Intelligent monitoring system for electrical cabinet

Abstract

The invention provides an electrical cabinet intelligent monitoring system, and relates to the technical field of intelligent monitoring systems, and the system comprises a data collection module which is used for collecting the real-time power distribution parameters of an electrical cabinet, the in-cabinet environment parameters, the face data of an operator, and the real-time locking state of the electrical cabinet; the core monitoring module is used for monitoring the electrical cabinet based on the real-time power distribution parameters and the in-cabinet environment parameters of the electrical cabinet, the face data of the operator and the real-time locking state of the electrical cabinet; the control execution module is used for controlling the linkage environment control equipment to work or carrying out fault alarm prompt based on the monitoring result of the core monitoring module; and the data storage module is used for storing the data of the data acquisition module, the core monitoring module and the control execution module and generating a visual report. According to the invention, the power distribution parameters of the electrical cabinet, the environmental parameters in the cabinet, the face data of an operator and the real-time locking state of the electrical cabinet are monitored, so that potential threats can be found in time, and potential safety hazards are avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of intelligent monitoring systems, and in particular relates to an intelligent monitoring system for an electrical cabinet. Background Art

[0002] As an indispensable power distribution equipment in modern industrial production, the stable operation of electrical cabinets is crucial to the normal operation of production lines. However, many electrical cabinets currently lack a complete monitoring system and rely entirely on manual monitoring, which leads to abnormal power distribution, abnormal environmental control, abnormal facial recognition, and abnormal locking status of electrical cabinets. Once a problem occurs, it often takes a lot of time and manpower to discover it, which poses a potential threat to production safety and efficiency.

[0003] The most serious of these is the safety hazard. Due to the lack of a real-time monitoring system, electrical cabinets may have safety hazards such as overload and short circuit. These problems are difficult to detect in a timely manner, increasing the risk of fire and personal safety accidents. The lack of a monitoring system also means that it is impossible to analyze the operating status and discover potential problems with the equipment, which affects the life and stability of the equipment. Summary of the invention

[0004] The present invention provides an intelligent monitoring system for an electrical cabinet, which is used to solve at least one of the above-mentioned technical problems.

[0005] In order to solve the above technical problems, the present invention discloses an intelligent monitoring system for an electrical cabinet, comprising:

[0006] Data collection module, used to collect real-time power distribution parameters of the electrical cabinet, environmental parameters inside the cabinet, facial data of operators and real-time locking status of the electrical cabinet;

[0007] The core monitoring module is used to monitor the electrical cabinet based on the real-time power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the real-time locking status of the electrical cabinet;

[0008] A control execution module is used to control the operation of the linked environmental control equipment or issue a fault alarm prompt based on the monitoring results of the core monitoring module;

[0009] The data storage module is used to store the data of the data acquisition module, the core monitoring module and the control execution module, and generate a visual report.

[0010] Preferably, the data acquisition module includes:

[0011] A power distribution parameter collection unit is used to collect the power distribution voltage, power distribution current, working power and running time of the electrical cabinet;

[0012] Temperature collection unit, used to collect the temperature inside each electrical cabinet;

[0013] Humidity collection unit, used to collect the humidity inside each electrical cabinet;

[0014] Infrared hot spot collection unit, used to collect hot spots inside each electrical cabinet;

[0015] A smoke collection unit is used to collect smoke parameters of the environment inside the electrical cabinet;

[0016] A facial data collection unit, used to collect facial data of operators;

[0017] The lock status collection unit is used to collect the switch status of the electrical cabinet lock.

[0018] Preferably, the core monitoring module includes:

[0019] The power distribution abnormality monitoring unit is used to compare the preset power distribution parameters with the actual power distribution parameters. If the actual power distribution parameters exceed the preset power distribution parameter range, the control execution module controls the power distribution control platform to perform control;

[0020] The cabinet environment monitoring unit is used to compare the preset cabinet environment parameters with the actual cabinet environment parameters. If the actual cabinet environment parameters exceed the preset cabinet environment parameter range, the control execution module controls the dehumidifier, air conditioning components, and fire protection components to regulate the cabinet environment;

[0021] The face recognition monitoring unit is used to compare the collected operator's facial data with the pre-stored operator's facial data. If the facial data does not match, the control execution module controls the alarm to issue a false intrusion alarm prompt;

[0022] The locking state monitoring unit is used to compare the actual locking state of the electrical cabinet with the preset locking state of the electrical cabinet. When the actual locking state of the electrical cabinet does not match the preset locking state of the electrical cabinet, the control execution module controls the alarm to give an error alarm prompt.

[0023] Preferably, it also includes an electrical cabinet overall status assessment module, and the electrical cabinet overall status assessment module includes:

[0024] An evaluation value acquisition unit is used to obtain the power distribution response performance evaluation value, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the real-time power distribution parameters and cabinet environment parameters of the electrical cabinet collected by the data acquisition module, the facial data of the operator and the real-time locking status of the electrical cabinet;

[0025] An evaluation matrix construction unit is used to construct an overall state evaluation matrix of the electrical cabinet based on the collected real-time power distribution parameters of the electrical cabinet and the environmental parameters inside the cabinet, the facial data of the operator, the real-time locking state of the electrical cabinet, the power distribution response performance evaluation value within the current monitoring period of the electrical cabinet, the environmental evaluation value inside the cabinet, the facial recognition accuracy evaluation value and the locking response sensitivity evaluation value of the electrical cabinet;

[0026] The overall status analysis unit is used to evaluate the overall status of the electrical cabinet in the current monitoring period based on the overall status evaluation matrix of the electrical cabinet.

[0027] Preferably, the evaluation value acquisition unit includes:

[0028] The power distribution response performance evaluation subunit is used to obtain the power distribution response performance evaluation value of the electrical cabinet in the current monitoring period based on the collected real-time power distribution parameters of the electrical cabinet and the preset power distribution response performance evaluation model;

[0029] The cabinet environment assessment subunit is used to obtain the cabinet environment assessment value of the electrical cabinet in the current monitoring period based on the collected real-time cabinet environment parameters of the electrical cabinet and the preset cabinet environment assessment model;

[0030] A facial recognition accuracy evaluation subunit is used to obtain a facial recognition accuracy evaluation value of the electrical cabinet within a current monitoring period based on the collected facial data of the operator, the facial recognition result and a preset facial recognition accuracy evaluation model;

[0031] The electrical cabinet locking response sensitivity evaluation subunit is used to obtain the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the collected real-time locking state parameters of the electrical cabinet and the preset electrical cabinet locking response sensitivity evaluation model.

[0032] Preferably, based on collecting the real-time power distribution parameters of the electrical cabinet and the environmental parameters inside the cabinet, the facial data of the operator, the real-time locking status of the electrical cabinet, the power distribution response performance evaluation value of the electrical cabinet in the current monitoring cycle, the environmental evaluation value inside the cabinet, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value, an overall status evaluation matrix of the electrical cabinet is constructed, including:

[0033] Calculate the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring period, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring period, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring period, and the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring period;

[0034] Based on the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring cycle, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring cycle, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring cycle, the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring cycle, the power distribution response performance evaluation value in each monitoring cycle, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value, an overall status evaluation matrix of the electrical cabinet is constructed.

[0035] Preferably, based on the power distribution parameters of the electrical cabinet in the nth monitoring period, the power distribution response performance sensor calculation value of the electrical cabinet in the nth monitoring period is calculated:

[0036] Where u is the total number of distribution parameters, a ni is the sensor detection value of the ith power distribution parameter in the nth monitoring cycle, a ni0 is the preset value of the ith power distribution parameter in the nth monitoring cycle;

[0037] Based on the environmental parameters inside the electrical cabinet in the nth monitoring period, the calculated value of the environmental control capability sensor inside the electrical cabinet in the nth monitoring period is calculated:

[0038] Where v is the total number of distribution parameters, b ni is the sensor detection value of the ith environmental parameter in the nth monitoring period, b ni0 is the preset value of the ith environmental parameter in the nth monitoring period;

[0039] Based on the total number of facial recognitions and the number of correct facial recognitions in the nth monitoring cycle, calculate the sensor calculation value of the electrical cabinet facial recognition accuracy in the nth monitoring cycle:

[0040] Among them, M n is the total number of facial recognitions in the nth monitoring cycle, m n is the number of correct facial recognitions in the nth monitoring cycle;

[0041] Based on the real-time locking state parameters of the electrical cabinet in the nth monitoring period, the calculated value of the locking response sensitivity sensor of the electrical cabinet in the nth monitoring period is calculated:

[0042] Where w is the total number of power distribution parameters, c ni is the sensor detection value of the i-th locking state parameter in the n-th monitoring cycle, c ni0 It is the preset value of the i-th locking state parameter in the n-th monitoring cycle.

[0043] Preferably, the overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle is:

[0044] Among them, γ n is the overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle, δ1 is the calculated value of the distribution response performance sensor of the electrical cabinet in the first monitoring cycle, δ2 is the calculated value of the distribution response performance sensor of the electrical cabinet in the second monitoring cycle, δ n is the calculated value of the distribution response performance sensor of the electrical cabinet in the nth monitoring cycle, ε1 is the calculated value of the environmental control capability sensor in the electrical cabinet in the first monitoring cycle, ε2 is the calculated value of the environmental control capability sensor in the electrical cabinet in the second monitoring cycle, and ε n is the calculated value of the environmental control capability sensor in the electrical cabinet in the nth monitoring cycle, α1 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the first monitoring cycle, α2 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the second monitoring cycle, and α n is the calculated value of the facial recognition accuracy sensor of the electrical cabinet in the nth monitoring cycle, β1 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the first monitoring cycle, β2 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the second monitoring cycle, β n is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the nth monitoring cycle, A1 is the distribution response performance evaluation value in the first monitoring cycle, A2 is the distribution response performance evaluation value in the second monitoring cycle, and A n is the distribution response performance evaluation value in the nth monitoring cycle, B1 is the cabinet environment evaluation value in the first monitoring cycle, B2 is the cabinet environment evaluation value in the second monitoring cycle, and B n is the evaluation value of the cabinet environment in the nth monitoring cycle, C1 is the evaluation value of the facial recognition accuracy in the first monitoring cycle, C2 is the evaluation value of the facial recognition accuracy in the second monitoring cycle, and C n is the facial recognition accuracy evaluation value in the nth monitoring cycle, D1 is the electrical cabinet locking response sensitivity evaluation value in the first monitoring cycle, D2 is the electrical cabinet locking response sensitivity evaluation value in the second monitoring cycle, and D n It is the evaluation value of the locking response sensitivity of the electrical cabinet in the nth monitoring cycle.

[0045] Preferably, the overall state analysis unit comprises:

[0046] The intermediate matrix acquisition subunit deletes the corresponding elements of each type of performance calculation value and each type of performance evaluation value in all matrix elements in the overall status evaluation matrix of the electrical cabinet in the nth monitoring period, and obtains the intermediate matrix corresponding to each type of performance;

[0047] The primary and secondary classification subunit compares the rank of the intermediate matrix corresponding to each type of performance with the preset evaluation value of each type of performance. If the rank of the intermediate matrix corresponding to each type of performance is greater than the preset evaluation value of each type of performance, it is a primary performance item, otherwise it is a secondary performance item;

[0048] An overall state calculation unit, used to calculate the current overall state coefficient of the electrical cabinet based on the evaluation values ​​corresponding to the main performance items and the secondary performance items;

[0049] The overall state evaluation and judgment unit issues a cabinet replacement alarm when the current overall state coefficient of the electrical cabinet is less than the preset current overall state coefficient of the electrical cabinet.

[0050] Preferably, the overall state coefficient of the electrical cabinet in the nth monitoring cycle is:

[0051] Among them, e is a natural number, f n is the number of secondary performance items, F n is the number of main performance items, lg is the logarithm with base 10, λ nj0 is the preset evaluation value corresponding to the jth main performance item in the nth monitoring period, λ nj It is the evaluation value corresponding to the jth main performance item in the nth monitoring cycle.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention monitors the power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the real-time locking status of the electrical cabinet, so as to timely discover potential threats and avoid potential safety hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 This is a schematic diagram of an intelligent monitoring system for electrical cabinets proposed by the present invention. DETAILED DESCRIPTION

[0056] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0057] In addition, in the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes, and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions and technical features between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0058] The present invention provides the following embodiments

[0059] Example 1

[0060] The embodiment of the present invention provides an intelligent monitoring system for an electrical cabinet, such as Figure 1 As shown, including:

[0061] Data collection module, used to collect real-time power distribution parameters of the electrical cabinet, environmental parameters inside the cabinet, facial data of operators and real-time locking status of the electrical cabinet;

[0062] The core monitoring module is used to monitor the electrical cabinet based on the real-time power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the real-time locking status of the electrical cabinet;

[0063] A control execution module is used to control the operation of the linked environmental control equipment or issue a fault alarm prompt based on the monitoring results of the core monitoring module;

[0064] The data storage module is used to store the data of the data acquisition module, the core monitoring module and the control execution module, and generate a visual report.

[0065] In this embodiment, the real-time power distribution parameters of the electrical cabinet include power distribution voltage, power distribution current, electrical cabinet operating power and electrical cabinet operating time.

[0066] In this embodiment, the environmental parameters inside the cabinet include the ambient temperature inside the electrical cabinet, the ambient humidity inside the electrical cabinet, the ambient hot spots inside the electrical cabinet, and the smoke conditions inside the electrical cabinet.

[0067] In this embodiment, the operator's facial data includes facial feature points (identifying and capturing key feature points in the face, such as eyes, nose, mouth, etc., for establishing the geometric structure and shape of the face), facial contour (detecting and extracting facial contour lines, including facial shape, chin, cheekbones and other features, for identifying the overall shape of the face), facial texture (extracting texture features of facial images, including skin color, wrinkles, spots, etc., for identifying unique features of individuals), facial expressions (recording facial expression features, such as smiling, closing eyes, etc., to obtain more facial information), and facial depth images (using technologies such as infrared or structured light to obtain three-dimensional depth information of the face to increase the accuracy and security of facial recognition).

[0068] In this embodiment, the real-time locking status of the electrical cabinet includes locked and unlocked.

[0069] In this embodiment, the linked environmental control equipment includes a dehumidifier, an air conditioning component, an alarm, a power distribution control platform and a fire protection component.

[0070] The working principle and beneficial effects of the above technical solution are as follows: the present invention obtains the power distribution parameters, environmental parameters, facial data of the operator and the locking status of the electrical cabinet in real time through the data acquisition module, and analyzes and monitors these data through the core monitoring module. By monitoring the real-time power distribution parameters and environmental parameters of the electrical cabinet, the system can timely detect and warn abnormal conditions of the electrical cabinet, such as overload, high temperature, excessive humidity, smoke, etc., so as to take corresponding measures to prevent the occurrence of safety problems such as equipment failure and fire. The collection and recognition of the facial data of the operator can realize the function of the smart door lock. By recognizing the facial features of the operator, face recognition can be performed to control the unlocking and locking status of the electrical cabinet, improve the safety of the equipment and the convenience of management. The control execution module can realize the linkage with the environmental control equipment according to the monitoring results of the core monitoring module, such as starting the dehumidifier, air conditioning components, etc. to adjust the temperature and humidity in the electrical cabinet, or triggering the alarm, fire protection components, etc. for emergency processing. The data storage module can store and manage the data of each module, and generate a visual report to facilitate the management personnel to perform data analysis and decision-making;

[0071] The present invention monitors the power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the real-time locking status of the electrical cabinet, so as to timely discover potential threats and avoid potential safety hazards.

[0072] Example 2

[0073] Based on Example 1, the data acquisition module includes:

[0074] A power distribution parameter collection unit is used to collect the power distribution voltage, power distribution current, working power and running time of the electrical cabinet;

[0075] Temperature collection unit, used to collect the temperature inside each electrical cabinet;

[0076] Humidity collection unit, used to collect the humidity inside each electrical cabinet;

[0077] Infrared hot spot collection unit, used to collect hot spots inside each electrical cabinet;

[0078] A smoke collection unit is used to collect smoke parameters of the environment inside the electrical cabinet;

[0079] A facial data collection unit, used to collect facial data of operators;

[0080] The lock status collection unit is used to collect the switch status of the electrical cabinet lock.

[0081] The working principle and beneficial effects of the above technical solution are as follows: the data acquisition module realizes the ability of multi-dimensional real-time monitoring of electrical cabinets through various special acquisition units, thereby improving the intelligent management level of electrical cabinets. The power distribution parameter acquisition unit can accurately monitor the voltage, current, power and operating time of the electrical cabinet, thereby ensuring the stability and safety of power supply. The temperature and humidity acquisition unit grasps the environmental status inside the cabinet in real time to prevent equipment failures caused by overheating or humidity. The infrared hotspot acquisition unit can promptly detect overheating areas of the equipment to ensure the safe operation of electrical equipment. The smoke collection unit provides an important basis for fire warning and effectively improves the safety prevention capability. The facial data acquisition unit enhances the safety control of the electrical cabinet by identifying the identity of the operator. The locking status acquisition unit ensures the safe opening and closing of the electrical cabinet, further improving the operational safety. By integrating information, the data acquisition module provides comprehensive and real-time support for intelligent monitoring and fault warning of the electrical cabinet, significantly improving the operating efficiency and safety of the equipment.

[0082] Example 3

[0083] Based on Example 1, the core monitoring module includes:

[0084] The power distribution abnormality monitoring unit is used to compare the preset power distribution parameters with the actual power distribution parameters. If the actual power distribution parameters exceed the preset power distribution parameter range, the control execution module controls the power distribution control platform to perform control;

[0085] The cabinet environment monitoring unit is used to compare the preset cabinet environment parameters with the actual cabinet environment parameters. If the actual cabinet environment parameters exceed the preset cabinet environment parameter range, the control execution module controls the dehumidifier, air conditioning components, and fire protection components to regulate the cabinet environment;

[0086] The face recognition monitoring unit is used to compare the collected operator's facial data with the pre-stored operator's facial data. If the facial data does not match, the control execution module controls the alarm to issue a false intrusion alarm prompt;

[0087] The locking state monitoring unit is used to compare the actual locking state of the electrical cabinet with the preset locking state of the electrical cabinet. When the actual locking state of the electrical cabinet does not match the preset locking state of the electrical cabinet, the control execution module controls the alarm to give an error alarm prompt.

[0088] In this embodiment, the preset power distribution parameters and the actual power distribution parameters include power distribution voltage, power distribution current, electrical cabinet operating power and electrical cabinet operating time.

[0089] In this embodiment, the preset cabinet environment parameters and the actual cabinet environment parameters include the ambient temperature in the electrical cabinet, the ambient humidity in the electrical cabinet, the ambient hot spots in the electrical cabinet, and the smoke condition in the environment in the electrical cabinet.

[0090] The working principle and beneficial effects of the above technical solution are as follows: through real-time monitoring of the power distribution parameters of the electrical cabinet, an alarm will be immediately sounded in case of an abnormality to ensure safe use of electricity in the electrical cabinet; through real-time monitoring of temperature and humidity, environmental control equipment such as dehumidifiers and air conditioners are linked to remotely adjust the temperature and humidity to keep them within the normal range to ensure the stability of the internal environment of the electrical cabinet; 7*24 hours real-time monitoring is provided, and various data of the computer room can be viewed in real time and without distance, and the operation and maintenance management process is optimized. The computer room can be operated and maintained anytime and anywhere, regardless of whether the personnel are in the computer room or not, which can improve management efficiency, save manpower, reduce labor intensity, quickly judge and respond to emergencies, and reduce accident hazards. The electrical cabinet monitoring system can also detect remote computer room faults in time, ensure the safe operation of communication equipment, and realize unmanned remote computer rooms, saving a lot of maintenance costs, improving maintenance levels, and reducing the number of maintenance personnel;

[0091] The core monitoring module realizes comprehensive intelligent monitoring and management of electrical cabinets through diversified monitoring units, significantly improving the safety and operating efficiency of the equipment.

[0092] Example 4

[0093] On the basis of embodiment 1, an electrical cabinet overall state evaluation module is also included, and the electrical cabinet overall state evaluation module includes:

[0094] An evaluation value acquisition unit is used to obtain the power distribution response performance evaluation value, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the real-time power distribution parameters and cabinet environment parameters of the electrical cabinet collected by the data acquisition module, the facial data of the operator and the real-time locking status of the electrical cabinet;

[0095] An evaluation matrix construction unit is used to construct an overall state evaluation matrix of the electrical cabinet based on the collected real-time power distribution parameters of the electrical cabinet and the environmental parameters inside the cabinet, the facial data of the operator, the real-time locking state of the electrical cabinet, the power distribution response performance evaluation value within the current monitoring period of the electrical cabinet, the environmental evaluation value inside the cabinet, the facial recognition accuracy evaluation value and the locking response sensitivity evaluation value of the electrical cabinet;

[0096] The overall status analysis unit is used to evaluate the overall status of the electrical cabinet in the current monitoring period based on the overall status evaluation matrix of the electrical cabinet.

[0097] The working principle and beneficial effects of the above technical solution are as follows: by evaluating multiple key indicators, the operating status and performance of the electrical cabinet can be fully and comprehensively understood; the power supply capacity and load adaptability of the electrical cabinet can be judged through the power distribution response performance evaluation value; the cabinet environment evaluation value can judge the safety and environmental suitability of the electrical equipment, and indirectly obtain the environmental control ability of the electrical cabinet; the facial recognition accuracy evaluation value can evaluate the accuracy and reliability of the facial recognition system; the electrical cabinet locking response sensitivity evaluation value can measure the safety and management efficiency of the electrical cabinet;

[0098] By constructing an overall status assessment matrix for the electrical cabinet, an objective assessment of the overall status of the electrical cabinet can be achieved, which can provide timely and effective reference for operation and maintenance personnel, help them judge the operating status of the electrical cabinet, take corresponding measures in a timely manner, and improve the reliability, safety and operating efficiency of the equipment.

[0099] Example 5

[0100] Based on Embodiment 4, the evaluation value acquisition unit includes:

[0101] The power distribution response performance evaluation subunit is used to obtain the power distribution response performance evaluation value of the electrical cabinet in the current monitoring period based on the collected real-time power distribution parameters of the electrical cabinet and the preset power distribution response performance evaluation model;

[0102] The cabinet environment assessment subunit is used to obtain the cabinet environment assessment value of the electrical cabinet in the current monitoring period based on the collected real-time cabinet environment parameters of the electrical cabinet and the preset cabinet environment assessment model;

[0103] A facial recognition accuracy evaluation subunit is used to obtain a facial recognition accuracy evaluation value of the electrical cabinet within a current monitoring period based on the collected facial data of the operator, the facial recognition result and a preset facial recognition accuracy evaluation model;

[0104] The electrical cabinet locking response sensitivity evaluation subunit is used to obtain the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the collected real-time locking state parameters of the electrical cabinet and the preset electrical cabinet locking response sensitivity evaluation model.

[0105] In this embodiment, the preset power distribution response performance evaluation model is a model obtained by training a neural network model using a large number of actual power distribution parameters and preset power distribution parameters as model inputs and manually evaluated power distribution response performance evaluation values ​​as model outputs.

[0106] In this embodiment, the preset cabinet environment assessment model is a model obtained by training a neural network model using a large number of actual cabinet environment parameters and preset cabinet environment parameters as model inputs and manually assessed cabinet environment assessment values ​​as model outputs.

[0107] In this embodiment, the preset facial recognition accuracy evaluation model is a model obtained by training a neural network model using a large number of actual facial recognition parameters and preset facial recognition parameters as model inputs and manually evaluated facial recognition accuracy evaluation values ​​as model outputs.

[0108] In this embodiment, the preset electrical cabinet locking response sensitivity evaluation model is a model obtained by training a neural network model with a large number of locking smoothness, locking depth, and locking response speed as model inputs and manually evaluated electrical cabinet locking response sensitivity evaluation values ​​as model outputs.

[0109] The working principle and beneficial effects of the above technical solution are as follows: each evaluation sub-unit in the evaluation value acquisition unit is responsible for obtaining the evaluation values ​​of the power distribution response performance, the cabinet environment, the facial recognition accuracy and the locking response of the electrical cabinet within the current monitoring cycle of the electrical cabinet based on the collected data and the preset evaluation model. The preset evaluation model refers to a pre-set standard or rule used to evaluate and measure the various performance and status of the electrical cabinet.

[0110] Example 6

[0111] On the basis of Example 4, based on the collection of real-time power distribution parameters and cabinet environment parameters of the electrical cabinet, facial data of the operator, real-time locking status of the electrical cabinet, power distribution response performance evaluation value of the electrical cabinet in the current monitoring cycle, cabinet environment evaluation value, facial recognition accuracy evaluation value and electrical cabinet locking response sensitivity evaluation value, an overall status evaluation matrix of the electrical cabinet is constructed, including:

[0112] Calculate the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring period, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring period, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring period, and the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring period;

[0113] Based on the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring cycle, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring cycle, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring cycle, the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring cycle, the power distribution response performance evaluation value in each monitoring cycle, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value, an overall status evaluation matrix of the electrical cabinet is constructed.

[0114] The working principle and beneficial effects of the above technical solution are as follows: based on the collected real-time power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the locking status, the process of constructing the overall status evaluation matrix of the electrical cabinet greatly improves the comprehensive performance and decision-making ability of the electrical cabinet monitoring system. By calculating the sensor calculation values ​​of the power distribution response performance, the environmental control capability inside the cabinet, the facial recognition accuracy and the locking response sensitivity in each monitoring cycle, the system can form a comprehensive evaluation basis. Combining these calculated values ​​with the corresponding evaluation values, the constructed overall status evaluation matrix not only provides correlation analysis between various performance indicators, helps operation and maintenance personnel quickly identify potential anomalies and risks, but also provides a scientific basis for optimizing the operation strategy and environmental regulation of the electrical cabinet.

[0115] Example 7

[0116] On the basis of Example 6, based on the power distribution parameters of the electrical cabinet in the nth monitoring period, the power distribution response performance sensor calculation value of the electrical cabinet in the nth monitoring period is calculated:

[0117] Where u is the total number of distribution parameters, a ni is the sensor detection value of the ith power distribution parameter in the nth monitoring cycle, a ni0 is the preset value of the ith power distribution parameter in the nth monitoring cycle;

[0118] Based on the environmental parameters inside the electrical cabinet in the nth monitoring period, the calculated value of the environmental control capability sensor inside the electrical cabinet in the nth monitoring period is calculated:

[0119] Where v is the total number of distribution parameters, b ni is the sensor detection value of the ith environmental parameter in the nth monitoring period, b ni0 is the preset value of the ith environmental parameter in the nth monitoring period;

[0120] Based on the total number of facial recognitions and the number of correct facial recognitions in the nth monitoring cycle, calculate the sensor calculation value of the electrical cabinet facial recognition accuracy in the nth monitoring cycle:

[0121] Among them, Mn is the total number of facial recognitions in the nth monitoring cycle, m n is the number of correct facial recognitions in the nth monitoring cycle;

[0122] Based on the real-time locking state parameters of the electrical cabinet in the nth monitoring period, the calculated value of the locking response sensitivity sensor of the electrical cabinet in the nth monitoring period is calculated:

[0123] Where w is the total number of power distribution parameters, c ni is the sensor detection value of the i-th locking state parameter in the n-th monitoring cycle, c ni0 It is the preset value of the i-th locking state parameter in the n-th monitoring cycle.

[0124] The working principle and beneficial effects of the above technical scheme are as follows: based on the power distribution parameters of the electrical cabinet in the nth monitoring cycle, the environmental parameters inside the cabinet, the facial recognition data and the locking status parameters, by calculating the power distribution response performance sensor calculation value, the cabinet environment control capability sensor calculation value, the facial recognition accuracy sensor calculation value and the locking response sensitivity sensor calculation value, a comprehensive evaluation of the overall status of the electrical cabinet is achieved. The power distribution response performance sensor calculation value reflects the power response execution capability of the electrical cabinet, the cabinet environment control capability sensor calculation value evaluates the environmental control capability of the electrical cabinet, the facial recognition accuracy sensor calculation value measures the accuracy of the facial recognition system, and the locking response sensitivity sensor calculation value reflects the safety performance of the electrical cabinet.

[0125] Example 8

[0126] Based on Example 6, the overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle is:

[0127] Among them, γ n is the overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle, δ1 is the calculated value of the distribution response performance sensor of the electrical cabinet in the first monitoring cycle, δ2 is the calculated value of the distribution response performance sensor of the electrical cabinet in the second monitoring cycle, δ n is the calculated value of the distribution response performance sensor of the electrical cabinet in the nth monitoring cycle, ε1 is the calculated value of the environmental control capability sensor in the electrical cabinet in the first monitoring cycle, ε2 is the calculated value of the environmental control capability sensor in the electrical cabinet in the second monitoring cycle, and ε n is the calculated value of the environmental control capability sensor in the electrical cabinet in the nth monitoring cycle, α1 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the first monitoring cycle, α2 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the second monitoring cycle, and α nis the calculated value of the facial recognition accuracy sensor of the electrical cabinet in the nth monitoring cycle, β1 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the first monitoring cycle, β2 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the second monitoring cycle, β n is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the nth monitoring cycle, A1 is the distribution response performance evaluation value in the first monitoring cycle, A2 is the distribution response performance evaluation value in the second monitoring cycle, and A n is the distribution response performance evaluation value in the nth monitoring cycle, B1 is the cabinet environment evaluation value in the first monitoring cycle, B2 is the cabinet environment evaluation value in the second monitoring cycle, and B n is the evaluation value of the cabinet environment in the nth monitoring cycle, C1 is the evaluation value of the facial recognition accuracy in the first monitoring cycle, C2 is the evaluation value of the facial recognition accuracy in the second monitoring cycle, and C n is the facial recognition accuracy evaluation value in the nth monitoring cycle, D1 is the electrical cabinet locking response sensitivity evaluation value in the first monitoring cycle, D2 is the electrical cabinet locking response sensitivity evaluation value in the second monitoring cycle, and D n It is the evaluation value of the locking response sensitivity of the electrical cabinet in the nth monitoring cycle.

[0128] The working principle and beneficial effects of the above technical solution are as follows: the establishment of an overall status evaluation matrix for the electrical cabinet in the nth monitoring cycle, by integrating the sensor calculation values ​​and evaluation values ​​of the power distribution response performance, the environmental control capability inside the cabinet, the facial recognition accuracy and the locking response sensitivity in each monitoring cycle, provides comprehensive data support for the comprehensive evaluation of the overall operating status of the electrical cabinet, and can intuitively display the changing trends of the key performance indicators of the electrical cabinet during different monitoring cycles, helping operation and maintenance personnel to identify potential safety hazards and performance degradation, and improve the management efficiency of the electrical cabinet and the scientific nature of operation and maintenance decisions. By comparing and analyzing various evaluation values, operation and maintenance personnel can timely adjust maintenance strategies and optimize operating parameters, thereby ensuring that the electrical cabinet is always in the best state in terms of safety, reliability and efficiency, and ultimately promoting the intelligent management and sustainable development of electrical equipment.

[0129] Example 9

[0130] Based on Example 8, the overall state analysis unit includes:

[0131] The intermediate matrix acquisition subunit deletes the corresponding elements of each type of performance calculation value and its corresponding performance evaluation value in all matrix elements in the overall status evaluation matrix of the electrical cabinet in the nth monitoring period, and obtains the intermediate matrix corresponding to each type of performance;

[0132] The primary and secondary classification subunit compares the rank of the intermediate matrix corresponding to each type of performance with the preset evaluation value of each type of performance. If the rank of the intermediate matrix corresponding to each type of performance is greater than the preset evaluation value of each type of performance, it is a primary performance item, otherwise it is a secondary performance item;

[0133] An overall state calculation unit, used to calculate the current overall state coefficient of the electrical cabinet based on the evaluation values ​​corresponding to the main performance items and the secondary performance items;

[0134] The overall state evaluation and judgment unit issues a cabinet replacement alarm when the current overall state coefficient of the electrical cabinet is less than the preset current overall state coefficient of the electrical cabinet.

[0135] In this embodiment, the main performance items include any one or more of power distribution response performance, environmental control capability, facial recognition accuracy, or lock response sensitivity.

[0136] In this embodiment, the secondary performance items include any one or more of power distribution response performance, environmental control capability, facial recognition accuracy, or lock response sensitivity.

[0137] The working principle and beneficial effects of the above technical solution are as follows: the overall status analysis unit effectively improves the operation monitoring and fault warning capabilities of the electrical cabinet through a series of refined processing steps. The intermediate matrix acquisition subunit first extracts the intermediate matrix corresponding to each type of performance from the overall status evaluation matrix of the nth monitoring cycle, thereby more clearly reflecting the actual performance of each type of performance. The primary and secondary classification subunit classifies the performance items into primary performance items and secondary performance items by comparing the rank of the intermediate matrix with the preset evaluation value, ensuring that the operation and maintenance personnel can focus on key performance indicators. The overall status calculation unit relies on the evaluation values ​​of the primary and secondary performance items to calculate the current overall status coefficient, providing a quantitative basis for the health status of the equipment. When the overall status coefficient is lower than the preset value, a cabinet replacement alarm is issued in time to prevent potential failures and safety hazards, thereby improving the safety and reliability of the electrical cabinet, optimizing equipment management, and ensuring the efficiency and stability of the operation of electrical equipment.

[0138] Example 10

[0139] Based on Example 9, the overall state coefficient of the electrical cabinet in the nth monitoring cycle is:

[0140] Among them, e is a natural number, f n is the number of secondary performance items, F n is the number of main performance items, lg is the logarithm with base 10, λ nj0 is the preset evaluation value corresponding to the jth main performance item in the nth monitoring period, λ njIt is the evaluation value corresponding to the jth main performance item in the nth monitoring cycle.

[0141] In this embodiment, the evaluation values ​​corresponding to the main performance items include one or more of a power distribution response performance evaluation value, an in-cabinet environment evaluation value, a facial recognition accuracy evaluation value, or an electrical cabinet locking response sensitivity evaluation value.

[0142] The working principle and beneficial effects of the above technical solution are as follows: the calculation formula for the overall status coefficient of the electrical cabinet in the nth monitoring cycle provides a quantitative indicator by comprehensively considering the evaluation values ​​of the main performance items and the secondary performance items, reflecting the overall health status of the electrical cabinet. The formula not only integrates the main performance items (such as the power distribution response performance evaluation value, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the locking response sensitivity evaluation value), but also enhances the sensitivity of the evaluation through logarithmic operations, ensuring that the different performances of the electrical cabinet can be effectively distinguished. The operation and maintenance personnel can accurately identify the operating status of the electrical cabinet, adjust the maintenance strategy in time, prevent potential risks, and thus improve the safety and reliability of the electrical cabinet.

[0143] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent monitoring system for electrical cabinets, characterized in that: include: Data collection module, used to collect real-time power distribution parameters of the electrical cabinet, environmental parameters inside the cabinet, facial data of operators and real-time locking status of the electrical cabinet; The core monitoring module is used to monitor the electrical cabinet based on the real-time power distribution parameters of the electrical cabinet, the environmental parameters inside the cabinet, the facial data of the operator and the real-time locking status of the electrical cabinet; A control execution module is used to control the operation of the linked environmental control equipment or issue a fault alarm prompt based on the monitoring results of the core monitoring module; The data storage module is used to store the data of the data acquisition module, the core monitoring module and the control execution module, and generate a visual report.

2. The intelligent monitoring system for electrical cabinets according to claim 1 is characterized in that: The data acquisition module includes: A power distribution parameter collection unit is used to collect the power distribution voltage, power distribution current, working power and running time of the electrical cabinet; Temperature collection unit, used to collect the temperature inside each electrical cabinet; Humidity collection unit, used to collect the humidity inside each electrical cabinet; Infrared hot spot collection unit, used to collect hot spots inside each electrical cabinet; A smoke collection unit is used to collect smoke parameters of the environment inside the electrical cabinet; A facial data collection unit, used to collect facial data of operators; The lock status collection unit is used to collect the switch status of the electrical cabinet lock.

3. The intelligent monitoring system for electrical cabinets according to claim 1 is characterized in that: The core monitoring modules include: The power distribution abnormality monitoring unit is used to compare the preset power distribution parameters with the actual power distribution parameters. If the actual power distribution parameters exceed the preset power distribution parameter range, the control execution module controls the power distribution control platform to perform control; The cabinet environment monitoring unit is used to compare the preset cabinet environment parameters with the actual cabinet environment parameters. If the actual cabinet environment parameters exceed the preset cabinet environment parameter range, the control execution module controls the dehumidifier, air conditioning components, and fire protection components to regulate the cabinet environment; The face recognition monitoring unit is used to compare the collected operator's facial data with the pre-stored operator's facial data. If the facial data does not match, the control execution module controls the alarm to issue a false intrusion alarm prompt; The locking state monitoring unit is used to compare the actual locking state of the electrical cabinet with the preset locking state of the electrical cabinet. When the actual locking state of the electrical cabinet does not match the preset locking state of the electrical cabinet, the control execution module controls the alarm to give an error alarm prompt.

4. The intelligent monitoring system for electrical cabinets according to claim 1 is characterized in that: It also includes an electrical cabinet overall status assessment module, which includes: An evaluation value acquisition unit is used to obtain the power distribution response performance evaluation value, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the real-time power distribution parameters and cabinet environment parameters of the electrical cabinet collected by the data acquisition module, the facial data of the operator and the real-time locking status of the electrical cabinet; An evaluation matrix construction unit is used to construct an overall state evaluation matrix of the electrical cabinet based on the collected real-time power distribution parameters of the electrical cabinet and the environmental parameters inside the cabinet, the facial data of the operator, the real-time locking state of the electrical cabinet, the power distribution response performance evaluation value within the current monitoring period of the electrical cabinet, the environmental evaluation value inside the cabinet, the facial recognition accuracy evaluation value and the locking response sensitivity evaluation value of the electrical cabinet; The overall status analysis unit is used to evaluate the overall status of the electrical cabinet in the current monitoring period based on the overall status evaluation matrix of the electrical cabinet.

5. The intelligent monitoring system for electrical cabinets according to claim 4 is characterized in that: The evaluation value acquisition unit includes: The power distribution response performance evaluation subunit is used to obtain the power distribution response performance evaluation value of the electrical cabinet in the current monitoring period based on the collected real-time power distribution parameters of the electrical cabinet and the preset power distribution response performance evaluation model; The cabinet environment assessment subunit is used to obtain the cabinet environment assessment value of the electrical cabinet in the current monitoring period based on the collected real-time cabinet environment parameters of the electrical cabinet and the preset cabinet environment assessment model; A facial recognition accuracy evaluation subunit is used to obtain a facial recognition accuracy evaluation value of the electrical cabinet within a current monitoring period based on the collected facial data of the operator, the facial recognition result and a preset facial recognition accuracy evaluation model; The electrical cabinet locking response sensitivity evaluation subunit is used to obtain the electrical cabinet locking response sensitivity evaluation value within the current monitoring period of the electrical cabinet based on the collected real-time locking state parameters of the electrical cabinet and the preset electrical cabinet locking response sensitivity evaluation model.

6. The intelligent monitoring system for electrical cabinets according to claim 4, characterized in that: Based on the collection of real-time power distribution parameters and cabinet environment parameters of the electrical cabinet, facial data of operators, real-time locking status of the electrical cabinet, power distribution response performance evaluation value of the electrical cabinet in the current monitoring cycle, cabinet environment evaluation value, facial recognition accuracy evaluation value and electrical cabinet locking response sensitivity evaluation value, the overall status evaluation matrix of the electrical cabinet is constructed, including: Calculate the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring period, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring period, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring period, and the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring period; Based on the power distribution response performance sensor calculation value of the electrical cabinet in each monitoring cycle, the environmental control capability sensor calculation value of the electrical cabinet in each monitoring cycle, the facial recognition accuracy sensor calculation value of the electrical cabinet in each monitoring cycle, the locking response sensitivity sensor calculation value of the electrical cabinet in each monitoring cycle, the power distribution response performance evaluation value in each monitoring cycle, the cabinet environment evaluation value, the facial recognition accuracy evaluation value and the electrical cabinet locking response sensitivity evaluation value, an overall status evaluation matrix of the electrical cabinet is constructed.

7. An intelligent monitoring system for electrical cabinets according to claim 6, characterized in that: Based on the power distribution parameters of the electrical cabinet in the nth monitoring cycle, the power distribution response performance sensor calculation value of the electrical cabinet in the nth monitoring cycle is calculated: Where u is the total number of distribution parameters, a ni is the sensor detection value of the ith power distribution parameter in the nth monitoring cycle, a ni0 is the preset value of the ith power distribution parameter in the nth monitoring cycle; Based on the environmental parameters inside the electrical cabinet in the nth monitoring period, the calculated value of the environmental control capability sensor inside the electrical cabinet in the nth monitoring period is calculated: Where v is the total number of power distribution parameters, b ni is the sensor detection value of the ith environmental parameter in the nth monitoring period, b ni0 is the preset value of the ith environmental parameter in the nth monitoring period; Based on the total number of facial recognitions and the number of correct facial recognitions in the nth monitoring cycle, calculate the sensor calculation value of the electrical cabinet facial recognition accuracy in the nth monitoring cycle: Among them, M n is the total number of facial recognitions in the nth monitoring cycle, m n is the number of correct facial recognitions in the nth monitoring cycle; Based on the real-time locking state parameters of the electrical cabinet in the nth monitoring period, the calculated value of the locking response sensitivity sensor of the electrical cabinet in the nth monitoring period is calculated: Where w is the total number of power distribution parameters, c ni is the sensor detection value of the i-th locking state parameter in the n-th monitoring cycle, c ni0 It is the preset value of the i-th locking state parameter in the n-th monitoring cycle.

8. The intelligent monitoring system for electrical cabinets according to claim 6, characterized in that: The overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle: Among them, γ n is the overall status evaluation matrix of the electrical cabinet in the nth monitoring cycle, δ1 is the calculated value of the distribution response performance sensor of the electrical cabinet in the first monitoring cycle, δ2 is the calculated value of the distribution response performance sensor of the electrical cabinet in the second monitoring cycle, δ n is the calculated value of the distribution response performance sensor of the electrical cabinet in the nth monitoring cycle, ε1 is the calculated value of the environmental control capability sensor in the electrical cabinet in the first monitoring cycle, ε2 is the calculated value of the environmental control capability sensor in the electrical cabinet in the second monitoring cycle, and ε n is the calculated value of the environmental control capability sensor in the electrical cabinet in the nth monitoring cycle, α1 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the first monitoring cycle, α2 is the calculated value of the facial recognition accuracy sensor in the electrical cabinet in the second monitoring cycle, and α n is the calculated value of the facial recognition accuracy sensor of the electrical cabinet in the nth monitoring cycle, β1 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the first monitoring cycle, β2 is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the second monitoring cycle, β n is the calculated value of the lock response sensitivity sensor of the electrical cabinet in the nth monitoring cycle, A1 is the distribution response performance evaluation value in the first monitoring cycle, A2 is the distribution response performance evaluation value in the second monitoring cycle, and A n is the distribution response performance evaluation value in the nth monitoring cycle, B1 is the cabinet environment evaluation value in the first monitoring cycle, B2 is the cabinet environment evaluation value in the second monitoring cycle, and B n is the evaluation value of the cabinet environment in the nth monitoring cycle, C1 is the evaluation value of the facial recognition accuracy in the first monitoring cycle, C2 is the evaluation value of the facial recognition accuracy in the second monitoring cycle, and C n is the facial recognition accuracy evaluation value in the nth monitoring cycle, D1 is the electrical cabinet locking response sensitivity evaluation value in the first monitoring cycle, D2 is the electrical cabinet locking response sensitivity evaluation value in the second monitoring cycle, and D n It is the evaluation value of the locking response sensitivity of the electrical cabinet in the nth monitoring cycle.

9. An intelligent monitoring system for electrical cabinets according to claim 8, characterized in that: Overall status analysis unit, including: The intermediate matrix acquisition subunit deletes the corresponding elements of each type of performance calculation value and each type of performance evaluation value in all matrix elements in the overall status evaluation matrix of the electrical cabinet in the nth monitoring period, and obtains the intermediate matrix corresponding to each type of performance; The primary and secondary classification subunit compares the rank of the intermediate matrix corresponding to each type of performance with the preset evaluation value of each type of performance. If the rank of the intermediate matrix corresponding to each type of performance is greater than the preset evaluation value of each type of performance, it is a primary performance item, otherwise it is a secondary performance item; An overall state calculation unit, used to calculate the current overall state coefficient of the electrical cabinet based on the evaluation values ​​corresponding to the main performance items and the secondary performance items; The overall state evaluation and judgment unit issues a cabinet replacement alarm when the current overall state coefficient of the electrical cabinet is less than the preset current overall state coefficient of the electrical cabinet.

10. An intelligent monitoring system for electrical cabinets according to claim 9, characterized in that: The overall status coefficient of the electrical cabinet in the nth monitoring cycle: Among them, e is a natural number, f n is the number of secondary performance items, F n is the number of main performance items, lg is the logarithm with base 10, λ nj0 is the preset evaluation value corresponding to the jth main performance item in the nth monitoring period, λ nj It is the evaluation value corresponding to the jth main performance item in the nth monitoring cycle.

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