An intelligent power distribution room operation monitoring system and method

Abstract

The present invention discloses an intelligent distribution room operation supervision system and method, which relates to the technical field of distribution equipment, including a standard operating condition database, a distribution modeling unit, an operation supervision unit, an abnormality judgment unit and a patrol and positioning unit; the present invention establishes a distribution room line operation model and marks supervision nodes, generates abnormal fluctuation values ​​according to actual operating condition data and standard data packets, judges that the distribution room equipment has an operating abnormality according to a preset fluctuation threshold, and then obtains the position coordinates of the abnormal node, analyzes and compares the standard data packet to generate a difference value to obtain the operating abnormality object, finds patrol personnel near the abnormal node and sends a maintenance notice, or finds a maintenance station near the abnormal node and sends a maintenance notice, so as to realize real-time emergency repair and avoid further losses caused by distribution failures.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution equipment, and in particular to an intelligent power distribution room operation monitoring system and method. Background Art

[0002] The normal operation of electrical equipment in the distribution room is an important guarantee for the production and operation of enterprises. Failure of electrical equipment in the distribution room will bring immeasurable harm to electricity users and residents. With the continuous progress and development of science and technology, the distribution room has become an indispensable equipment in many industries. The normal operation of the distribution room is the guarantee for the normal development of various work, especially the dangerous environmental factors such as high temperature, humidity, water immersion and excessive concentration of flammable gas in the distribution room. Therefore, comprehensive supervision of the distribution room is particularly important.

[0003] The management of distribution rooms has always been one of the weak links in the reliability of power supply system operation management. Some distribution room switches trip and overheating affect equipment operation, water flooding in distribution rooms causes equipment damage, and equipment in distribution rooms is stolen. These failures are easy to burn equipment and affect the normal power consumption of users, but these failures are often ignored. However, due to the lack of detection methods in the low-voltage distribution network for many years, the staff usually measure the distribution devices and conduct inspections one by one on a few typical days every year or every season. As a result, it is time-consuming and labor-intensive, and can neither reflect the real situation in time nor solve practical problems in time.

[0004] There are two main ways to supervise traditional distribution rooms: the first is to set up shifts and conduct manual inspections in 24-hour shifts; the second is to install various sensors in the distribution room to detect various environmental parameters of the distribution room, but it has not really achieved intelligence and requires supervisors to conduct real-time monitoring in the background. The above two supervision methods cannot completely solve the existing problems. First, distribution room supervision has high technical requirements for personnel, requiring supervisors to be able to check and solve problems; secondly, manual inspections take up a lot of manpower, resulting in a waste of human resources. At the same time, there are many human factors in the supervision results, which can easily lead to subjective judgment errors. The use of the above two supervision methods may cause more serious losses and impacts. These two supervision methods do not have good stability and reliability, and cannot effectively improve work efficiency, wasting a lot of human resources;

[0005] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0006] The purpose of the present invention is to establish a distribution room line operation model and mark the supervision nodes, generate abnormal fluctuation values ​​according to the actual working condition data and the standard data packet, judge the operation abnormality of the distribution room equipment according to the preset fluctuation threshold, and then obtain the position coordinates of the abnormal nodes, and analyze and compare with the standard data packet to generate difference values ​​to obtain the operation abnormality object.

[0007] In order to achieve the above-mentioned object, the present invention adopts the following technical scheme: an intelligent power distribution room operation supervision system, including a standard working condition database, a power distribution modeling unit, an operation supervision unit, an abnormality judgment unit and an inspection and positioning unit;

[0008] The power distribution modeling unit is used to obtain the design size and line distribution data of the power distribution room to establish the power distribution room line operation model, and mark the supervision nodes according to the power distribution room line operation model, obtain the coordinates of each supervision node, and send the coordinate information of each supervision node to the inspection and positioning unit for storage;

[0009] The standard operating condition database includes a data storage module and a scheduling module. The data storage module is used to store the standard operating condition data of each circuit and component in the power distribution room, and generate a standard data packet corresponding to each supervision node; the scheduling module is used to search for the corresponding standard data packet according to the coordinate information of the supervision node and output it to the operation supervision unit and the abnormality judgment unit;

[0010] The operation monitoring unit obtains the actual working condition data on the monitoring node, generates an abnormal fluctuation value according to the comparison between the actual working condition data and the standard data packet, and generates an abnormal notification signal to the abnormal judgment unit according to the preset fluctuation threshold;

[0011] The abnormality judgment unit obtains the position coordinates of the abnormal node, and analyzes and compares the standard data packet to generate a difference value, and then obtains the operation abnormality object through the generated difference value analysis, combines the position coordinates of the abnormal node with the operation abnormality object to generate primary abnormality mark information or secondary abnormality mark information, and sends the abnormal mark information to the inspection and positioning unit;

[0012] The inspection and positioning unit is used to obtain and process the first-level abnormal marking information or the second-level abnormal marking information, find the inspection personnel near the abnormal node according to the first-level abnormal marking information and send a maintenance notification, and find the maintenance station near the abnormal node according to the second-level abnormal marking information and send a maintenance notification.

[0013] Furthermore, the standard data packet includes equipment status monitoring data, environmental monitoring data, intelligent access control system status data, video surveillance data and intelligent inspection feedback data;

[0014] The equipment status monitoring data includes standard condition partial discharge current data, standard condition battery output voltage data and standard condition equipment temperature range;

[0015] Environmental monitoring data include normal ranges of ambient temperature, ambient humidity and noise;

[0016] The smart access control system includes smart door locks, infrared dual identification, perimeter detection and electronic fences. The status data of the smart access control system includes the number of normal feedback and the number of abnormal feedback;

[0017] Video surveillance data is the abnormal feedback analysis signal in the real-time video surveillance screen, including abnormal personnel signals and normal personnel signals;

[0018] Intelligent inspection feedback data is the feedback signal of the inspection robot or inspection safety officer, including inspection abnormality signal and inspection normality signal.

[0019] Furthermore, the specific process of generating an abnormal notification signal according to the preset fluctuation threshold is as follows:

[0020] S101, marking a number of supervision nodes as Qn, and obtaining real-time equipment status monitoring data at the supervision nodes, including partial discharge current data In, battery output voltage data Un, and equipment temperature data Tn;

[0021] S102, according to the label Qn of the supervision node, find the corresponding standard data packet through the scheduling module, wherein the standard data packet includes standard condition partial discharge current data Ii, standard condition battery output voltage data Ui and standard condition equipment temperature range (Tmin, Tmax);

[0022] S103. Calculate the abnormal fluctuation value We according to the following formula: , where e1, e2 and e3 are preset proportional coefficients, and the abnormal fluctuation value is used to evaluate the operating conditions of the power distribution equipment in the power distribution room. The larger the abnormal fluctuation value, the more the operating conditions of the power distribution equipment in the power distribution room deviate from the operating conditions in the standard operating state. On the contrary, the smaller the abnormal fluctuation value, the closer the operating conditions of the power distribution equipment in the power distribution room are to the operating conditions in the standard operating state.

[0023] S104, obtaining a preset fluctuation threshold Wmax, and if the abnormal fluctuation value We is greater than or equal to the fluctuation threshold Wmax, generating an abnormal notification signal and sending it to the abnormality judgment unit;

[0024] If the abnormal fluctuation value We is less than the fluctuation threshold Wmax, no signal is generated.

[0025] Furthermore, the specific process of obtaining abnormal operation objects through the generated difference value analysis is as follows:

[0026] S201, obtaining environmental monitoring data from a standard data packet, including a normal range of ambient temperature (Tmin, Tmax), a normal range of ambient humidity (RHmin, RHmax), and a normal range of noise (Bmin, Bmax);

[0027] S202, calculate the environmental difference value Ki according to the real-time monitoring data of the monitoring node: , where e4, e5 and e6 are preset proportional coefficients. The environmental difference value is used to determine whether the environmental data in the power distribution room is within the normal range. The larger the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range. Conversely, the smaller the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range.

[0028] S203, obtaining a preset difference threshold, if the environmental difference value Ki is greater than the difference threshold, the environmental monitoring data is an abnormal operation object;

[0029] S204, obtaining real-time intelligent access control system status data, recording the number of abnormal feedback n1, if n1 is greater than 0, the intelligent access control system status data is an abnormal operation object;

[0030] Obtain real-time video surveillance data and record the number of abnormal signals of personnel n2. If n2 is greater than 0, the video surveillance data is an abnormal operation object;

[0031] Obtain real-time intelligent inspection feedback data, including the number of abnormal inspection signals n3. If n3 is greater than 0, the intelligent inspection feedback data is an abnormal operation object.

[0032] Furthermore, the specific process of generating the first-level abnormal marking information or the second-level abnormal marking information is as follows:

[0033] Obtain the number of items Xn of abnormal operation objects, and according to the preset abnormal item number judgment threshold Xi, if the number of items of abnormal message objects is greater than the abnormal judgment threshold, generate secondary abnormal marking information;

[0034] If the number of items in the exception message object is greater than the exception judgment threshold, secondary exception marking information is generated.

[0035] Furthermore, the inspection and positioning unit includes a dynamic inspection recording module and a maintenance point selection and judgment module. The dynamic inspection recording module is used to obtain and process the first-level abnormal mark information. The dynamic inspection recording module is used to record the real-time coordinates of the inspection personnel, and the inspection personnel closest to the abnormal node are judged as the optimal maintenance target according to the abnormal node position coordinates in the abnormal mark information, and a maintenance notification is sent to the optimal maintenance target;

[0036] The maintenance point selection module is used to store the location data of each maintenance point, and after obtaining the secondary abnormality mark information, it determines the maintenance point closest to the abnormal node as the optimal maintenance target according to the abnormal node position coordinates in the abnormality mark information, and sends a maintenance notification to the maintenance point.

[0037] The present invention also provides an intelligent power distribution room operation supervision method, comprising the following steps:

[0038] Step 1: Establish a distribution room line operation model according to the design size and line distribution data of the distribution room, mark the supervision nodes according to the distribution room line operation model, obtain the coordinates of each supervision node, and store the coordinate information of each supervision node;

[0039] Step 2: Obtain standard operating data of each circuit and component in the power distribution room, generate a standard data packet for each supervisory node, and search for the corresponding standard data packet based on the coordinate information of the supervisory node;

[0040] Step 3: Obtain the actual working condition data on the supervision node, generate an abnormal fluctuation value based on the comparison between the actual working condition data and the standard data packet, and generate an abnormal notification signal based on the preset fluctuation threshold;

[0041] Step 4: Obtain the location coordinates of the abnormal node, and analyze and compare them with the standard data packet to generate a difference value, and then analyze the generated difference value to obtain the operation abnormal object, and combine the location coordinates of the abnormal node with the operation abnormal object to generate primary abnormal marking information or secondary abnormal marking information;

[0042] Step 5: Find the inspection personnel near the abnormal node according to the first-level abnormal mark information and send a maintenance notice; find the maintenance station near the abnormal node according to the second-level abnormal mark information and send a maintenance notice.

[0043] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0044] The present invention establishes a distribution room line operation model and marks supervision nodes, generates abnormal fluctuation values ​​based on comparisons of actual operating condition data with standard data packets, determines that the distribution room equipment has operational abnormalities based on preset fluctuation thresholds, and then obtains the position coordinates of the abnormal nodes, analyzes and compares with standard data packets to generate difference values ​​to obtain operational abnormality objects, finds inspection personnel near the abnormal nodes and sends maintenance notifications, or finds maintenance stations near the abnormal nodes and sends maintenance notifications, thereby achieving real-time emergency repairs and avoiding further losses caused by distribution failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of the system structure of the present invention is shown;

[0046] Figure 2 A schematic flow chart of the method of the present invention is shown. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Embodiment 1:

[0049] like Figure 1 As shown, an intelligent power distribution room operation supervision system includes a standard operating condition database, a power distribution modeling unit, an operation supervision unit, an abnormality judgment unit and an inspection and positioning unit;

[0050] The power distribution modeling unit is used to obtain the design size and line distribution data of the power distribution room to establish the power distribution room line operation model, and mark the supervision nodes according to the power distribution room line operation model, obtain the coordinates of each supervision node, and send the coordinate information of each supervision node to the inspection and positioning unit for storage;

[0051] The standard operating condition database includes a data storage module and a scheduling module. The data storage module is used to store the standard operating condition data of each circuit and component in the power distribution room, and generate a standard data packet corresponding to each supervision node; the scheduling module is used to search for the corresponding standard data packet according to the coordinate information of the supervision node and output it to the operation supervision unit and the abnormality judgment unit;

[0052] The standard data package includes equipment status monitoring data, environmental monitoring data, smart access control system status data, video surveillance data and smart inspection feedback data;

[0053] The equipment status monitoring data includes standard condition partial discharge current data, standard condition battery output voltage data and standard condition equipment temperature range;

[0054] Environmental monitoring data include normal ranges of ambient temperature, ambient humidity and noise;

[0055] The smart access control system includes smart door locks, infrared dual identification, perimeter detection and electronic fences. The status data of the smart access control system includes the number of normal feedback and the number of abnormal feedback;

[0056] Video surveillance data is the abnormal feedback analysis signal in the real-time video surveillance screen, including abnormal personnel signals and normal personnel signals;

[0057] Intelligent inspection feedback data is the feedback signal of the inspection robot or inspection safety officer, including inspection abnormality signal and inspection normality signal.

[0058] The operation monitoring unit obtains the actual working condition data on the monitoring node, generates an abnormal fluctuation value according to the comparison between the actual working condition data and the standard data packet, and generates an abnormal notification signal to the abnormal judgment unit according to the preset fluctuation threshold;

[0059] The specific process of generating an abnormal notification signal based on the preset fluctuation threshold is as follows:

[0060] S101, marking a number of supervision nodes as Qn, and obtaining real-time equipment status monitoring data at the supervision nodes, including partial discharge current data In, battery output voltage data Un, and equipment temperature data Tn;

[0061] S102, according to the label Qn of the supervision node, find the corresponding standard data packet through the scheduling module, wherein the standard data packet includes standard condition partial discharge current data Ii, standard condition battery output voltage data Ui and standard condition equipment temperature range (Tmin, Tmax);

[0062] S103. Calculate the abnormal fluctuation value We according to the following formula: , where e1, e2 and e3 are preset proportional coefficients, and the abnormal fluctuation value is used to evaluate the operating conditions of the power distribution equipment in the power distribution room. The larger the abnormal fluctuation value, the more the operating conditions of the power distribution equipment in the power distribution room deviate from the operating conditions in the standard operating state. On the contrary, the smaller the abnormal fluctuation value, the closer the operating conditions of the power distribution equipment in the power distribution room are to the operating conditions in the standard operating state.

[0063] S104, obtaining a preset fluctuation threshold Wmax, and if the abnormal fluctuation value We is greater than or equal to the fluctuation threshold Wmax, generating an abnormal notification signal and sending it to the abnormality judgment unit;

[0064] If the abnormal fluctuation value We is less than the fluctuation threshold Wmax, no signal is generated.

[0065] The abnormality judgment unit obtains the position coordinates of the abnormal node, and analyzes and compares the standard data packet to generate a difference value, and then obtains the operation abnormality object through the generated difference value analysis, combines the position coordinates of the abnormal node with the operation abnormality object to generate primary abnormality mark information or secondary abnormality mark information, and sends the abnormal mark information to the inspection and positioning unit;

[0066] The specific process of obtaining abnormal operation objects through the generated difference value analysis is as follows:

[0067] S201, obtaining environmental monitoring data from a standard data packet, including a normal range of ambient temperature (Tmin, Tmax), a normal range of ambient humidity (RHmin, RHmax), and a normal range of noise (Bmin, Bmax);

[0068] S202, calculate the environmental difference value Ki according to the real-time monitoring data of the monitoring node: , where e4, e5 and e6 are preset proportional coefficients. The environmental difference value is used to determine whether the environmental data in the power distribution room is within the normal range. The larger the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range. Conversely, the smaller the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range.

[0069] S203, obtaining a preset difference threshold, if the environmental difference value Ki is greater than the difference threshold, the environmental monitoring data is an abnormal operation object;

[0070] S204, obtaining real-time intelligent access control system status data, recording the number of abnormal feedback n1, if n1 is greater than 0, the intelligent access control system status data is an abnormal operation object;

[0071] Obtain real-time video surveillance data and record the number of abnormal signals of personnel n2. If n2 is greater than 0, the video surveillance data is an abnormal operation object;

[0072] Obtain real-time intelligent inspection feedback data, including the number of abnormal inspection signals n3. If n3 is greater than 0, the intelligent inspection feedback data is an abnormal operation object.

[0073] The specific process of generating the first-level abnormal marking information or the second-level abnormal marking information is as follows:

[0074] Obtain the number of items Xn of abnormal operation objects, and according to the preset abnormal item number judgment threshold Xi, if the number of items of abnormal message objects is greater than the abnormal judgment threshold, generate secondary abnormal marking information;

[0075] If the number of items in the exception message object is greater than the exception judgment threshold, secondary exception marking information is generated.

[0076] The inspection and positioning unit is used to obtain and process the first-level abnormal marking information or the second-level abnormal marking information, find the inspection personnel near the abnormal node according to the first-level abnormal marking information and send a maintenance notification, and find the maintenance station near the abnormal node according to the second-level abnormal marking information and send a maintenance notification.

[0077] The inspection and positioning unit includes a dynamic inspection recording module and a maintenance point selection and judgment module. The dynamic inspection recording module is used to obtain and process the first-level abnormal mark information. The dynamic inspection recording module is used to record the real-time coordinates of the inspection personnel, and the inspection personnel closest to the abnormal node are judged as the optimal maintenance target according to the abnormal node position coordinates in the abnormal mark information, and a maintenance notification is sent to the optimal maintenance target;

[0078] The maintenance point selection module is used to store the location data of each maintenance point, and after obtaining the secondary abnormality mark information, it determines the maintenance point closest to the abnormal node as the optimal maintenance target according to the abnormal node position coordinates in the abnormality mark information, and sends a maintenance notification to the maintenance point.

[0079] The present invention establishes a distribution room line operation model and marks supervision nodes, generates abnormal fluctuation values ​​based on comparisons of actual operating condition data with standard data packets, determines that the distribution room equipment has operational abnormalities based on preset fluctuation thresholds, and then obtains the position coordinates of the abnormal nodes, analyzes and compares with standard data packets to generate difference values ​​to obtain operational abnormality objects, finds inspection personnel near the abnormal nodes and sends maintenance notifications, or finds maintenance stations near the abnormal nodes and sends maintenance notifications, thereby achieving real-time emergency repairs and avoiding further losses caused by distribution failures.

[0080] Embodiment 2:

[0081] like Figure 2 As shown, the present invention also provides an intelligent distribution room operation supervision method, comprising the following steps:

[0082] Step 1: Establish a distribution room line operation model according to the design size and line distribution data of the distribution room, mark the supervision nodes according to the distribution room line operation model, obtain the coordinates of each supervision node, and store the coordinate information of each supervision node;

[0083] Step 2: Obtain standard operating data of each circuit and component in the power distribution room, generate a standard data packet for each supervisory node, and search for the corresponding standard data packet based on the coordinate information of the supervisory node;

[0084] Step 3: Obtain the actual working condition data on the supervision node, generate an abnormal fluctuation value based on the comparison between the actual working condition data and the standard data packet, and generate an abnormal notification signal based on the preset fluctuation threshold;

[0085] Step 4: Obtain the location coordinates of the abnormal node, and analyze and compare them with the standard data packet to generate a difference value, and then analyze the generated difference value to obtain the operation abnormal object, and combine the location coordinates of the abnormal node with the operation abnormal object to generate primary abnormal marking information or secondary abnormal marking information;

[0086] Step 5: Find the inspection personnel near the abnormal node according to the first-level abnormal mark information and send a maintenance notice; find the maintenance station near the abnormal node according to the second-level abnormal mark information and send a maintenance notice.

[0087] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0088] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0089] In the two embodiments provided in the present application, it should be understood that the disclosed devices and systems can be implemented in other ways; for example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, the indirect coupling or communication connection of devices or modules can be electrical, mechanical or other forms;

[0090] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent power distribution room operation supervision system, characterized in that: It includes standard operating condition database, power distribution modeling unit, operation supervision unit, abnormality judgment unit and inspection positioning unit; The power distribution modeling unit is used to obtain the design size and line distribution data of the power distribution room to establish the power distribution room line operation model, and mark the supervision nodes according to the power distribution room line operation model, obtain the coordinates of each supervision node, and send the coordinate information of each supervision node to the inspection and positioning unit for storage; The standard operating condition database includes a data storage module and a scheduling module. The data storage module is used to store the standard operating condition data of each circuit and component in the power distribution room, and generate a standard data packet corresponding to each supervision node; The scheduling module is used to search for the corresponding standard data packet according to the coordinate information of the supervision node and output it to the operation supervision unit and the abnormality judgment unit; The operation monitoring unit obtains the actual working condition data on the monitoring node, generates an abnormal fluctuation value according to the comparison between the actual working condition data and the standard data packet, and generates an abnormal notification signal to the abnormal judgment unit according to the preset fluctuation threshold; The specific process of generating an abnormal notification signal based on the preset fluctuation threshold is as follows: S101, marking a number of supervision nodes as Qn, and obtaining real-time equipment status monitoring data at the supervision nodes, including partial discharge current data In, battery output voltage data Un, and equipment temperature data Tn; S102, according to the label Qn of the supervision node, find the corresponding standard data packet through the scheduling module, wherein the standard data packet includes standard condition partial discharge current data Ii, standard condition battery output voltage data Ui and standard condition equipment temperature range (Tmin, Tmax); S103. Calculate the abnormal fluctuation value We according to the following formula: , where e1, e2 and e3 are preset proportional coefficients, and the abnormal fluctuation value is used to evaluate the operating conditions of the power distribution equipment in the power distribution room. The larger the abnormal fluctuation value, the more the operating conditions of the power distribution equipment in the power distribution room deviate from the operating conditions in the standard operating state. On the contrary, the smaller the abnormal fluctuation value, the closer the operating conditions of the power distribution equipment in the power distribution room are to the operating conditions in the standard operating state. S104, obtaining a preset fluctuation threshold Wmax, and if the abnormal fluctuation value We is greater than or equal to the fluctuation threshold Wmax, generating an abnormal notification signal and sending it to the abnormality judgment unit; If the abnormal fluctuation value We is less than the fluctuation threshold Wmax, no signal is generated; The abnormality judgment unit obtains the position coordinates of the abnormal node, and analyzes and compares the standard data packet to generate a difference value, and then obtains the operation abnormality object through the generated difference value analysis, combines the position coordinates of the abnormal node with the operation abnormality object to generate primary abnormality mark information or secondary abnormality mark information, and sends the abnormal mark information to the inspection and positioning unit; The specific process of generating the first-level abnormal marking information or the second-level abnormal marking information is as follows: Obtain the number of items Xn of abnormal operation objects, and according to the preset abnormal item number judgment threshold Xi, if the number of items of abnormal message objects is greater than the abnormal judgment threshold, generate the first-level abnormal marking information; If the number of items in the abnormal message object is greater than the abnormal judgment threshold, the secondary abnormal marking information is generated; The inspection and positioning unit is used to obtain and process the primary abnormal marking information or the secondary abnormal marking information, find the inspection personnel near the abnormal node according to the primary abnormal marking information and send a maintenance notice, and find the maintenance station near the abnormal node according to the secondary abnormal marking information and send a maintenance notice; The inspection and positioning unit includes a dynamic inspection recording module and a maintenance point selection and judgment module. The dynamic inspection recording module is used to obtain and process the first-level abnormal mark information. The dynamic inspection recording module is used to record the real-time coordinates of the inspection personnel, and the inspection personnel closest to the abnormal node are judged as the optimal maintenance target according to the abnormal node position coordinates in the abnormal mark information, and a maintenance notification is sent to the optimal maintenance target; The maintenance point selection module is used to store the location data of each maintenance point, and after obtaining the secondary abnormality mark information, it determines the maintenance point closest to the abnormal node as the optimal maintenance target according to the abnormal node position coordinates in the abnormality mark information, and sends a maintenance notification to the maintenance point.

2. The intelligent power distribution room operation monitoring system according to claim 1 is characterized in that: The standard data package includes equipment status monitoring data, environmental monitoring data, intelligent access control system status data, video surveillance data and intelligent inspection feedback data; The equipment status monitoring data includes standard condition partial discharge current data, standard condition battery output voltage data and standard condition equipment temperature range; Environmental monitoring data include normal ranges of ambient temperature, ambient humidity and noise; The smart access control system includes smart door locks, infrared dual identification, perimeter detection and electronic fences. The status data of the smart access control system includes the number of normal feedback and the number of abnormal feedback; Video surveillance data is the abnormal feedback analysis signal in the real-time video surveillance screen, including abnormal personnel signals and normal personnel signals; Intelligent inspection feedback data is the feedback signal of the inspection robot or inspection safety officer, including inspection abnormality signal and inspection normality signal.

3. The intelligent power distribution room operation monitoring system according to claim 1 is characterized in that: The specific process of obtaining abnormal operation objects through the generated difference value analysis is as follows: S201, obtaining environmental monitoring data from a standard data packet, including a normal range of ambient temperature (T′min, T′max), a normal range of ambient humidity (RHmin, RHmax), and a normal range of noise (Bmin, Bmax); S202, calculate the environmental difference value Ki according to the real-time monitoring data of the monitoring node: , where e4, e5 and e6 are preset proportional coefficients, RHn is real-time environmental humidity data, T′n is real-time environmental temperature data, Bn is real-time noise data, and the environmental difference value is used to determine whether the environmental data in the power distribution room is within the normal range. The larger the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range. Conversely, the smaller the environmental difference value, the more the environmental data in the power distribution room deviates from the normal range. S203, obtaining a preset difference threshold, if the environmental difference value Ki is greater than the difference threshold, the environmental monitoring data is an abnormal operation object; S204, obtaining real-time intelligent access control system status data, recording the number of abnormal feedback n1, if n1 is greater than 0, the intelligent access control system status data is an abnormal operation object; Obtain real-time video surveillance data and record the number of abnormal signals of personnel n2. If n2 is greater than 0, the video surveillance data is an abnormal operation object; Obtain real-time intelligent inspection feedback data, including the number of abnormal inspection signals n3. If n3 is greater than 0, the intelligent inspection feedback data is an abnormal operation object.

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