A method for detecting faults in a substation

Abstract

The present invention relates to the technical field of detecting electrical variables, and specifically discloses a substation fault detection method. The method divides the area to which the substation belongs into regions according to a preset method, obtains environmental information of each substation sub-region, comprehensively analyzes the corresponding operation abnormality index of each operating equipment in each substation sub-region, obtains each potential fault equipment in each substation sub-region through a screening mechanism, obtains its historical fault data, the corresponding operation abnormality index and the structural information of each substation sub-region, thereby comprehensively obtaining the fault warning degree value of each potential fault equipment in each substation sub-region, and obtains the fault warning degree value comparison result, thereby determining whether to perform fault warning for each potential fault equipment in each substation sub-region, and by introducing multi-dimensional detection variables, more comprehensively reflects the equipment status, improves the accuracy of substation fault detection, can timely discover faulty equipment, and thus ensure the stable operation of the substation.

Description

Technical Field

[0001] The invention relates to the technical field of detecting electric variables, and in particular to a method for detecting faults in a transformer substation. Background Art

[0002] Substation fault detection is extremely important. Through fault detection, abnormal situations in substations can be discovered and handled in a timely manner, preventing faults from expanding and reducing the probability of accidents. At the same time, fault detection can also provide an important basis for the maintenance and management of substations, improve the utilization rate of equipment, and ensure the stable and safe operation of the power system.

[0003] For example, the invention patent with publication number CN116840579A discloses a substation fault detection method and system, including obtaining the relative ground capacitance and relative ground voltage of the substation bus; judging the neutral point voltage fault state of the substation bus according to the symmetry of the relative ground capacitance and the relative ground voltage; obtaining the frequency division resonance and high-frequency resonance in the substation; judging the balanced fault state of the three-phase voltage of the substation according to the content of the frequency division resonance and the high-frequency resonance in the substation, and realizing the comprehensive judgment of the three-phase imbalance and neutral point fault state of the substation bus by comprehensively detecting and judging the relative ground capacitance, the ground voltage and the resonance content at the same time.

[0004] For example, the invention patent with publication number CN117741305A discloses a fault detection system and detection method for a substation, which relates to the field of power testing technology. The system includes a distributed data acquisition module, which is arranged in a key area of ​​the substation, including multiple electromagnetic induction sensors for collecting real-time working status information of the substation; a data processing module, which is connected to the distributed data acquisition module through a preset anti-interference communication line, is used to receive real-time working status information and generate fault detection results based on the real-time working status information. The real-time working status information of the substation grounding network can be efficiently collected through the distributed data acquisition module, and the electromagnetic induction sensor can accurately collect the real-time working status information in the substation grounding network in a high electromagnetic interference environment, and realize communication through the preset anti-interference communication line.

[0005] Combined with the above technical solutions, it is found that in the current process of substation fault detection, the substation is directly detected in one dimension through variables. The variables here are only related to the detection dimension, which will cause a large deviation between the detection result and the actual result, so that the substation fault detection is not accurate, further increasing the difficulty of substation fault detection. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a substation fault detection method, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A substation fault detection method, comprising: S1. Dividing the area to which the substation belongs according to a preset method to obtain each substation sub-area, thereby obtaining environmental information of each substation sub-area, and analyzing the environmental impact index of each substation sub-area, while performing operation detection on each operating equipment in each substation sub-area, comprehensively analyzing the corresponding operation abnormality index of each operating equipment in each substation sub-area, and obtaining each potential fault device in each substation sub-area through a screening mechanism; S2. Obtaining the historical fault data of each potential fault device in each substation sub-area and the corresponding operation abnormality index of each potential fault device in each substation sub-area, and obtaining the structural information of each substation sub-area, thereby comprehensively analyzing the fault warning degree value of each potential fault device in each substation sub-area; S3. Comparing the fault warning degree value of each potential fault device in each substation sub-area with the fault warning degree threshold preset in the substation detection library, obtaining a fault warning degree comparison result, and based on the fault warning degree comparison result, determining whether to perform a fault warning for each potential fault device in each substation sub-area.

[0008] As a further method, the environmental impact index of each substation sub-area is analyzed, and the specific analysis process is as follows:

[0009] The environmental information of each substation sub-area includes the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period.

[0010] Therefore, the environmental impact indicators of each substation sub-area are comprehensively analyzed through the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period.

[0011] As a further method, the potential faulty equipment in each substation sub-area is obtained through a screening mechanism. Specifically, the operation abnormality index corresponding to each operating equipment in each substation sub-area is compared with the operation abnormality index threshold preset in the substation detection library. If the operation abnormality index corresponding to an operating equipment in a substation sub-area is greater than the operation abnormality index threshold, the operating equipment in the substation sub-area corresponding to the operation abnormality index is recorded as the potential faulty equipment in the substation sub-area, thereby counting the potential faulty equipment in each substation sub-area whose operation abnormality index is greater than the operation abnormality index threshold.

[0012] As a further method, the historical failure data of each potential fault equipment in each substation sub-area specifically includes the historical failure times of each potential fault equipment in each substation sub-area, the maximum duration of historical failures of each potential fault equipment in each substation sub-area, and the number of parts replaced for each potential fault equipment in each substation sub-area.

[0013] As a further method, the comprehensive analysis is performed to obtain the fault warning degree value of each potential fault device in each substation sub-area. The specific analysis process is as follows:

[0014] The structural information of each substation sub-area specifically includes the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within a fault warning detection period.

[0015] Based on the historical failure times of each potential fault equipment in each substation sub-area, the maximum duration of historical failures of each potential fault equipment in each substation sub-area, the number of parts replaced for each potential fault equipment in each substation sub-area, the corresponding operation abnormality index of each potential fault equipment in each substation sub-area, the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within the fault warning detection cycle, the fault warning degree value of each potential fault equipment in each substation sub-area is analyzed. The specific acquisition method is as follows:

[0016] ;

[0017] In the formula, Indicates the fault warning level value of the Nth potential fault device in the Rth substation sub-area, represents the historical failure count of the Nth potential fault device in the Rth substation sub-area, Indicates the maximum duration of the historical fault of the Nth potential fault device in the Rth substation sub-area, represents the number of parts replacements for the Nth potential faulty equipment in the Rth substation sub-area, represents the number of drainage leakages in the Rth substation sub-area within the fault warning detection cycle, represents the number of ventilation equipment failures in the Rth substation sub-area within the fault warning detection cycle, It represents the operation abnormality index corresponding to the Nth potential fault equipment in the Rth substation sub-area, e is a natural constant, Indicates the impact weight of the number of historical faults preset in the substation detection database, Indicates the influence weight of the maximum duration of historical faults preset in the substation detection library. Indicates the influence weight of the number of parts replacement preset in the substation detection library, Indicates the impact weight of the operation abnormality index preset in the substation detection library. Indicates the impact weight of the drainage leakage quantity preset in the substation detection library, represents the influence weight of the number of ventilation equipment failures preset in the substation detection library, R is the number of each substation sub-area, T, T is the total number of substation sub-areas, N is the number of each potential fault device, Q, Q is the total number of potential faulty devices.

[0018] As a further method, the fault warning degree value of each potential fault device in each substation sub-area is compared with the fault warning degree threshold preset in the substation detection library to obtain the fault warning degree comparison result. The specific analysis process is as follows:

[0019] The fault warning degree comparison result is specifically a first fault warning degree comparison result and a second fault warning degree comparison result.

[0020] The first fault warning degree comparison result is specifically that the fault warning degree value is less than the fault warning degree threshold.

[0021] The second fault warning level comparison result is specifically that the fault warning level value is greater than or equal to the fault warning level threshold.

[0022] As a further method, based on the comparison result of the fault warning degree, it is determined whether to perform a fault warning for each potential fault device in each substation sub-area. The specific analysis process is as follows:

[0023] If the fault warning degree result is the first fault warning degree comparison result, there is no need to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value.

[0024] If the fault warning degree result is the second fault warning degree comparison result, it is necessary to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value.

[0025] As a further method, the fault warning is performed on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value, specifically marking the potential fault equipment in the substation sub-area as a faulty equipment and notifying the fault detection personnel to perform fault detection.

[0026] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0027] (1) The present invention provides a substation fault detection method. First, the area to which the substation belongs is divided into regions according to a preset method to obtain each substation sub-area, thereby obtaining environmental information of each substation sub-area, and analyzing the environmental impact index of each substation sub-area. At the same time, operation detection is performed on each operating equipment in each substation sub-area, and the corresponding operation abnormality index of each operating equipment in each substation sub-area is comprehensively analyzed. Each potential fault device in each substation sub-area is obtained through a screening mechanism, and then the historical fault data of each potential fault device in each substation sub-area and the corresponding operation abnormality index of each potential fault device in each substation sub-area are obtained. The constant index is obtained, and the structural information of each substation sub-area is obtained at the same time, thereby comprehensively analyzing the fault warning degree value of each potential fault equipment in each substation sub-area, and comparing the fault warning degree value of each potential fault equipment in each substation sub-area with the fault warning degree threshold preset in the substation detection library to obtain the fault warning degree comparison result, and based on the fault warning degree comparison result, it is determined whether to perform fault warning on each potential fault equipment in each substation sub-area. By introducing multi-dimensional detection variables and comprehensively considering multiple operating status parameters of the equipment, it can more comprehensively reflect the actual situation of the equipment and improve the accuracy of substation fault detection.

[0028] (2) The present invention divides the area to which the substation belongs into regions according to a preset method to obtain sub-regions of each substation, thereby obtaining environmental information of each substation sub-region and analyzing the environmental impact index of each substation sub-region. At the same time, operation detection is performed on each operating equipment in each substation sub-region, and the corresponding operation abnormality index of each operating equipment in each substation sub-region is comprehensively analyzed. Through the screening mechanism, each potential faulty equipment in each substation sub-region is obtained, and the potential faulty equipment can be located more accurately, thereby improving the efficiency and accuracy of fault detection.

[0029] (3) The present invention obtains the historical fault data of each potential fault equipment in each substation sub-area and the corresponding operation abnormality index of each potential fault equipment in each substation sub-area, and simultaneously obtains the structural information of each substation sub-area, thereby comprehensively analyzing the fault warning degree value of each potential fault equipment in each substation sub-area, which helps to timely discover potential fault equipment and avoid losses caused by equipment suspension through accurate and comprehensive inspection of the equipment.

[0030] (4) The present invention compares the fault warning level value of each potential fault device in each substation sub-area with the fault warning level threshold preset in the substation detection library to obtain a fault warning level comparison result, and based on the fault warning level comparison result, determines whether to perform a fault warning for each potential fault device in each substation sub-area. This can accurately and timely discover faulty equipment and avoid the expansion of faults, thereby ensuring the stable operation of the substation. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0032] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0034] Reference Figure 1 As shown, the present invention provides a substation fault detection method, comprising: S1. Dividing the area to which the substation belongs into regions according to a preset method to obtain each substation sub-area, thereby obtaining environmental information of each substation sub-area, and analyzing the environmental impact index of each substation sub-area, and at the same time performing operation detection on each operating equipment in each substation sub-area, comprehensively analyzing the corresponding operation abnormality index of each operating equipment in each substation sub-area, and obtaining each potential faulty equipment in each substation sub-area through a screening mechanism.

[0035] In this embodiment, the area to which the substation belongs is divided according to a preset method to obtain substation sub-areas, which specifically refers to equal area division according to the area. For example, if the area of ​​the substation area is 100 square meters, it is divided into four substation sub-areas with 25 square meters per substation sub-area.

[0036] Specifically, the environmental impact index of each substation sub-area is analyzed, and the specific analysis process is as follows:

[0037] The environmental information of each substation sub-area includes the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period.

[0038] It should be explained that the above-mentioned operation detection period specifically refers to the time period from the start of the operation detection of the substation to the end of the detection, which is recorded as the operation detection period. The specific duration will vary depending on factors such as the scale of the substation and the location of the substation. The average temperature of each substation sub-area during the operation detection period can be obtained by using a high-sensitivity temperature sensor deployed in each substation sub-area, wherein the temperature sensor can monitor multiple temperature values ​​during the operation detection period in real time, and obtain the average temperature through average value calculation processing; the average humidity of each substation sub-area during the operation detection period can be obtained by using a high-sensitivity humidity sensor deployed in each substation sub-area, wherein the humidity sensor can monitor the temperature of the substation in real time during the operation detection period. Multiple humidity values ​​are obtained by averaging operations to obtain the average humidity; the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period can be obtained by using a high-sensitivity electromagnetic field intensity meter deployed in each substation sub-area, wherein the electromagnetic field intensity meter can monitor multiple electromagnetic interference intensity values ​​during the operation detection period in real time, and screen out the maximum value as the maximum electromagnetic interference signal strength by comparing the values; the maximum dust concentration of each substation sub-area during the operation detection period can be obtained by using a high-sensitivity dust concentration monitor deployed in each substation sub-area, wherein the dust concentration monitor can monitor multiple dust concentration values ​​during the operation detection period in real time, and screen out the maximum value as the maximum dust concentration by comparing the values.

[0039] Therefore, the environmental impact index of each substation sub-area is comprehensively analyzed through the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period. The specific analysis method is as follows:

[0040] ;

[0041] In the formula, It represents the average temperature of the R-th substation sub-area during the operation detection period, specifically refers to the average value of the temperature of the R-th substation sub-area during the operation detection period.

[0042] It indicates the average temperature reference value preset in the substation detection library, specifically the optimal average temperature set during the operation of the substation equipment.

[0043] It represents the average humidity of the Rth substation sub-area during the operation detection period, specifically refers to the average value of the humidity of the Rth substation sub-area during the operation detection period.

[0044] It indicates the average humidity reference value preset in the substation detection library, specifically the optimal average humidity set during the operation of the substation equipment.

[0045] It represents the maximum electromagnetic interference signal strength of the R-th substation sub-area during the operation detection period, specifically refers to the maximum value of the electromagnetic interference signal strength measured and recorded by the electromagnetic field intensity meter in the R-th substation sub-area during the operation detection period.

[0046] It indicates the maximum dust concentration of the Rth substation sub-area during the operation detection period, specifically, the maximum value of the dust concentration monitored and recorded in real time by the dust concentration monitor in the Rth substation sub-area during the operation detection period. This maximum value represents the highest dust pollution level that may exist in the Rth substation sub-area during the operation detection period.

[0047] It represents the average temperature influence weight preset in the substation detection library, and represents the numerical value of the influence degree of the average temperature preset in the substation detection library on the environmental impact index. When used, the average temperature influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a pre-set mapping relationship. For example, the average temperature and the average temperature influence weight preset in the substation detection library form a mapping set, and the real-time average temperature is input into the mapping set to obtain the average temperature influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0048] It represents the average humidity impact weight preset in the substation detection library, and represents the numerical value of the influence degree of the average humidity preset in the substation detection library on the environmental impact index. When used, the average humidity impact weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the average humidity and the average humidity impact weight preset in the substation detection library form a mapping set, and the real-time average humidity is input into the mapping set to obtain the average humidity impact weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0049] It represents the maximum electromagnetic interference signal strength influence weight preset in the substation detection library, and represents the numerical value of the influence degree of the maximum electromagnetic interference signal strength preset in the substation detection library on the environmental impact index. When used, the maximum electromagnetic interference signal strength influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the maximum electromagnetic interference signal strength and the maximum electromagnetic interference signal strength influence weight preset in the substation detection library form a mapping set, and the real-time maximum electromagnetic interference signal strength is input into the mapping set to obtain the maximum electromagnetic interference signal strength influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0050] It represents the influence weight of the maximum dust concentration preset in the substation detection library, and represents the numerical value of the influence degree of the maximum dust concentration preset in the substation detection library on the environmental impact index. When used, the influence weight of the maximum dust concentration can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the maximum dust concentration and the influence weight of the maximum dust concentration preset in the substation detection library form a mapping set, and the real-time maximum dust concentration is input into the mapping set to obtain the influence weight of the maximum dust concentration. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0051] R is the number of each substation sub-area, T, T is the total number of substation sub-areas.

[0052] It represents the environmental impact index of the Rth substation sub-area. During the operation detection process, if the temperature is too high, that is, it deviates from the temperature reference value, the humidity value in the air will decrease. If the humidity deviates from the humidity reference value, the dust will be more easily suspended in the air, resulting in an increase in dust concentration. The conductive substances in the dust can form a conductive path, which will enhance the electromagnetic interference signal strength, thereby increasing the environmental impact index. If the temperature is too low, that is, it deviates from the temperature reference value, the humidity value in the air will increase. If the humidity deviates from the humidity reference value, the moisture in the air will adhere to the dust particles, resulting in an increase in dust conductivity, which will enhance the electromagnetic interference signal strength, thereby increasing the environmental impact index.

[0053] Furthermore, the operation detection is performed on each operating equipment in each substation sub-area, thereby obtaining corresponding operation detection information of each operating equipment in each substation sub-area through the operation detection, specifically including the average operating temperature, operating vibration frequency and maximum operating noise intensity of each operating equipment in each substation sub-area during the operation detection period.

[0054] It should be explained that the average operating temperature of each operating equipment in the above-mentioned substation sub-area during the operation detection period can be obtained by using a high-sensitivity temperature sensor installed inside each operating equipment, wherein the temperature sensor can monitor multiple temperature values ​​during the operation detection period in real time, and obtain the average operating temperature through average value calculation processing; the operating vibration frequency can be obtained by a high-sensitivity vibration sensor installed inside each operating equipment; the maximum intensity of the operating noise can be obtained by a high-sensitivity noise sensor installed inside each operating equipment, wherein the noise sensor can monitor multiple operating noise intensity values ​​during the operation detection period in real time, and screen out the maximum value as the maximum intensity of the operating noise through numerical value comparison.

[0055] Specifically, the comprehensive analysis is performed to obtain the corresponding abnormal operation index of each operating equipment in each substation sub-area, and the specific analysis method is as follows:

[0056] The operation abnormality index corresponding to each operating equipment in each substation sub-area is comprehensively analyzed through the average operating temperature, operating vibration frequency, maximum operating noise intensity of each operating equipment in each substation sub-area during the operation detection period and the environmental impact index of each substation sub-area. The acquisition method is as follows:

[0057] ;

[0058] In the formula, It represents the environmental impact index of the Rth substation sub-area, which is specifically the value of the environmental impact index of each substation sub-area obtained by comprehensive analysis of the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period.

[0059] It represents the average operating temperature of the Dth operating equipment in the Rth substation sub-area during the operation detection period, specifically refers to the average operating temperature of the Dth operating equipment in the Rth substation sub-area during the operation detection period.

[0060] It represents the operating vibration frequency of the Dth operating equipment in the Rth substation sub-area during the operation detection period, specifically refers to the number of vibrations of the operating equipment per unit time monitored and recorded in real time by the vibration sensor installed on the Dth operating equipment in the Rth substation sub-area during the operation detection period.

[0061] It indicates the maximum intensity of the operating noise of the D-th operating equipment in the R-th substation sub-area during the operation detection period, specifically refers to the maximum value of the noise level generated by the D-th operating equipment in the R-th substation sub-area during the operation detection period.

[0062] e is a natural constant, It represents the influence weight of the operating average temperature preset in the substation detection library, and represents the numerical value of the influence degree of the operating average temperature preset in the substation detection library on the operation abnormality index. When used, the operating average temperature influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the operating average temperature and the operating average temperature influence weight preset in the substation detection library form a mapping set, and the real-time operating average temperature is input into the mapping set to obtain the operating average temperature influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0063] It represents the influence weight of the operation vibration frequency preset in the substation detection library, and represents the numerical value of the influence degree of the operation vibration frequency preset in the substation detection library on the operation abnormality index. When used, the operation vibration frequency influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the operation vibration frequency and the operation vibration frequency influence weight preset in the substation detection library form a mapping set, and the real-time operation vibration frequency is input into the mapping set to obtain the operation vibration frequency influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0064] It represents the influence weight of the maximum intensity of operating noise preset by the substation detection library, and represents the numerical value of the influence degree of the maximum intensity of operating noise preset by the substation detection library on the operation abnormality index. When used, the influence weight of the maximum intensity of operating noise can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the maximum intensity of operating noise and the influence weight of the maximum intensity of operating noise preset by the substation detection library form a mapping set, and the real-time maximum intensity of operating noise is input into the mapping set to obtain the influence weight of the maximum intensity of operating noise. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0065] It represents the influence weight of the environmental impact indicator preset in the substation detection library, and represents the numerical value of the influence degree of the environmental impact indicator preset in the substation detection library on the operation abnormality index. When used, the environmental impact indicator influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a pre-set mapping relationship. For example, the environmental impact indicator and the environmental impact indicator influence weight preset in the substation detection library form a mapping set, and the real-time environmental impact indicator is input into the mapping set to obtain the environmental impact indicator influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0066] R is the number of each substation sub-area, T, T is the total number of substation sub-areas, D is the number of each operating equipment, M, M is the total number of running devices.

[0067] It represents the operation abnormality index corresponding to the Dth operating equipment in the Rth substation sub-area. During the operation of the equipment, the influencing factors in the environmental impact index will affect the operating status of the equipment. For example, a high temperature environment may cause the operating temperature of the equipment to rise, and an increase in the electromagnetic interference intensity may increase the operating vibration frequency and the maximum intensity of the operating noise of the equipment. When the operating temperature of the equipment is too high, its internal mechanical components may increase friction due to thermal expansion and contraction, resulting in an increase in the operating vibration frequency. Vibration will cause the interactions between components to be more frequent and intense, which will generate greater noise and increase the maximum intensity of the operating noise, thereby increasing the corresponding operation abnormality index of the operating equipment.

[0068] Furthermore, the potential faulty equipment in each substation sub-area is obtained through the screening mechanism. Specifically, the operation abnormality index corresponding to each operating equipment in each substation sub-area is compared with the operation abnormality index threshold preset in the substation detection library. If the operation abnormality index corresponding to an operating equipment in a substation sub-area is greater than the operation abnormality index threshold, the operating equipment in the substation sub-area corresponding to the operation abnormality index is recorded as the potential faulty equipment in the substation sub-area. Thus, the potential faulty equipment in each substation sub-area whose operation abnormality index is greater than the operation abnormality index threshold is statistically analyzed.

[0069] It should be explained that the above-mentioned operation abnormality index threshold represents the critical value used to judge whether the operation abnormality index reaches the fault standard during the operation detection process, and is used to quantitatively evaluate the degree of abnormality of substation equipment during operation, and help the screening mechanism determine whether it is necessary to record a certain operating equipment as a potential fault equipment; if the operation abnormality index corresponding to a certain operating equipment in a certain substation sub-area is greater than the operation abnormality index threshold, it means that the degree of abnormality of the substation equipment in the operation process is too high, and there will be hidden fault problems, and the operating equipment needs to be recorded as a potential fault equipment; if the operation abnormality index corresponding to a certain operating equipment in a certain substation sub-area is less than or equal to the operation abnormality index threshold, it means that the degree of abnormality of the substation equipment in the operation process is within a safe range, there is no hidden fault problem, and there is no need to record the operating equipment as a potential fault equipment.

[0070] S2. Obtain the historical fault data of each potential fault device in each substation sub-area and the corresponding operation abnormality index of each potential fault device in each substation sub-area, and simultaneously obtain the structural information of each substation sub-area, thereby comprehensively analyzing the fault warning degree value of each potential fault device in each substation sub-area.

[0071] It should be explained that the operation abnormality index corresponding to each potential faulty equipment in each substation sub-area mentioned above is obtained based on the analysis of the operation abnormality index corresponding to each operating equipment in each substation sub-area and the potential faulty equipment in each substation sub-area obtained through a screening mechanism, thereby comprehensively obtaining the operation abnormality index corresponding to each potential faulty equipment in each substation sub-area.

[0072] Specifically, the historical failure data of each potential faulty equipment in each substation sub-area includes the historical failure times of each potential faulty equipment in each substation sub-area, the maximum duration of historical failures of each potential faulty equipment in each substation sub-area, and the number of parts replaced for each potential faulty equipment in each substation sub-area.

[0073] It should be explained that the historical number of failures of each potential faulty equipment in each substation sub-area, the historical maximum duration of failures of each potential faulty equipment in each substation sub-area, and the number of parts replaced for each potential faulty equipment in each substation sub-area can all be obtained through the equipment failure record report.

[0074] Furthermore, the comprehensive analysis is performed to obtain the fault warning degree value of each potential fault device in each substation sub-area. The specific analysis process is as follows:

[0075] The structural information of each substation sub-area specifically includes the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within a fault warning detection period.

[0076] It should be explained that the above-mentioned fault warning detection cycle specifically refers to the time period from the start of fault warning detection to the end of detection, which is recorded as the fault warning detection cycle.

[0077] The method for obtaining the drainage leakage quantity of each substation sub-area within the fault warning detection cycle is as follows:

[0078] The substation itself carries a drainage management system, so several drainage detection location points of the substation can be obtained through the drainage management system of the substation. Since the substation is divided into substation sub-areas according to a preset method, several drainage detection location points of each substation sub-area are obtained through regional comparison. For example, the preset method is to divide the area into equal areas according to the area. Then, if the substation area is 100 square meters, it is divided into four substation sub-areas with an equal area of ​​25 square meters per substation sub-area. Then, through regional comparison, it is obtained that the first substation sub-area has 5 drainage detection location points and the second substation sub-area has 10 drainage detection location points. According to the drainage leakage information recorded in the drainage management system, it is obtained that multiple drainage detection location points of the substation are leaking, which is recorded as the number of drainage leakages in each substation sub-area within the fault warning detection cycle.

[0079] The method for obtaining the number of ventilation equipment failures in each of the above substation sub-areas within the fault warning detection cycle is as follows:

[0080] The substation itself is equipped with an exhaust system, so several ventilation equipment detection points of each substation sub-area can be obtained through the exhaust system of the substation. Since the substation is divided into each substation sub-area according to a preset method, several ventilation equipment of each substation sub-area can be obtained through regional comparison. For example, the preset method is to divide the area into equal areas according to the area of ​​the area. If the substation area is 100 square meters, it is divided into four substation sub-areas with an equal area of ​​25 square meters per substation sub-area. Then, through regional comparison, it is concluded that there are 8 ventilation equipment in the first substation sub-area and 12 ventilation equipment in the second substation sub-area. According to the exhaust fan fault information recorded in the exhaust system, it is concluded that multiple ventilation equipment of the substation is faulty, which is recorded as the number of ventilation equipment failures in each substation sub-area within the fault warning detection cycle.

[0081] It needs to be explained that the above-mentioned ventilation equipment is mainly used in the substation to maintain the air circulation of the substation, discharge the heat emitted from the substation, reduce the equipment temperature, and ensure the normal operation of the equipment; and the above-mentioned operating equipment refers to the equipment used for power transmission, distribution, conversion, monitoring, measurement, adjustment, protection, switching and stopping in the substation, mainly including transformers, circuit breakers, disconnectors, voltage transformers, current transformers, capacitors, reactors, etc.

[0082] Based on the historical failure times of each potential fault equipment in each substation sub-area, the maximum duration of historical failures of each potential fault equipment in each substation sub-area, the number of parts replaced for each potential fault equipment in each substation sub-area, the corresponding operation abnormality index of each potential fault equipment in each substation sub-area, the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within the fault warning detection cycle, the fault warning degree value of each potential fault equipment in each substation sub-area is analyzed. The specific acquisition method is as follows:

[0083] ;

[0084] In the formula, It represents the number of historical failures of the Nth potential faulty device in the Rth substation sub-area, specifically refers to the number of failures recorded in the past for the Nth potential faulty device in the Rth substation sub-area.

[0085] It indicates the maximum duration of the historical fault of the Nth potential fault device in the Rth substation sub-area, specifically refers to the longest duration of the fault recorded in the past for the Nth potential fault device in the Rth substation sub-area.

[0086] It indicates the number of parts replaced for the Nth potential faulty equipment in the Rth substation sub-area, specifically refers to the number of parts that have been replaced for the Nth potential faulty equipment in the Rth substation sub-area during the maintenance or repair process.

[0087] It indicates the number of drainage leakages in the R-th substation sub-area within the fault warning detection cycle, specifically, the number of drainage detection location points where faults occur in the R-th substation sub-area within the fault warning detection cycle.

[0088] It indicates the number of ventilation equipment failures in the R-th substation sub-area within the fault warning detection cycle, specifically, the total number of ventilation equipment failures in the R-th substation sub-area within the fault warning detection cycle.

[0089] It represents the operation abnormality index corresponding to the Nth potential faulty equipment in the Rth substation sub-area. Specifically, it is the operation abnormality index corresponding to each potential faulty equipment in each substation sub-area obtained by comprehensive analysis of the average operation temperature, operation vibration frequency, maximum operation noise intensity of each operating equipment in each substation sub-area during the operation detection period and the environmental impact index of each substation sub-area.

[0090] e is a natural constant, It represents the influence weight of the historical fault times preset in the substation detection library, and represents the numerical value of the influence degree of the historical fault times preset in the substation detection library on the fault warning degree value. When used, the influence weight of the historical fault times can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the historical fault times and the influence weight of the historical fault times preset in the substation detection library form a mapping set, and the real-time historical fault times are input into the mapping set to obtain the influence weight of the historical fault times. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0091] It represents the influence weight of the maximum duration of historical faults preset in the substation detection library, and represents the numerical value of the influence degree of the maximum duration of historical faults preset in the substation detection library on the fault warning degree value. When used, the influence weight of the maximum duration of historical faults can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the maximum duration of historical faults and the influence weight of the maximum duration of historical faults preset in the substation detection library form a mapping set, and the real-time maximum duration of historical faults is input into the mapping set to obtain the influence weight of the maximum duration of historical faults. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0092] It represents the influence weight of the number of parts replacement preset in the substation detection library, and represents the numerical value of the influence degree of the number of parts replacement preset in the substation detection library on the fault warning degree value. When used, the influence weight of the number of parts replacement can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the number of parts replacement and the influence weight of the number of parts replacement preset in the substation detection library form a mapping set, and the real-time number of parts replacement is input into the mapping set to obtain the influence weight of the number of parts replacement. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0093] It represents the influence weight of the operation abnormality index preset in the substation detection library, and represents the numerical value of the influence degree of the operation abnormality index preset in the substation detection library on the fault warning degree value. When used, the operation abnormality index influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the operation abnormality index and the operation abnormality index influence weight preset in the substation detection library form a mapping set, and the real-time operation abnormality index is input into the mapping set to obtain the operation abnormality index influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0094] It represents the influence weight of the drainage leakage quantity preset in the substation detection library, and represents the numerical value of the influence degree of the drainage leakage quantity preset in the substation detection library on the fault warning degree value. When used, the drainage leakage quantity influence weight can be directly obtained from the substation detection library, and the corresponding relationship can be a preset mapping relationship. For example, the drainage leakage quantity and the drainage leakage quantity influence weight preset in the substation detection library form a mapping set, and the real-time drainage leakage quantity is input into the mapping set to obtain the drainage leakage quantity influence weight. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0095] It represents the influence weight of the number of ventilation equipment failures preset in the substation detection library, and represents the numerical value of the influence degree of the number of ventilation equipment failures preset in the substation detection library on the fault warning degree value. When used, the influence weight of the number of ventilation equipment failures can be directly obtained from the substation detection library, and the corresponding relationship can be a pre-set mapping relationship. For example, the number of ventilation equipment failures and the influence weight of the number of ventilation equipment failures preset in the substation detection library form a mapping set, and the real-time number of ventilation equipment failures is input into the mapping set to obtain the influence weight of the number of ventilation equipment failures. The mapping relationship can be one-to-one or many-to-one. In this example, its value range is [0, 1].

[0096] R is the number of each substation sub-area, T, T is the total number of substation sub-areas, N is the number of each potential fault device, Q, Q is the total number of potential faulty devices.

[0097] It represents the fault warning degree value of the Nth potential fault equipment in the Rth substation sub-area. During the fault warning detection process, the more historical faults of the potential fault equipment, the more unstable the equipment is, which directly leads to an increase in the number of possible parts replacements during the fault repair period, and the maximum duration of historical faults may be longer, further reducing the operating stability of the equipment, that is, it may increase the operating vibration frequency and the maximum intensity of the operating noise, thereby increasing the corresponding operating abnormality index of the potential fault equipment, and ultimately increasing the fault warning degree value of the potential fault equipment; the more drainage leakage and ventilation equipment failures, the more equipment failures will occur, thereby increasing the corresponding operating abnormality index of the potential fault equipment, and ultimately causing the fault warning degree to increase.

[0098] S3. Compare the fault warning degree value of each potential fault device in each substation sub-area with the fault warning degree threshold preset in the substation detection library to obtain a fault warning degree comparison result, and based on the fault warning degree comparison result, determine whether to issue a fault warning for each potential fault device in each substation sub-area.

[0099] Specifically, the fault warning degree value of each potential fault device in each substation sub-area is compared with the fault warning degree threshold preset in the substation detection library to obtain the fault warning degree comparison result. The specific analysis process is as follows:

[0100] The fault warning degree comparison result is specifically a first fault warning degree comparison result and a second fault warning degree comparison result.

[0101] The first fault warning level comparison result is specifically that the fault warning level value is less than the fault warning level threshold, wherein the fault warning level threshold represents the critical value used to determine whether the fault warning level value reaches the fault warning standard during the fault warning detection process, and is used to measure the possibility and severity of failure of substation equipment during operation, and help determine whether potential fault equipment requires fault warning; the above-mentioned fault warning level value is less than the fault warning level threshold, indicating that the potential fault equipment does not have a fault or the fault that occurs is minor, and there is no need to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning level value.

[0102] The second fault warning level comparison result is specifically that the fault warning level value is greater than or equal to the fault warning level threshold.

[0103] Furthermore, based on the comparison result of the fault warning degree, it is determined whether to perform a fault warning for each potential fault device in each substation sub-area. The specific analysis process is as follows:

[0104] If the fault warning degree result is the first fault warning degree comparison result, there is no need to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value.

[0105] If the fault warning degree result is the second fault warning degree comparison result, it is necessary to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value.

[0106] Specifically, the fault warning is performed on the potential faulty equipment in the substation sub-area corresponding to the fault warning degree value, specifically marking the potential faulty equipment in the substation sub-area as a faulty equipment, and notifying a fault detection personnel to perform a fault detection.

[0107] It needs to be explained that the above-mentioned fault warning for the potential fault equipment in the substation sub-area corresponding to the fault warning degree value is specifically performed by performing difference processing on the fault warning degree value of each potential fault equipment in each substation sub-area and the fault warning degree threshold preset in the substation detection library, thereby obtaining the fault warning degree deviation value, and matching it with the fault warning data set corresponding to the fault warning degree deviation value interval preset in the substation detection library, and finally matching to obtain the fault warning data set to which the fault warning degree value belongs, and the fault detection personnel perform fault warning operations on the faulty equipment through the fault warning data set.

[0108] The above matching obtains the fault warning data set to which the fault warning degree value belongs. The specific matching process is as follows:

[0109] The above fault warning degree deviation values ​​and the corresponding fault warning data sets are developed by authoritative fault warning institutions or standardization organizations through data collection, collation, and encryption. Each fault warning degree deviation value is carefully divided, and the corresponding fault warning data set is designed for each fault warning degree deviation value range based on substation safety standards, threat and risk analysis, business needs, and compliance requirements.

[0110] For example, if the fault warning degree deviation value in this example is 6, it belongs to the fault warning degree deviation value interval corresponding to [3, 7]. At the same time, the fault warning data set corresponding to the fault warning degree deviation value interval of the fault warning data set [3, 7] preset in the substation detection library includes checking whether the faulty equipment can dissipate heat normally, checking whether the relevant components of the faulty equipment (such as the oil tank) are consumed normally, and checking whether the surface of the faulty equipment is severely worn.

[0111] It should be explained that the potential faulty equipment in the above-mentioned substation sub-area is marked as a faulty equipment, and the fault detection personnel are notified to perform fault detection. The purpose of providing fault warning for the potential faulty equipment is to ensure the safe and stable operation of all equipment in the substation, and ultimately ensure that the fault warning degree value evaluated after the fault warning is completed is less than the fault warning degree threshold.

[0112] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A substation fault detection method, characterized in that: include: S1. Divide the area to which the substation belongs according to a preset method to obtain each substation sub-area, thereby obtaining the environmental information of each substation sub-area, and analyzing the environmental impact index of each substation sub-area. At the same time, perform operation detection on each operating equipment in each substation sub-area, comprehensively analyze the corresponding operation abnormality index of each operating equipment in each substation sub-area, and obtain each potential fault equipment in each substation sub-area through a screening mechanism; S2. Obtain the historical fault data of each potential fault device in each substation sub-area and the corresponding operation abnormality index of each potential fault device in each substation sub-area, and obtain the structural information of each substation sub-area, thereby comprehensively analyzing the fault warning degree value of each potential fault device in each substation sub-area; S3. Compare the fault warning level value of each potential fault device in each substation sub-area with the fault warning level threshold preset in the substation detection library to obtain a fault warning level comparison result, and based on the fault warning level comparison result, determine whether to perform a fault warning on each potential fault device in each substation sub-area; The environmental impact indicators of each substation sub-area are analyzed, and the specific analysis process is as follows: The environmental information of each substation sub-area includes the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period; Thus, the environmental impact index of each substation sub-area is comprehensively analyzed through the average temperature of each substation sub-area during the operation detection period, the average humidity of each substation sub-area during the operation detection period, the maximum electromagnetic interference signal strength of each substation sub-area during the operation detection period, and the maximum dust concentration of each substation sub-area during the operation detection period; The operation detection is performed on each operating equipment in each substation sub-area, thereby obtaining the corresponding operation detection information of each operating equipment in each substation sub-area through the operation detection, specifically including the average operation temperature, operation vibration frequency and maximum operation noise intensity of each operating equipment in each substation sub-area during the operation detection period; The comprehensive analysis is performed to obtain the corresponding abnormal operation index of each operating equipment in each substation sub-area. The specific analysis method is as follows: The corresponding operation abnormality index of each operating equipment in each substation sub-area is comprehensively analyzed through the average operation temperature, operation vibration frequency, maximum operation noise intensity of each operating equipment in each substation sub-area during the operation detection period and the environmental impact index of each substation sub-area; The historical fault data of each potential fault device in each substation sub-area specifically includes the number of historical faults of each potential fault device in each substation sub-area, the maximum duration of historical faults of each potential fault device in each substation sub-area, and the number of parts replaced for each potential fault device in each substation sub-area; The comprehensive analysis is performed to obtain the fault warning degree value of each potential fault device in each substation sub-area. The specific analysis process is as follows: The structural information of each substation sub-area specifically includes the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within a fault warning detection cycle; Based on the historical failure times of each potential fault equipment in each substation sub-area, the maximum duration of historical failures of each potential fault equipment in each substation sub-area, the number of parts replaced for each potential fault equipment in each substation sub-area, the corresponding operation abnormality index of each potential fault equipment in each substation sub-area, the number of drainage leakages and the number of ventilation equipment failures in each substation sub-area within the fault warning detection cycle, the fault warning degree value of each potential fault equipment in each substation sub-area is analyzed. The specific acquisition method is as follows: ; In the formula, Indicates the fault warning level value of the Nth potential fault device in the Rth substation sub-area, represents the historical failure times of the Nth potential faulty device in the Rth substation sub-area, Indicates the maximum duration of the historical fault of the Nth potential fault device in the Rth substation sub-area, represents the number of parts replacements for the Nth potential faulty equipment in the Rth substation sub-area, represents the number of drainage leakages in the Rth substation sub-area within the fault warning detection cycle, represents the number of ventilation equipment failures in the Rth substation sub-area within the fault warning detection cycle, It represents the operation abnormality index corresponding to the Nth potential fault equipment in the Rth substation sub-area, e is a natural constant, Indicates the impact weight of the number of historical faults preset in the substation detection database, Indicates the influence weight of the maximum duration of historical faults preset in the substation detection library. Indicates the influence weight of the number of parts replacement preset in the substation detection library, Indicates the impact weight of the operation abnormality index preset in the substation detection library. Indicates the impact weight of the drainage leakage quantity preset in the substation detection library, represents the influence weight of the number of ventilation equipment failures preset in the substation detection library, R is the number of each substation sub-area, T, T is the total number of substation sub-areas, N is the number of each potential fault device, Q, Q is the total number of potential faulty devices; The environmental impact indicators of each substation sub-area are analyzed, and the specific analysis process is as follows: ； In the formula, represents the average temperature of the Rth substation sub-area during the operation detection period, Indicates the average temperature reference value preset in the substation detection library. represents the average humidity of the Rth substation sub-area during the operation detection period, Indicates the average humidity reference value preset in the substation detection library. represents the maximum electromagnetic interference signal strength of the Rth substation sub-area during the operation detection period, It represents the maximum dust concentration of the Rth substation sub-area during the operation detection period. Indicates the average temperature impact weight preset in the substation detection library, Indicates the average humidity impact weight preset in the substation detection library. Indicates the maximum electromagnetic interference signal strength influence weight preset by the substation detection library. It indicates the maximum dust concentration impact weight preset by the substation detection library. R is the number of each substation sub-area. T, T is the total number of substation sub-areas, represents the environmental impact index of the Rth substation sub-area; The comprehensive analysis is performed to obtain the corresponding abnormal operation index of each operating equipment in each substation sub-area. The specific analysis method is as follows: ； In the formula, represents the environmental impact index of the Rth substation sub-area, represents the average operating temperature of the Dth operating equipment in the Rth substation sub-area during the operation detection period, It represents the operating vibration frequency of the Dth operating equipment in the Rth substation sub-area during the operation detection period, represents the maximum intensity of the operating noise of the Dth operating equipment in the Rth substation sub-area during the operation detection period, e is a natural constant, Indicates the influence weight of the average operating temperature preset in the substation detection library. Indicates the operating vibration frequency influence weight preset in the substation detection library. Indicates the maximum intensity impact weight of the operating noise preset in the substation detection library. It represents the impact weight of the environmental impact index preset in the substation detection library, R is the number of each substation sub-area, T, T is the total number of substation sub-areas, D is the number of each operating equipment, M, M is the total number of running devices, It indicates the operation abnormality index corresponding to the D-th operating equipment in the R-th substation sub-area.

2. A substation fault detection method according to claim 1, characterized in that: The potential faulty equipment in each substation sub-area is obtained through the screening mechanism, specifically, the operation abnormality index corresponding to each operating equipment in each substation sub-area is compared with the operation abnormality index threshold preset in the substation detection library. If the operation abnormality index corresponding to a certain operating equipment in a certain substation sub-area is greater than the operation abnormality index threshold, the operating equipment in the substation sub-area corresponding to the operation abnormality index is recorded as the potential faulty equipment in the substation sub-area, thereby counting the potential faulty equipment in each substation sub-area whose operation abnormality index is greater than the operation abnormality index threshold.

3. A substation fault detection method according to claim 1, characterized in that: The fault warning degree value of each potential fault device in each substation sub-area is compared with the fault warning degree threshold preset in the substation detection library to obtain the fault warning degree comparison result. The specific analysis process is as follows: The fault warning degree comparison result is specifically a first fault warning degree comparison result and a second fault warning degree comparison result; The first fault warning degree comparison result is specifically that the fault warning degree value is less than the fault warning degree threshold; The second fault warning level comparison result is specifically that the fault warning level value is greater than or equal to the fault warning level threshold.

4. A substation fault detection method according to claim 3, characterized in that: Based on the comparison result of the fault warning degree, it is determined whether to issue a fault warning to each potential fault device in each substation sub-area. The specific analysis process is as follows: If the fault warning degree result is the first fault warning degree comparison result, there is no need to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value; If the fault warning degree result is the second fault warning degree comparison result, it is necessary to perform a fault warning on the potential fault equipment in the substation sub-area corresponding to the fault warning degree value.

5. A substation fault detection method according to claim 4, characterized in that: The fault warning is performed on the potential faulty equipment in the substation sub-area corresponding to the fault warning degree value, specifically marking the potential faulty equipment in the substation sub-area as a faulty equipment and notifying a fault detection personnel to perform a fault detection.

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