Intelligent electric appliance cabinet management and control method

Abstract

The application discloses an intelligent electric appliance cabinet management and control method applied to an intelligent electric appliance cabinet management and control system, and comprises a data collection module, an intelligent monitoring module and a communication management module, characterized by that the data collection module is used for collecting identity authentication data of management personnel and comprehensive monitoring data of electric equipment; the intelligent monitoring module is used for monitoring whether there is a stranger around the electric appliance cabinet and verifying identity information of an electric appliance cabinet operator; the communication management module is used for managing a communication channel and a communication node of the electric appliance cabinet and reducing communication time delay of the electric appliance cabinet; the data collection module, the intelligent monitoring module and the communication management module are mutually communicated and connected; the data collection module comprises a data acquisition module, a visual module and a sensor module; the data acquisition module is used for collecting setting data of the electric appliance cabinet; and the visual module is used for collecting visual images around the electric appliance cabinet. The application has the characteristics of high safety and low time delay.

Description

Intelligent appliance cabinet management and control methods Technical Field

[0001] This invention relates to the field of electrical appliance cabinet management technology, specifically to an intelligent electrical appliance cabinet control method. Background Technology

[0002] Electrical cabinets are the final-level devices in power distribution systems. With the rapid development of internet technology, power distribution systems are gradually becoming more intelligent. Currently, most power distribution systems are equipped with intelligent monitoring systems. However, existing technologies can only passively monitor the safety of electrical cabinets and cannot actively identify and remove them, which still poses significant safety hazards. Some electrical cabinets are located outdoors, making them susceptible to vandalism. Furthermore, when power is cut off in factories for equipment maintenance, the careless behavior of some workers can easily lead to accidental contact with electrical cabinets, endangering the lives of maintenance workers. Moreover, for ease of maintenance, most companies' electrical cabinets are located on the same local area network. Due to limited network resources, a large number of electrical cabinets will compete for network resources, resulting in some electrical cabinets occupying only a small portion of the network resources, causing data transmission congestion and large response delays. Therefore, it is essential to design an intelligent electrical cabinet management method with high security and low latency. Summary of the Invention

[0003] The purpose of this invention is to provide a method for controlling intelligent electrical appliance cabinets to solve the problems mentioned in the background art.

[0004] To address the aforementioned technical problems, the present invention provides the following technical solution: a method for controlling an intelligent appliance cabinet, comprising a data collection module, an intelligent monitoring module, and a communication management module, characterized in that: the data collection module is used to collect identity verification data of management personnel and comprehensive monitoring data of electrical equipment; the intelligent monitoring module is used to monitor whether strangers appear around the appliance cabinet and verify the identity information of the appliance cabinet operator; the communication management module is used to manage the communication channels and communication nodes of the appliance cabinet and reduce the communication latency of the appliance cabinet; the data collection module, the intelligent monitoring module, and the communication management module are interconnected.

[0005] The safety monitoring module includes a visual detection submodule and an equipment detection submodule. The visual detection submodule is used to detect whether there are strangers around the electrical cabinet, and the equipment detection submodule is used to detect whether the operating data of the electrical cabinet is abnormal.

[0006] The access control module includes a maintenance detection submodule and an access verification submodule. The maintenance detection submodule is used to detect whether the enterprise's electrical equipment is under maintenance, adjust the electrical cabinet to maintenance mode and lock it. The access verification submodule is used to verify the identity information and permissions of the electrical cabinet operator.

[0007] According to the above technical solution, the data collection module includes a data acquisition module, a vision module, and a sensor module. The data acquisition module is used to collect the setting data of the electrical cabinet, the vision module is used to collect visual images around the electrical cabinet, and the sensor module is used to collect the comprehensive operating data of the electrical cabinet.

[0008] According to the above technical solution, the intelligent monitoring module includes a safety monitoring module and an access control module. The safety monitoring module is used to monitor the impact of external forces and the electrical cabinet itself on the operation of the electrical cabinet. The access control module is used to verify the operator's identity according to the operating mode of the electrical cabinet.

[0009] According to the above technical solution, the communication management module includes a communication channel selection module, which is used to select a communication channel based on the data volume of the electrical cabinet and the remaining network channel resources.

[0010] According to the above technical solution, the communication management module further includes a node adjustment module and a communication module. The node adjustment module is used to adjust the load balance between communication nodes, and the communication module is used to send alarm information to the administrator when the electrical equipment fails.

[0011] According to the above technical solution, the intelligent appliance cabinet management and control method mainly includes the following steps:

[0012] Step S1: Collect the identity information of the electrical cabinet operator through the data acquisition module; capture visual images of the area around the electrical cabinet in real time through the vision module and capture visual images of the target object locked according to the system guidance; and collect the operating status data of the electrical components inside the electrical cabinet in real time through the sensor module.

[0013] Step S2: After data collection is completed, the system starts the security monitoring module to analyze whether there are strangers in the visual images around the electrical cabinet. Based on the analysis results, strangers are driven away. The system also analyzes the supply and demand relationship between the electrical cabinet and the electrical equipment and adjusts the power supply to the electrical cabinet based on the analysis results.

[0014] Step S3: When the electrical equipment is under maintenance, the access control module is activated, begins to analyze the setting mode of the electrical cabinet, verifies the operator's identity information, and responds to the operator's operation based on the analysis results;

[0015] Step S4: When the system is processing and transmitting data, the system sends an electrical signal to start the communication management module, which begins to analyze the size of the transmitted data and the load of the transmission channel, and adjusts the data communication channel and processing node according to the analysis results.

[0016] According to the above technical solution, step S2 further includes the following steps:

[0017] Step S21: Retrieve visual images around the intelligent electrical cabinet, periodically crop the visual images according to the frame rate set by the system, identify the feature nodes of the cropped images, and compare the feature nodes of adjacent images. When the similarity is less than the system-set threshold, the non-overlapping parts are marked. The system anchors the marked area of ​​the visual image, scans and identifies the marked feature nodes in the marked area, connects the marked feature nodes to construct a contour model, and compares it with the operator contour model in the database. If there is an operator contour model in the database with a matching degree greater than the system-set threshold, the operator's position in the power distribution room model is marked; otherwise, the marking is removed, and the system continues to monitor. When the similarity is greater than the system-set threshold, the system continues to monitor.

[0018] Step S22: When there is an operator profile model in the database with a matching degree greater than the threshold, retrieve the power distribution room model, establish a coordinate system, and calculate the distance L between the electrical cabinet and the target stranger using the distance formula. If the distance L between the electrical cabinet and the target stranger is greater than the second threshold, the system anchors the stranger's features and tracks the stranger's movement trajectory in real time. If the distance between the electrical cabinet and the stranger is less than the second threshold but greater than the first threshold, the system activates the expulsion device to expel the stranger and issues an alarm.

[0019] Step S23: Retrieve detailed parameters of the company's electrical equipment, analyze the historical power consumption data of the equipment, analyze the supply and demand relationship of the company's power distribution system, and adjust the power supply settings of the electrical cabinets according to the supply and demand relationship.

[0020] According to the above technical solution, in step S23, the power transmission distance between the electrical cabinet and the electrical equipment is retrieved, a historical database is searched based on the power transmission distance between the electrical cabinet and the electrical equipment, the power loss coefficient α during the power transmission process is given, the detailed parameters of the electrical equipment connected to the electrical cabinet are retrieved, and the rated voltage U of the electrical equipment is identified. 额 and rated current I 额 The voltage and current after transformer transformation are calculated using formulas. In the formula, U represents the voltage after the transformer transformation, and I represents the current after the transformer transformation. The voltage and current in the power supply system at this time are retrieved, and the conversion coefficient β in the database is searched based on the voltage and current in the power supply system at this time. The conversion mode of the transformer is set according to the conversion coefficient β, and the voltage and current in the power supply system are converted into the rated voltage and rated current of the electrical equipment.

[0021] According to the above technical solution, step S3 further includes the following steps:

[0022] Step S31: Retrieve real-time operating information data of the electrical equipment, identify the temperature and operating status of the electrical equipment. If the operating temperature of the electrical equipment is greater than the threshold, the system controls the electrical cabinet to cut off the power for maintenance. Otherwise, the electrical equipment continues to operate. When the operating status of the electrical equipment is down, retrieve the visual image of the electrical equipment, scan and identify human feature nodes in the visual image. If human feature nodes are present in the visual image, the electrical equipment is marked as being under maintenance. Otherwise, it is marked as being damaged and requiring maintenance.

[0023] Step S32: Identify the operating mode set by the electrical cabinet. When the electrical cabinet is in operating mode, if the operator issues a command, the system will verify the operator's facial data by recording it. If the verification is successful, the operator's command will be allowed to enter the execution module; otherwise, the system will refuse to execute it. When the electrical cabinet is in maintenance mode, if the operator issues a command (i.e., when the enterprise's electrical equipment is being maintained), the system will identify the markings on the electrical equipment. If a "maintenance in progress" marking is found on the electrical equipment, the system will lock the execution module of the electrical cabinet. At the same time, the system will record the operator's facial data and send the facial data to the security management department through the communication module. Otherwise, the command will be loaded into the execution module after the permission verification is successful.

[0024] According to the above technical solution, in step S4, the historical transmission data records of the electrical cabinet are retrieved, the number of bytes of the historical transmission data is scanned, and the dispersion of the historical transmission data is calculated using a formula. In the formula, i = 1, 2, 3, ..., n, P represents the dispersion of historical transmitted data, and M represents the number of bytes of historical transmitted data of the electrical cabinet. This represents the average number of bytes of historical data transmitted by the electrical cabinet. If the dispersion of the historical data transmitted by the electrical cabinet exceeds a system-set threshold, it is removed from the cluster head candidate node; otherwise, the cluster head rating of the electrical cabinet is calculated using a formula. In the formula, W represents the cluster head rating of the electrical cabinet, λ represents the weighting coefficient of the dispersion of historical transmitted data, and κ represents the weighting coefficient of the average number of bytes of historical transmitted data of the electrical cabinet. The highest-rated node is selected as the cluster head node. The system allocates CPU cores and memory resources to the processing nodes according to the node rating and retrieves the load rate of the processing nodes in the cluster. If the load rate of the processing node is greater than the system-set threshold, the data of the processing node is transmitted to the cluster head node; otherwise, the data is transmitted by the current processing node.

[0025] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: By detecting changes around the electrical cabinet, this invention can quickly and accurately determine whether a stranger is present around the cabinet, thereby preventing strangers from damaging it and greatly improving the cabinet's security. By analyzing the distance between the cabinet and the target stranger in real time, it activates a repulsion device to issue an alarm, driving the stranger away from the cabinet and significantly enhancing its security. By setting the transformer's conversion mode using the conversion coefficients before and after voltage and current conversion within the cabinet, it ensures that the voltage and current output by the cabinet are suitable for the operation of the electrical equipment, preventing excessive voltage or current from being used. The equipment overheating and even fire hazards greatly enhance the safety of the electrical cabinet. By verifying the operator's identity and permissions, it is possible to prevent unauthorized operation of the electrical cabinet, which could lead to equipment malfunctions and endanger the safety of production workers. By locking the execution module of the electrical cabinet, it is possible to prevent technicians from accidentally touching the cabinet while maintaining the equipment, which could cause injury to the technicians and further improve the safety of the equipment. By allocating resources to nodes based on the dispersion and average data transmission volume of the processing nodes, it is possible to prevent electrical cabinets from competing for resources, which could prevent some electrical cabinets from obtaining enough resources to transmit data, thereby greatly reducing the system's data transmission latency. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 is a schematic diagram of the system module composition of the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Please refer to Figure 1. The present invention provides a technical solution: an intelligent appliance cabinet management and control method, including a data collection module for collecting identity verification data of management personnel and comprehensive monitoring data of electrical equipment, an intelligent monitoring module for monitoring whether there are strangers around the appliance cabinet and verifying the identity information of the appliance cabinet operator, a communication management module for managing the communication channels and communication nodes of the appliance cabinet and reducing the communication latency of the appliance cabinet, and the data collection module, intelligent monitoring module and communication management module are interconnected.

[0030] The safety monitoring module includes a visual inspection submodule and an equipment inspection submodule. The visual inspection submodule is used to detect whether there are strangers around the electrical cabinet, and the equipment inspection submodule is used to detect whether the operating data of the electrical cabinet is abnormal.

[0031] The access control module includes a maintenance detection submodule and an access verification submodule. The maintenance detection submodule is used to detect whether the company's electrical equipment is under maintenance, adjust the electrical cabinet to maintenance mode and lock it. The access verification submodule is used to verify the identity information and permissions of the electrical cabinet operator.

[0032] The data collection module includes a data acquisition module, a vision module, and a sensor module. The data acquisition module is used to collect the setting data of the electrical cabinet, the vision module is used to collect visual images of the area around the electrical cabinet, and the sensor module is used to collect comprehensive operating data of the electrical cabinet.

[0033] The intelligent monitoring module includes a safety monitoring module and an access control module. The safety monitoring module is used to monitor the impact of external forces and the electrical cabinet itself on the operation of the electrical cabinet. The access control module is used to verify the operator's identity based on the operating mode of the electrical cabinet.

[0034] The communication management module includes a communication channel selection module, which is used to select a communication channel based on the data volume of the electrical cabinet and the remaining network channel resources.

[0035] The communication management module also includes a node adjustment module and a communication module. The node adjustment module is used to adjust the load balance between communication nodes, and the communication module is used to send alarm information to the administrator when the electrical equipment fails.

[0036] The intelligent appliance cabinet management and control method mainly includes the following steps:

[0037] Step S1: Collect the identity information of the electrical cabinet operator through the data acquisition module; capture visual images of the area around the electrical cabinet in real time through the vision module and capture visual images of the target object locked according to the system guidance; and collect the operating status data of the electrical components inside the electrical cabinet in real time through the sensor module.

[0038] Step S2: After data collection is completed, the system starts the security monitoring module to analyze whether there are strangers in the visual images around the electrical cabinet. Based on the analysis results, strangers are driven away. The system also analyzes the supply and demand relationship between the electrical cabinet and the electrical equipment and adjusts the power supply to the electrical cabinet based on the analysis results.

[0039] Step S3: When the electrical equipment is under maintenance, the access control module is activated, begins to analyze the setting mode of the electrical cabinet, verifies the operator's identity information, and responds to the operator's operation based on the analysis results;

[0040] Step S4: When the system is processing and transmitting data, the system sends an electrical signal to start the communication management module, which begins to analyze the size of the transmitted data and the load of the transmission channel, and adjusts the data communication channel and processing node according to the analysis results.

[0041] Step S2 further includes the following steps:

[0042] Step S21: Retrieve visual images around the intelligent electrical cabinet, periodically crop the visual images according to the frame rate set by the system, identify the feature nodes of the cropped images, and compare the feature nodes of adjacent images. When the similarity is less than the system-set threshold, the non-overlapping parts are marked. The system anchors the marked area of ​​the visual image, scans and identifies the marked feature nodes in the marked area, connects the marked feature nodes to construct a contour model, and compares it with the operator contour model in the database. If there is an operator contour model in the database with a matching degree greater than the system-set threshold, it means that the marked model is a stranger, and the stranger's position in the power distribution room model is marked. Otherwise, the marking is removed, and the system continues to monitor. When the similarity is greater than the system-set threshold, it means that there is no abnormality in the current area, and the system continues to monitor. By detecting changes around the electrical cabinet, it is possible to quickly and accurately determine whether a stranger has appeared around the electrical cabinet, thereby preventing strangers from damaging the electrical cabinet and greatly improving the security of the electrical cabinet.

[0043] Step S22: When an operator profile model with a matching degree greater than the threshold exists in the database, the power distribution room model is retrieved, a coordinate system is established, and the distance L between the electrical cabinet and the target stranger is calculated using the distance formula. If the distance L between the electrical cabinet and the target stranger is greater than the second threshold, the system anchors the stranger's features and tracks the stranger's movement trajectory in real time. If the distance between the electrical cabinet and the stranger is less than the second threshold but greater than the first threshold, the system activates the expulsion device to expel the stranger and issues an alarm. By analyzing the distance between the electrical cabinet and the target stranger in real time and activating the expulsion device to issue an alarm, the target stranger can be expelled from the electrical cabinet, greatly enhancing the security of the electrical cabinet.

[0044] Step S23: Retrieve detailed parameters of the company's electrical equipment, analyze the historical power consumption data of the equipment, analyze the supply and demand relationship of the company's power distribution system, and adjust the power supply settings of the electrical cabinets according to the supply and demand relationship.

[0045] In step S23, the power transmission distance between the electrical cabinet and the electrical equipment is retrieved. Based on this distance, a historical database is searched to obtain the power loss coefficient α during power transmission. Detailed parameters of the electrical equipment connected to the electrical cabinet are then retrieved, and the rated voltage U of the equipment is identified. 额 and rated current I 额The voltage and current after transformer transformation are calculated using formulas. In the formula, U represents the voltage after the transformer transformation, and I represents the current after the transformer transformation. The voltage and current in the power supply system at this time are retrieved, and the conversion coefficient β in the database is searched based on the voltage and current in the power supply system at this time. The conversion mode of the transformer is set according to the conversion coefficient β, and the voltage and current in the power supply system are converted into the rated voltage and rated current of the electrical equipment. By setting the conversion mode of the transformer through the conversion coefficient before and after the voltage and current conversion in the electrical cabinet, the voltage and current output by the electrical cabinet can be made suitable for the operation of the electrical equipment, avoiding the electrical equipment from overheating or even causing a fire due to excessive voltage or current output by the electrical cabinet, which greatly improves the safety of the electrical cabinet.

[0046] Step S3 further includes the following steps:

[0047] Step S31: Retrieve real-time operating information data of the electrical equipment, identify the temperature and operating status of the electrical equipment. If the operating temperature of the electrical equipment is greater than the threshold, the system controls the electrical cabinet to cut off the power for maintenance. Otherwise, the electrical equipment continues to operate. When the operating status of the electrical equipment is down, retrieve the visual image of the electrical equipment, scan and identify human feature nodes in the visual image. If human feature nodes are present in the visual image, the electrical equipment is marked as being under maintenance. Otherwise, it is marked as being damaged and requiring maintenance.

[0048] Step S32: Identify the operating mode set by the electrical cabinet. When the electrical cabinet is in operating mode, if the operator issues a command, the system will verify the operator's facial data by recording it. If the verification is successful, the operator's command is allowed to enter the execution module; otherwise, the system will refuse to execute it. When the electrical cabinet is in maintenance mode, if the operator issues a command (i.e., when the company's electrical equipment is being maintained), the system will identify the markings on the electrical equipment. If a "Maintenance in Progress" marking is present, it indicates that the technician is still maintaining the equipment. The system will lock the execution module of the electrical cabinet and simultaneously record the operator's facial data, which will be sent to the safety management department via the communication module. Otherwise, the command will be loaded into the execution module after the permission verification is successful. By verifying the operator's identity and permissions, the system can prevent unauthorized personnel from operating the electrical cabinet, which could lead to equipment malfunctions and endanger the safety of production workers. By locking the execution module of the electrical cabinet, the system can prevent technicians from accidentally touching the electrical cabinet while maintaining the equipment, which could cause injury to the technicians and further improve equipment safety.

[0049] In step S4, the historical transmission data records of the electrical cabinet are retrieved, the number of bytes in the historical transmission data is scanned, and the dispersion of the historical transmission data is calculated using a formula. In the formula, i = 1, 2, 3, ..., n, P represents the dispersion of historical transmitted data, and M represents the number of bytes of historical transmitted data of the electrical cabinet. This indicates the average number of bytes of historical data transmitted by the electrical cabinet. This represents the average number of bytes of historical data transmitted by the electrical cabinet. If the dispersion of the historical data transmitted by the electrical cabinet exceeds a system-set threshold, it is removed from the cluster head candidate node; otherwise, the cluster head rating of the electrical cabinet is calculated using a formula. In the formula, W represents the cluster head rating of the appliance cabinet, λ represents the weighting coefficient of the dispersion of historical transmitted data, and κ represents the weighting coefficient of the average number of bytes of historical transmitted data of the appliance cabinet. The highest-rated node is selected as the cluster head node. The system allocates CPU cores and memory resources to the processing nodes according to the node rating and retrieves the load rate of the processing nodes in the cluster. If the load rate of the processing node is greater than the system-set threshold, the data of the processing node is transmitted to the cluster head node. Otherwise, the current processing node transmits the data. By allocating resources to nodes according to the dispersion and average amount of transmitted data of the processing nodes, it is possible to avoid appliance cabinets competing for resources, which would prevent some appliance cabinets from obtaining enough resources to transmit data, thereby greatly reducing the data transmission latency of the system.

[0050] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0051] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for controlling an intelligent appliance cabinet, applied to an intelligent appliance cabinet control system, comprising a data collection module, an intelligent monitoring module, and a communication management module, characterized in that: The data collection module is used to collect identity verification data of management personnel and comprehensive monitoring data of electrical equipment. The intelligent monitoring module is used to monitor whether there are strangers around the electrical cabinet and verify the identity information of the operator controlling the electrical cabinet. The communication management module is used to manage the communication channels and communication nodes of the electrical cabinet and reduce the communication latency of the electrical cabinet. The data collection module, intelligent monitoring module, and communication management module are interconnected. The intelligent monitoring module includes a safety monitoring module and an access control module. The safety monitoring module is used to monitor the impact of external factors and the electrical cabinet itself on the operation of the electrical cabinet. The access control module is used to verify the operator's identity according to the operating mode of the electrical cabinet. The safety monitoring module includes a visual inspection submodule. The system includes a block and equipment detection submodule. The visual detection submodule detects the presence of strangers around the electrical cabinet, and the equipment detection submodule detects abnormal operating data of the electrical cabinet. The access control module includes a maintenance detection submodule and an access verification submodule. The maintenance detection submodule detects whether the enterprise's electrical equipment is under maintenance, adjusts the electrical cabinet to maintenance mode, and locks it. The access verification submodule verifies the identity and permissions of the electrical cabinet operator. The data collection module includes a data acquisition module, a vision module, and a sensor module. The data acquisition module collects the set data of the electrical cabinet, the vision module collects visual images of the area around the electrical cabinet, and the sensor module collects comprehensive data about the electrical cabinet. The operation data; the communication management module includes a communication channel selection module, which is used to select a communication channel based on the data volume of the electrical cabinet and the remaining network channel resources; the communication management module also includes a node adjustment module and a communication module, the node adjustment module is used to adjust the load balancing between communication nodes, and the communication module is used to send alarm information to the administrator when the electrical equipment fails; the intelligent electrical cabinet control method mainly includes the following steps: Step S1: Collect the identity information of the electrical cabinet operator through the data acquisition module, capture real-time visual images of the area around the electrical cabinet through the vision module and capture visual images of the target object locked according to the system guidance through the system, and collect real-time data of the electrical components inside the electrical cabinet through the sensor module. Step S2: After data collection is completed, the system starts the safety monitoring module to analyze whether there are strangers in the visual images around the electrical cabinet. Based on the analysis results, strangers are expelled. The system also analyzes the supply and demand relationship between the electrical cabinet and the electrical equipment and adjusts the power supply to the electrical cabinet based on the analysis results. Step S3: When the electrical equipment is under maintenance, the access control module starts to analyze the setting mode of the electrical cabinet, verifies the operator's identity information, and responds to the operator's operations based on the analysis results. Step S4: When the system is processing and transmitting data, the system sends an electrical signal to start the communication management module to analyze the size of the transmitted data and the load of the transmission channel. Based on the analysis results, the system adjusts the data communication channel and processing nodes.Step S2 further includes the following steps: Step S21: Retrieve visual images of the area surrounding the intelligent electrical cabinet, periodically crop the visual images according to the frame rate set by the system, identify the feature nodes of the cropped images, compare the feature nodes of adjacent images, and mark the non-overlapping parts when the similarity is less than the system-set threshold. The system anchors the marked area of ​​the visual image, scans and identifies the marked feature nodes in the marked area, connects the marked feature nodes to construct a contour model, and compares it with the operator contour model in the database. If there is no operator contour model in the database with a matching degree greater than the system-set threshold, the position of the stranger in the power distribution room model is marked; otherwise, the marking is removed, and the system continues monitoring. When the similarity is greater than the system-set threshold, the system continues monitoring. Step S22: When there is no operator contour model in the database with a matching degree greater than the system-set threshold, retrieve the power distribution room... The system establishes a coordinate system and calculates the distance L between the appliance cabinet and the target stranger using a distance formula. If the distance L is greater than a second threshold, the system anchors the stranger's characteristics and tracks the stranger's movement trajectory in real time. If the distance is less than the second threshold but greater than the first threshold, the system activates the expulsion device to expel the stranger and issues an alarm. Step S23: Retrieve detailed parameters of the enterprise's electrical equipment, analyze the historical power consumption data of the equipment, analyze the supply and demand relationship of the enterprise's power distribution system, and adjust the power supply settings of the appliance cabinet according to the supply and demand relationship. In step S23, the system retrieves the power transmission distance between the appliance cabinet and the electrical equipment, searches the historical database based on the power transmission distance between the appliance cabinet and the electrical equipment, provides the power loss coefficient α during the power transmission process, retrieves detailed parameters of the electrical equipment connected to the appliance cabinet, and identifies the rated voltage U of the electrical equipment. 额 and rated current I 额 The voltage and current after transformer transformation are calculated using formulas. In the formula, U represents the voltage after the transformer transformation, and I represents the current after the transformer transformation. The voltage and current in the power supply system at this time are retrieved, and the conversion coefficient β in the database is searched based on the voltage and current in the power supply system at this time. The conversion mode of the transformer is set according to the conversion coefficient β, and the voltage and current in the power supply system are converted into the rated voltage and rated current of the electrical equipment.

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