value.

[0064] Optionally, the warning response time and the range of the impedance error value are determined to determine the defect of the insulation monitoring device.

[0065] In the above-mentioned defect detection method for an insulation monitoring device, the following steps are performed: responding to a detection request from the insulation monitoring device and connecting the insulation monitoring device; simulating a preset fault on the insulation monitoring device through an automated testing platform, collecting the impedance measurement value and warning response time generated by the insulation monitoring device during the preset fault; calculating the difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault, and using the quotient of this difference and the theoretical impedance value as the impedance error value; and determining the defect of the insulation monitoring device based on the warning response time and the impedance error value. In this way, the automated testing platform enables automated testing of the insulation monitoring device, reducing manual operations and directly determining the corresponding missing item based on the quantified impedance error value and warning response time, thereby improving detection efficiency.

[0066] In an exemplary embodiment, based on the early warning response time and the impedance error value, the defect of the insulation monitoring device is determined, including: when the impedance error value is not greater than the first impedance threshold and the early warning response time is greater than the time threshold, determining that a software defect occurs in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, determining that a hardware defect occurs in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, determining that both the software and hardware of the insulation monitoring device have defects; when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, determining that the measurement accuracy of the insulation monitoring device is insufficient.

[0067] In actual implementation, the defects of the insulation monitoring device are determined based on the early warning response time Δt and the impedance error value δZ. When the impedance error value is not greater than the first impedance threshold and the early warning response time is greater than the time threshold, it indicates that the detection result is accurate but the response time is too long, indicating that the software processing efficiency is low, and it is determined that there is a software defect in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it indicates that the detection error is large but the response is rapid, and it is determined that there is a hardware defect in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, it indicates that the detection error is large and the response is slow, and it is determined that there are defects in both the software and hardware of the insulation monitoring device; when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it indicates that there is a certain error in the detection, but it does not exceed the threshold and the response is rapid, and it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

[0068] Among them, the first impedance threshold, the duration threshold and the second impedance threshold can be set by the user according to actual conditions, and the embodiments of the present application do not limit this.

[0069] For example, when the first impedance threshold is 5%, the time threshold is 2 seconds, and the second impedance threshold is 10%, when δZ ≤ 5% and Δt ≤ 2s, the insulation monitoring device is detected normally; when δZ ≤ 5% and Δt > 2s, it is determined that a software defect has occurred in the insulation monitoring device; when δZ > 10% and Δt ≤ 2s, it is determined that a hardware defect has occurred in the insulation monitoring device; when δZ > 10% and Δt > 2s or 5% < δZ ≤ 10% and Δt > 2s, it is determined that both the software and hardware of the insulation monitoring device have defects; and when 5% < δZ ≤ 10% and Δt ≤ 2s, it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

[0070] In the above embodiment, the response of the insulation monitoring device is converted into quantifiable parameters, namely the impedance error value and the warning response time, and a corresponding relationship between the defect and the quantified parameters is established. The defect is located most directly through the quantified parameters, thereby accelerating the detection efficiency.

[0071] In an exemplary embodiment, the defect detection method of the insulation monitoring device also includes: calculating a first difference between the impedance measurement value and the theoretical impedance value corresponding to the preset insulation monitoring device standard, and taking the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard as the standard adaptation deviation of the impedance; calculating a second difference between the early warning response time and the theoretical response time corresponding to the preset insulation monitoring device standard, and taking the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard as the standard adaptation deviation of the response time; when the standard adaptation deviation of the impedance and the standard adaptation deviation of the response time are both greater than the preset standard value, it is determined that the insulation monitoring device has a compatibility defect with the preset standard.

[0072] In actual implementation, the first difference between the impedance measurement value and the theoretical impedance value corresponding to the preset insulation monitoring device standard is calculated, and the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard is used as the standard adaptation deviation of the impedance; the second difference between the early warning response time and the theoretical response time corresponding to the preset insulation monitoring device standard is calculated, and the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard is used as the standard adaptation deviation of the response time; when the standard adaptation deviation of the impedance is greater than the preset standard value of the impedance and the standard adaptation deviation of the response time is greater than the preset standard value of the time, it is determined that the insulation monitoring device has a compatibility defect with the preset standard.

[0073] Among them, the preset insulation monitoring device standard can be set by the user according to specific circumstances, and the embodiment of the present application does not limit this.

[0074] In the above embodiment, by comparing the deviations of the impedance and the response time with the standard, it is ensured that the standard of the insulation monitoring device is appropriate, thereby ensuring that the detection result of the insulation monitoring device is accurate.

[0075] In an exemplary embodiment, the preset faults include: ground fault, ring network fault, AC inrush fault, and system capacitor fault.

[0076] In actual implementation, the automatic test platform can simulate ground faults, ring network faults, AC inrush faults and system capacitance faults by changing the connection method of the specific structure.

[0077] For example, Figure 1 As shown, the DC power supply is a standard source output 220V / 110V DC power supply. The switch K1 can be closed to point a, at this time R1 is connected to the positive pole, simulating a positive grounding fault. The switch K1 can be closed to point b, at this time R1 is connected to the negative pole, simulating a negative grounding fault, and the same applies to R2. When K5 and K6 are closed accordingly, an AC inrush fault is simulated. There is a special ring network test interface on the automatic test platform panel, which is used to connect the ring network part of the insulation monitoring device to simulate a ring network fault. The system capacitor fault is simulated through capacitors C1 and C2.

[0078] In the above embodiment, various preset faults are simulated by the automatic testing platform, thereby realizing automatic detection of the insulation monitoring device, reducing the manual processing process and accelerating the detection efficiency.

[0079] In an exemplary embodiment, the insulation monitoring device method further includes: determining that a topology structure of the insulation monitoring device has a defect when, during multiple detections of the insulation monitoring device, each time a previous defect is detected and resolved, and the impedance error value detected each time is greater than a second impedance threshold.

[0080] In actual implementation, the insulation monitoring device is tested multiple times, and before each test, it is ensured that the insulation monitoring device is free of defects. When the impedance error value obtained in each test is greater than the second impedance threshold, it is determined that the topology structure of the insulation monitoring device is defective.

[0081] In one embodiment, the system uses the quantified resolution of multi-point grounding test data to identify topological defects in the insulation monitoring device. When simulating a single-point positive ground fault (e.g., setting R1 = 15kΩ), the system records the R1 impedance error δZ reported by the device. If δZ remains consistently greater than 10%, it is determined that the sampling circuit has a linearity defect. When a negative ground fault is superimposed to form a multi-point grounding scenario (e.g., adding R2 = 20kΩ), the system focuses on analyzing the device's accuracy in identifying the dual-ground resistance ratio (calculating |R1_measured / R2_measured - R1_set / R2_set|). If this ratio deviates by more than 5%, it indicates that the device cannot accurately resolve the topological relationship of the parallel fault branch, thereby exposing a logical flaw in the topology identification algorithm.

[0082] In one embodiment, the anti-interference capability of the insulation monitoring device is detected by controlling the injection of AC power; for example, by closing K5, simulating positive interference, and counting the frequency of false alarms during repeated testing, the anti-interference capability of the insulation monitoring device is quantified.

[0083] In the above embodiment, detecting whether there are defects in the topological structure of the insulation monitoring device and then repairing the defects can effectively improve the reliability and safety of the insulation monitoring device.

[0084] In an exemplary embodiment, after the insulation monitoring device is inspected, the defect location and corresponding improvement plan of the insulation monitoring device are determined based on a preset defect feature comparison library, and an inspection report of the insulation monitoring device is output.

[0085] Among them, the inspection report includes the defect location, inspection time point, impedance error value, warning response time and corresponding improvement plan.

[0086] In actual implementation, after the insulation monitoring device inspection is completed, the defect location and corresponding improvement plan of the insulation monitoring device are determined based on the preset defect feature comparison library, impedance error value, and early warning response time, and an inspection report of the insulation monitoring device is output.

[0087] In one embodiment, when defects occur in the insulation monitoring device software, the corresponding improvement plan is to optimize the signal processing algorithm, such as reducing the FIR filter order and adjusting the cutoff frequency; when defects occur in the insulation monitoring device hardware, the specific location of the defective hardware is determined based on a preset defect feature comparison library, and the corresponding hardware is replaced; when defects occur in both the insulation monitoring device software and hardware, the relevant hardware is replaced at the same time and the relevant algorithm is optimized; when the measurement accuracy of the insulation monitoring device is insufficient, the insulation monitoring device is recalibrated and the hardware aging problem is checked.

[0088] In the above embodiment, accurate positioning of the insulation monitoring device is achieved through a multi-parameter combination rule, thereby accelerating the detection efficiency of the insulation monitoring device.

[0089] To explain the defect detection method of the insulation monitoring device in this application in detail, an embodiment is described below. The specific flow chart is as follows: Figure 3 As shown, illustratively, the present application describes a defect detection method for an insulation monitoring device in a specific test scenario.

[0090] First, the automatic test platform responds to a detection request for the insulation monitoring device and connects the automatic test platform to the insulation monitoring device.

[0091] By changing the connection relationship between the various components on the automatic test platform, ground faults, ring network faults, AC inrush faults, and system capacitance faults are simulated, and the impedance measurement values ​​and warning response times generated by the insulation monitoring device during various faults are collected. The difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault is calculated, and the quotient of the difference and the theoretical impedance value is used as the impedance error value. The specific calculation formula is shown in (1).

[0092] According to the early warning response time Δt and the impedance error value δZ, the defect of the insulation monitoring device is determined. When the impedance error value is not greater than the first impedance threshold and the early warning response time is greater than the time threshold, it indicates that the detection result is accurate but the response time is too long, indicating that the software processing efficiency is low, and it is determined that there is a software defect in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it indicates that the detection error is large but the response is rapid, and it is determined that there is a hardware defect in the insulation monitoring device; when the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, it indicates that the detection error is large and the response is slow, and it is determined that there are defects in both the software and hardware of the insulation monitoring device; when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it indicates that there is a certain error in the detection, but it does not exceed the threshold and the response is rapid, and it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

[0093] Calculate the first difference between the impedance measurement value and the theoretical impedance value corresponding to the preset insulation monitoring device standard, and use the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard as the standard adaptation deviation of the impedance; calculate the second difference between the early warning response time and the theoretical response time corresponding to the preset insulation monitoring device standard, and use the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard as the standard adaptation deviation of the response time; when the standard adaptation deviation of the impedance is greater than the preset standard value of the impedance and the standard adaptation deviation of the response time is greater than the preset standard value of the time, determine that the insulation monitoring device has a compatibility defect with the preset standard.

[0094] After the insulation monitoring device inspection is completed, the defect location and corresponding improvement plan of the insulation monitoring device are determined based on the preset defect feature comparison library, impedance error value, and early warning response time, and an inspection report of the insulation monitoring device is output.

[0095] This application converts the response of the insulation monitoring device into quantifiable parameters, namely the impedance error value and the warning response time, establishes a corresponding relationship between defects and quantified parameters, and accelerates the detection efficiency.

[0096] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless clearly stated herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps. It is understandable that the various steps in different embodiments can be freely combined as needed, and the various non-contradictory schemes formed by the combination all fall within the scope of protection of this application.

[0097] Based on the same inventive concept, embodiments of the present application also provide a defect detection device for an insulation monitoring device for implementing the aforementioned defect detection method for an insulation monitoring device. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of the defect detection device for one or more insulation monitoring devices provided below can be found in the aforementioned limitations of the defect detection method for an insulation monitoring device, and will not be further elaborated here.

[0098] In an exemplary embodiment, Figure 4As shown, a defect detection device for an insulation monitoring device is provided, comprising: a connection module 401, a collection module 402, a calculation module 403 and a determination module 404, wherein:

[0099] The connection module is used to respond to a detection request from the insulation monitoring device and connect to the insulation monitoring device.

[0100] The acquisition module is used to simulate a preset fault on the insulation monitoring device through an automatic test platform, and collect the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault.

[0101] The calculation module calculates the difference between the impedance measurement value and the theoretical impedance value corresponding to the preset fault, and uses the quotient of the difference and the theoretical impedance value as the impedance error value.

[0102] A determination module is used to determine a defect of the insulation monitoring device based on the early warning response time and the impedance error value.

[0103] In an exemplary embodiment, the determination module is further configured to determine that a software defect occurs in the insulation monitoring device when the impedance error value is not greater than a first impedance threshold and the warning response duration is greater than a duration threshold;

[0104] When the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, determining that a hardware defect occurs in the insulation monitoring device;

[0105] When the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, it is determined that both the software and the hardware in the insulation monitoring device are defective;

[0106] When the impedance error value is greater than the first impedance threshold and not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

[0107] In an exemplary embodiment, the determination module is further configured to calculate a first difference between the impedance measurement value and a theoretical impedance value corresponding to a preset insulation monitoring device standard, and use the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard as the standard adaptation deviation of the impedance;

[0108] Calculating a second difference between the warning response time and a theoretical response time corresponding to a preset insulation monitoring device standard, and taking the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard as a standard adaptation deviation of the response time;

[0109] When both the standard adaptation deviation of the impedance and the standard adaptation deviation of the response time are greater than preset standard values, it is determined that the insulation monitoring device has a compatibility defect with the preset standard.

[0110] In an exemplary embodiment, the preset faults include: ground fault, ring network fault, AC inrush fault, and system capacitor fault.

[0111] In an exemplary embodiment, the above-mentioned determination module is also used to determine that a topological structure of the insulation monitoring device has a defect when, during multiple detections of the insulation monitoring device, the previous defect is re-detected and resolved each time, and the impedance error value detected each time is greater than the second impedance threshold.

[0112] In an exemplary embodiment, the device also includes an output module for determining the defect location and corresponding improvement plan of the insulation monitoring device based on a preset defect feature comparison library after the insulation monitoring device is inspected, and outputting an inspection report of the insulation monitoring device; the inspection report includes the defect location, inspection time point, impedance error value, warning response duration and the corresponding improvement plan.

[0113] Each module in the defect detection device of the insulation monitoring device described above may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0114] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface, a display unit and an input device. The processor, memory and input / output interface are connected via a system bus, and the communication interface, display unit and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store detection data of the insulation monitoring device. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a defect detection method for an insulation monitoring device is implemented.

[0115] The display unit of the computer device is used to produce a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, a keypad, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0116] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0117] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0118] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0119] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0120] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0121] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0122] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0123] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0124] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0125] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0126] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0127] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0128] responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device;

[0129] Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault;

[0130] Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value;

[0131] A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

[0132] 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, stored data, displayed data, 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 relevant data must comply with relevant regulations.

[0133] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, 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 various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0134] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, 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.

[0135] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A defect detection method for an insulation monitoring device, characterized in that: Applied to an automatic testing platform, the method includes: responding to a detection request from an insulation monitoring device and connecting the insulation monitoring device; Simulating a preset fault on the insulation monitoring device through an automatic testing platform, and collecting the impedance measurement value and early warning response time generated by the insulation monitoring device during the occurrence of the preset fault; Calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value; A defect of the insulation monitoring device is determined based on the early warning response time and the impedance error value.

2. The method according to claim 1, characterized in that The determining of the defect of the insulation monitoring device based on the early warning response time and the impedance error value includes: When the impedance error value is not greater than the first impedance threshold and the warning response time is greater than the time threshold, determining that a software defect occurs in the insulation monitoring device; When the impedance error value is greater than the second impedance threshold and the early warning response time is not greater than the time threshold, determining that a hardware defect occurs in the insulation monitoring device; When the impedance error value is greater than the second impedance threshold and the early warning response time is greater than the time threshold, or when the impedance error value is greater than the first impedance threshold but not greater than the second impedance threshold and the early warning response time is greater than the time threshold, it is determined that both the software and the hardware in the insulation monitoring device are defective; When the impedance error value is greater than the first impedance threshold and not greater than the second impedance threshold and the early warning response time is not greater than the time threshold, it is determined that the measurement accuracy of the insulation monitoring device is insufficient.

3. The method according to claim 2, characterized in that The method further comprises: Calculating a first difference between the impedance measurement value and a theoretical impedance value corresponding to a preset insulation monitoring device standard, and using the quotient of the first difference and the theoretical impedance value corresponding to the preset insulation monitoring device standard as a standard adaptation deviation of the impedance; Calculating a second difference between the warning response time and a theoretical response time corresponding to a preset insulation monitoring device standard, and taking the quotient of the second difference and the theoretical response time corresponding to the preset insulation monitoring device standard as a standard adaptation deviation of the response time; When both the standard adaptation deviation of the impedance and the standard adaptation deviation of the response time are greater than preset standard values, it is determined that the insulation monitoring device has a compatibility defect with the preset standard.

4. The method according to claim 1, wherein The preset faults include: ground fault, ring network fault, AC inrush fault and system capacitor fault.

5. The method according to claim 1, wherein The method further comprises: If, during multiple detections of the insulation monitoring device, it is detected that the previous defect has been resolved each time and the impedance error value detected each time is greater than the second impedance threshold, it is determined that a topological structure of the insulation monitoring device has a defect.

6. The method according to claim 3, characterized in that The method further comprises: After the insulation monitoring device is inspected, the defect location and corresponding improvement plan of the insulation monitoring device are determined based on a preset defect feature comparison library, and an inspection report of the insulation monitoring device is output; the inspection report includes the defect location, inspection time point, impedance error value, warning response time and the corresponding improvement plan.

7. A defect detection device for an insulation monitoring device, characterized in that: The device comprises: a connection module, configured to respond to a detection request from the insulation monitoring device and connect to the insulation monitoring device; an acquisition module, configured to simulate a preset fault on the insulation monitoring device through an automatic test platform, and acquire an impedance measurement value and an early warning response duration generated by the insulation monitoring device during the occurrence of the preset fault; a calculation module for calculating a difference between the impedance measurement value and a theoretical impedance value corresponding to the preset fault, and taking a quotient of the difference and the theoretical impedance value as an impedance error value; A determination module is used to determine a defect of the insulation monitoring device based on the early warning response time and the impedance error value.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images