A high-low voltage power distribution cabinet stop power transmission safety operation system and method based on a double-check mechanism

Abstract

The application discloses a high-low voltage power distribution cabinet stop power supply safety operation system and method based on a double-checking mechanism, relates to the power distribution cabinet stop power supply technology field, and comprises four modules of power grid data acquisition networking, double-closed loop pre-checking, automatic operation execution, double-closed loop post-checking and data storage. The physical state, electrical parameters and power grid environment data of the power distribution cabinet are collected through a sensing subsystem and a collaborative autonomous network, the double-closed loop checking threshold is initially set and dynamically optimized, and the pre-operation safety condition is evaluated in combination with a fault-tolerant mechanism. If the condition is met, the robot is driven to perform automatic operation, if the condition is not met, the operation is rechecked after hierarchical treatment; and the effect is verified and stored through secondary double-closed loop checking after the operation is completed. The physical and electrical double-closed loop checking system is innovatively constructed, the working condition and the equipment state are dynamically adapted, the operation safety and the accuracy are improved, the invalid shutdown is reduced through hierarchical treatment and the fault-tolerant mechanism, and the operation and maintenance efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of power distribution cabinet power outage and restoration technology, specifically to a safe operation system and method for power outage and restoration of high and low voltage power distribution cabinets based on a dual verification mechanism. Background Technology

[0002] In power system operation and maintenance, high- and low-voltage switchgear, as core equipment for power distribution and control, directly impacts the stable operation of the power grid and the personal safety of maintenance personnel through the safety and reliability of their power outage and restoration operations. However, current traditional power outage and restoration operation modes still suffer from various technical bottlenecks. Therefore, there is an urgent need for a power outage and restoration safety operation system with multi-dimensional dual closed-loop verification, dynamic threshold adaptation, high fault tolerance, tiered handling, and data closed-loop management.

[0003] Existing technology, such as the invention patent application with publication number CN109212346A, discloses a debugging method for a low-voltage intelligent distribution cabinet. The method involves five steps: First, parsing the data stored in the registers of electrical components and generating editable and non-editable data tables; second, automatically inspecting the addresses of electrical components under the intelligent distribution cabinet and generating equipment information reports for each scanned online electrical component; third, providing a detection function selection when an online electrical component is scanned; fourth, automatically displaying the online device address and device type of the current electrical component after the detection function selection, and accessing the corresponding data table based on the device address and device type; and fifth, realizing telemetry, remote adjustment, or remote control based on the corresponding data table. This method is applied to the low-voltage intelligent distribution cabinet for production verification, checking whether its network data link is properly connected and whether the equipment functions normally, performing initial equipment configuration, and generating a test report for convenient subsequent data management.

[0004] Regarding the above-mentioned solutions, the applicant of this invention has found that the above-mentioned technologies have at least the following technical problems: 1. In the power outage and restoration verification of distribution cabinets, the existing technologies mostly focus on the single-dimensional detection of electrical parameters such as voltage and current, neglecting the key impact of the physical condition of the cabinet on operational safety. Traditional solutions do not incorporate physical characteristics such as wear of the operating target, cabinet deformation, and nameplate matching into the core verification system, and only rely on whether the electrical parameters meet the standards to judge the feasibility of the operation. This can easily lead to accidental contact with live parts by mechanical operation due to "misidentification of the cabinet" or "excessive positioning deviation", or jamming or malfunction caused by wear of the operating target, which can induce safety accidents such as electric shock and short circuit. It is impossible to form a full-dimensional safety protection of "physical condition + electrical parameters".

[0005] 2. Existing verification thresholds are mostly statically set based on equipment rated parameters, without being dynamically adjusted in conjunction with real-time operating conditions, making it difficult to adapt to the complex and ever-changing power grid operating environment. On the one hand, they do not consider the differences in the equipment's own state. For example, using the same threshold standard for old equipment and newly commissioned equipment cannot match the safety redundancy requirements of equipment with different aging levels. On the other hand, they do not link real-time power grid environment (such as total load factor and ambient humidity) with equipment operating status (such as temperature and partial discharge). During high-load periods, thresholds that are too wide may lead to insufficient safety margins, while during low-load periods, thresholds that are too strict may cause misjudgments of normal equipment, significantly reducing operational efficiency and verification accuracy.

[0006] 3. Existing sensing systems mostly employ a single-path data acquisition mode, lacking robust redundancy design and fault-tolerant mechanisms. Sensors are susceptible to malfunctions or data anomalies due to temperature drift, signal interference, and equipment aging. Traditional technologies lack both multi-sensor redundancy backup systems and effective data fusion verification methods. If a sensor fails, the verification process is directly interrupted. Furthermore, existing technologies separate the detection and correction of data defects, failing to fully utilize the complementary characteristics of multi-source data. This makes it difficult to distinguish between "sensor failure" and "environmental interference," leading to false alarms and missed alarms, further reducing the reliability of verification results.

[0007] 4. Existing technologies often employ a "one-size-fits-all" approach to halt operations when equipment fails to meet safety requirements, lacking a risk-level-based tiered response mechanism. The same shutdown procedure is used for both critical risks like severe voltage exceedances and cabinet discharges, and minor anomalies such as slight threshold deviations and environmental interference. This results in both untimely handling of high-risk hazards and excessive intervention in low-risk situations, leading to reduced operational efficiency. Furthermore, the lack of a clear re-inspection logic after fault handling prevents precise matching of recovery paths based on fault type, resulting in repetitive and time-consuming workflows.

[0008] 5. Existing technologies lack a closed-loop data management system for the entire power outage and restoration process. Key information such as verification data, sensor status logs, fault handling records, and operation results are stored in a scattered manner, and some are not even retained long-term. This data lacks a unified standardized format and an immutable evidence storage mechanism, making it difficult to trace the root cause of problems during subsequent operation and maintenance, and failing to provide data support for equipment health status assessment. Furthermore, due to the lack of in-depth analysis of historical data, it is impossible to summarize fault occurrence patterns, hindering proactive optimization such as verification threshold optimization and work process improvement. This results in the technical solution remaining at a "passive handling" level for a long time, lacking continuous iteration capabilities. Summary of the Invention

[0009] To address the aforementioned technical shortcomings, the present invention aims to provide a safe operation system and method for power outages and restorations of high and low voltage distribution cabinets based on a dual-verification mechanism.

[0010] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In the first aspect, the present invention provides a high and low voltage distribution cabinet power outage and restoration safety operation system based on a dual verification mechanism, including the following modules: power grid data acquisition and networking module: used to collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, a collaborative autonomous network of edge controllers and digital twin platforms is deployed in each distribution cabinet to build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform.

[0011] Dual-loop pre-verification module: Used to acquire real-time data corresponding to each distribution cabinet, initially set the dual-loop verification threshold for each distribution cabinet, and analyze the final optimized threshold corresponding to the dual-loop verification of each distribution cabinet, thereby evaluating whether each distribution cabinet needs to trigger the fault tolerance mechanism and determining whether each distribution cabinet meets the pre-safety conditions for power outage and restoration operations.

[0012] Automated operation execution module: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, the module drives the power outage and restoration robot to perform the mechanical operation on that power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the module immediately suspends the operation process for that power distribution cabinet and, after handling the situation according to the levels of emergency intervention, data supplementation, and parameter optimization, re-executes the dual closed-loop pre-verification. The operation can only be restarted after the verification is passed. If the verification still fails after handling, the power distribution cabinet is locked and a fault report is generated.

[0013] Dual-loop post-verification and data storage module: After each power distribution cabinet completes the mechanical operation of power outage and restoration, it collects the physical status data and electrical parameter data of each power distribution cabinet after the operation, and completes a second dual-loop verification based on the dynamic adaptive verification threshold to verify whether the operation effect meets the standard.

[0014] In a second aspect, the present invention provides a method for safe operation of high and low voltage distribution cabinets for power outage and restoration based on a dual verification mechanism, comprising the following steps: Step 1: Power grid data acquisition and networking: Collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, deploy a collaborative autonomous network of edge controllers and digital twin platforms in each distribution cabinet, and build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform.

[0015] Step 2, Dual Closed-Loop Pre-Verification: Obtain real-time data for each distribution cabinet, initially set the dual closed-loop verification threshold for each distribution cabinet, and analyze the final optimized threshold corresponding to the dual closed-loop verification for each distribution cabinet. This will help assess whether each distribution cabinet needs to trigger a fault-tolerant mechanism and determine whether each distribution cabinet meets the pre-operation safety conditions for power outage and restoration.

[0016] Step 3: Automated Operation Execution: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, the power outage and restoration robot will be driven to perform the power outage and restoration mechanical operation on that power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the operation process for that power distribution cabinet will be immediately suspended. After handling the situation according to the classification of emergency intervention, data supplementation, and parameter optimization, the dual closed-loop pre-verification will be re-executed. The operation can only be restarted after the verification is passed. If the verification is still not passed after handling, the power distribution cabinet will be locked and a fault report will be generated.

[0017] Step 4: Dual-loop post-verification and data storage: After each distribution cabinet completes the mechanical operation of power supply and shutdown, the physical status data and electrical parameter data of each distribution cabinet after the operation are collected again. Based on the dynamic adaptive verification threshold, a second dual-loop verification is completed to verify whether the operation effect meets the standard.

[0018] The beneficial effects of this invention are as follows: 1. This embodiment of the solution breaks through the limitations of traditional single electrical parameter verification technology and innovatively establishes a dual closed-loop verification mechanism for spatial attitude and electrical parameters: The spatial attitude closed loop uses multimodal perception such as 3D vision and lidar to accurately verify the cabinet identity, operation target position and physical state, eliminating mechanical risks such as "misidentifying the wrong cabinet" and "accidentally touching live parts due to positioning deviation"; The electrical parameter closed loop combines the redundancy design of main and backup sensors and dynamic threshold adjustment to monitor key parameters such as voltage, current and partial discharge value in real time, avoiding electrical hazards such as "power outage under load" and "overvoltage power supply". At the same time, a sound fault tolerance mechanism is established for sensor failure scenarios. Through redundant data fusion and digital twin-assisted verification, the verification process is ensured to be uninterrupted and the results reliable, building "double insurance" from both physical and electrical dimensions, and significantly reducing the incidence of operational accidents.

[0019] 2. This solution abandons the traditional fixed threshold mode and dynamically optimizes the verification threshold based on equipment characteristics (years of operation, number of failures) and real-time operating conditions (temperature, load rate, humidity): thresholds are tightened for older equipment and during high-load periods to ensure safety redundancy, while thresholds are appropriately relaxed for low-load, non-core equipment to reduce misjudgments. Simultaneously, for distribution cabinets that do not meet safety conditions, a tiered handling plan is matched according to "safety risk level, fault impact range, and data anomaly degree"—critical risks trigger emergency intervention for rapid risk control, while minor anomalies are efficiently restored through data supplementation or parameter optimization, avoiding efficiency losses caused by "one-size-fits-all" shutdowns. This "precise adaptation + tiered handling" model ensures that the verification results closely match actual operating conditions and reduces fault handling time by more than 30%, significantly improving operation and maintenance efficiency.

[0020] 3. This embodiment of the solution achieves complete retention and tamper-proof management of data throughout the entire power outage and restoration process through a dual closed-loop post-verification and blockchain evidence storage module: from the initial data collection, threshold setting, and fault tolerance assessment, to the mid-term operation execution and fault handling, and then to the later secondary verification, all key data (sensor logs, verification results, and handling records) are uploaded to the digital twin platform and blockchain in real time. This provides a reliable basis for operation traceability, facilitating the investigation of the root cause of problems in the later stage; and through the accumulation of historical data, it can analyze the equipment failure patterns and threshold adaptation effects, feed back into the optimization of threshold setting logic and the improvement of sensor layout, and promote the system to iterate from "passive handling" to "proactive prevention", providing long-term data support and technical upgrade path for the operation and maintenance of the target power plant's distribution cabinet. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0023] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Detailed Implementation

[0024] 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.

[0025] Examples of embodiments of the present invention Figure 1 As shown, a high- and low-voltage switchgear power outage and restoration safety operation system based on a dual verification mechanism includes the following modules: a power grid data acquisition and networking module, a dual closed-loop pre-verification module, an automated operation execution module, and a dual closed-loop post-verification and data storage module.

[0026] The dual-closed-loop pre-verification module is connected to the power grid data acquisition and networking module and the automated operation execution module, respectively. The automated operation execution module is connected to the dual-closed-loop post-verification and data storage module.

[0027] Power grid data acquisition and networking module: used to collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, a collaborative autonomous network of edge controllers and digital twin platforms is deployed in each distribution cabinet to build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform.

[0028] In a specific embodiment, the deployment process of the collaborative autonomous network of edge controllers and digital twin platforms in each distribution cabinet is as follows: The digital twin platform is deployed on the cloud server of the target power plant, configured with a global data storage module and a super real-time simulation engine, and accesses the power plant's grid dispatch system to obtain the topology and load basic data of each distribution cabinet in the target power plant; the edge controllers are deployed in the distribution room of the target power plant, and according to the regional division principle, each distribution cabinet in the target power plant is divided into several control groups, each group containing 3-5 edge controllers corresponding to adjacent distribution cabinets, each group establishing a dedicated communication link with the digital twin platform, and the edge controllers within the same group building a P2P communication subnet.

[0029] Dual-loop pre-verification module: Used to acquire real-time data corresponding to each distribution cabinet, initially set the dual-loop verification threshold for each distribution cabinet, and analyze the final optimized threshold corresponding to the dual-loop verification of each distribution cabinet, thereby evaluating whether each distribution cabinet needs to trigger the fault tolerance mechanism and determining whether each distribution cabinet meets the pre-safety conditions for power outage and restoration operations.

[0030] In a specific embodiment, the initial setting of the dual closed-loop verification threshold for each distribution cabinet is as follows: obtain the operating years and historical fault counts of each distribution cabinet in the target power plant, and divide them into three scenarios.

[0031] It should be noted that by establishing data interfaces with the power plant asset management system (EAM) and equipment operation and maintenance management system (OMS) through the digital twin platform, the manufacturing date and commissioning acceptance records of the distribution cabinets are automatically obtained to calculate the service life (current date minus actual commissioning date). Simultaneously, historical data such as equipment operation and maintenance ledgers, fault reports, and maintenance records are retrieved to filter out downtime or abnormal events caused by electrical faults (such as short circuits and insulation failures) and mechanical faults (such as operational jamming and component damage). The cumulative number of faults is counted (repeated occurrences of the same fault are counted as single occurrences, excluding faults not caused by the equipment itself due to misoperation or temporary external environmental interference). For older distribution cabinets with missing data, the manufacturing date is identified through the cabinet nameplate, and the commissioning time is supplemented by feedback from on-site maintenance personnel. Historical fault counts are manually calculated by reviewing paper maintenance files and shift handover records. Finally, the integrated service life and fault count are linked to the unique identifier of each distribution cabinet (such as cabinet number), providing an accurate data foundation for subsequent equipment classification and threshold setting.

[0032] If the operating years and historical failure count of a certain power distribution cabinet are: operating years ≤ 2 years, historical failure count = 0, then it is classified as newly commissioned equipment. If the operating years and historical failure count of a certain power distribution cabinet are: 2 years < operating years ≤ 8 years, historical failure count ≤ 3 times, then it is classified as conventional equipment. If the operating years and historical failure count of a certain power distribution cabinet are: operating years > 8 years, historical failure count > 3 times, then it is classified as old equipment.

[0033] Basic thresholds are set for spatial attitude closed loop: positioning accuracy of newly commissioned equipment ≤ ±2mm, nameplate matching degree ≥ 99.8%; positioning accuracy of conventional equipment ≤ ±1.5mm, nameplate matching degree ≥ 99.5%; positioning accuracy of old equipment ≤ ±1mm, nameplate matching degree ≥ 99.8%.

[0034] It should be noted that the spatial attitude closed loop is a dynamic verification closed loop built by this solution to ensure the accuracy and physical safety of mechanical operation of power supply and shutdown of high and low voltage distribution cabinets. The core is to collect the physical state data of the cabinet through the multimodal perception module (3D vision sensor, lidar, force control sensor) carried by the power supply and shutdown robot, and complete the real-time verification and feedback adjustment in combination with the digital twin platform, so as to solve the risks of "misidentifying the wrong cabinet" and "accidentally touching live parts due to positioning deviation" in traditional operations. The specific logic is as follows: After the power outage / restoration robot moves to the target distribution cabinet, the 3D vision sensor collects the cabinet nameplate information to complete the identification, the lidar scans the operation target (opening / closing handle, grounding switch operation hole) and outputs three-dimensional coordinates, and the force control sensor provides contact feedback on the wear amount of the operation target and the deformation amount of the cabinet; the robot uploads the collected data to the edge controller in real time and compares it with the cabinet's three-dimensional model, reference coordinates and final optimization thresholds pre-stored in the digital twin platform. If the nameplate matching degree, positioning deviation and wear / deformation amount all meet the threshold requirements, the robot receives the "permit operation" command and executes the mechanical action; if the parameters exceed the standard, the robot immediately corrects the positioning path or stops the operation until the verification is passed. The entire process uses the robot as the physical data collection carrier and operation execution subject to achieve closed-loop verification of "data collection-threshold comparison-feedback adjustment-operation execution", ensuring the accuracy and safety of mechanical operation.

[0035] For closed-loop electrical parameter settings, the basic thresholds are as follows: voltage deviation ≤ ±1% and current deviation ≤ ±1% for newly commissioned equipment; voltage deviation ≤ ±2% and current deviation ≤ ±2% for conventional equipment; and voltage deviation ≤ ±0.8% and current deviation ≤ ±0.8% for older equipment.

[0036] It should be noted that the electrical parameter closed loop is a dynamic verification closed loop built by this solution for the electrical safety of high and low voltage distribution cabinets during power outages and restorations. The core is to collect electrical data through the main and backup dual-path sensor modules deployed in the distribution cabinet, dynamically adjust the thresholds in combination with the real-time operating conditions of the power grid, and form an operation permission linkage with the power outage and restoration robot to solve electrical risks such as "power outage under load" and "power restoration under overvoltage". The specific logic is as follows: The main and backup voltage / current sensors, temperature sensors, and partial discharge sensors of the sensing subsystem collect circuit electrical parameters in real time. After preprocessing by the edge controller, the parameters are uploaded to the digital twin platform and compared with the thresholds optimized based on equipment characteristics and power grid environment (total load rate, humidity). At the same time, the power outage and restoration safety logic is verified (e.g., current ≤ 0A before power outage operation, grounding switch opened before power restoration operation). If the parameters meet the thresholds and the logic verification is passed, the digital twin platform issues an "executable operation" command to the power outage and restoration robot. The robot starts the end effector such as the insulated crank and button operation head to complete the opening and closing operation. If the parameters exceed the standard or the logic conflicts, the system immediately sends a "stop operation" signal to the robot. After the electrical state is adjusted to a safe range, the system is re-verified. The robot only performs the operation after the closed-loop verification is passed. During the operation, the robot receives electrical parameter feedback in real time. If a sudden abnormality occurs, the robot stops immediately, realizing closed-loop control of "parameter acquisition - threshold verification - operation permission - real-time monitoring". The robot is used as the operation execution terminal to ensure the consistency of electrical safety and operation logic.

[0037] In a specific embodiment, the analysis of the final optimization threshold corresponding to the dual closed-loop verification of each distribution cabinet is carried out in the following specific analysis process: real-time electrical parameters, real-time physical state parameters and real-time power grid environment parameters corresponding to each distribution cabinet are obtained. The real-time electrical parameters include: current voltage, current, temperature and partial discharge value; the real-time physical state parameters include: wear amount of the operation target and cabinet deformation amount; the real-time power grid environment parameters include: total load rate and ambient humidity.

[0038] It should be noted that real-time electrical parameters (current voltage, current, temperature, and partial discharge value) are collected through "main and backup dual-path electrical sensing modules" deployed inside each distribution cabinet, and the data is transmitted and preprocessed in real time in conjunction with the edge controller. Main and backup voltage and current sensors are installed at the incoming and outgoing ends of each distribution cabinet, respectively, to collect loop voltage and current signals in real time through electromagnetic induction. Surface-mount temperature sensors are attached to key heat-generating parts such as cabinet contacts and busbars to collect real-time temperature through thermocouple effects. An ultrasonic partial discharge sensor is installed on the top inside the cabinet to detect ultrasonic signals generated by partial discharge and convert them into partial discharge values ​​(unit: pC). All electrical sensors are connected to the edge controller next to the distribution cabinet via an RS485 bus. The edge controller filters the collected raw data (removing jump values ​​caused by electromagnetic interference) and performs per-unit processing (converting the actual value to a ratio relative to the rated value), before uploading it to the digital twin platform in real time through a collaborative autonomous network.

[0039] Real-time physical state parameters (wear of the operating target and deformation of the cabinet) are collected jointly by the "multimodal perception module" on the power-off robot and a fixedly deployed LiDAR to achieve accurate detection of the physical state. Among them, the wear of the operating target (such as the wear of the opening and closing handle and the inner wall of the operating hole) is obtained through the collaborative acquisition of the force control sensor and 3D vision sensor on the robot's end effector: when the robot contacts the operating target, the force control sensor provides real-time feedback on the contact pressure distribution. If there is a local pressure anomaly (such as a reduction in contact area or pressure concentration due to wear), the depth and area of ​​the wear area are calculated by combining the point cloud data of the operating target surface captured by the 3D vision sensor, thereby determining the wear amount. The cabinet deformation is calculated by the LiDAR deployed on the top of the power distribution room (scanning range covering 3-5 adjacent power distribution cabinets) periodically scanning the cabinet outline. The real-time three-dimensional coordinates of the cabinet are compared with the coordinates of the standard cabinet model pre-stored in the digital twin platform to calculate the displacement deviation of key parts of the cabinet (such as cabinet doors and operating panels), which is the cabinet deformation. The physical state data collected by the robot is transmitted to the edge controller in real time via a wireless communication module (5G / industrial WiFi). The LiDAR data is directly connected to the edge controller. After data fusion (removing positional deviations caused by robot movement), the data is uploaded to the digital twin platform to ensure that the timestamps of the physical state parameters and electrical parameters are synchronized.

[0040] Real-time power grid environmental parameters (total load factor, ambient humidity) are jointly acquired through the "power grid dispatching system interface" and the "distribution room environmental sensor network", covering both macro-level power grid operating conditions and micro-level environmental conditions. The total load factor is retrieved in real time through a data interface established between the digital twin platform and the target power plant's grid dispatch system. The grid dispatch system periodically (collection cycle 5 minutes / time) outputs the real-time total active power of each bus in the target power plant. The digital twin platform compares this with the rated total capacity of the bus and calculates the total load factor using the formula "Total Load Factor = (Real-time Total Active Power / Rated Total Capacity) × 100%". At the same time, it associates the bus information of each distribution cabinet to accurately match the total load factor to the corresponding distribution cabinet. Ambient humidity is collected by temperature and humidity sensors deployed in the distribution room. The sensors are evenly distributed at a density of "one per 50㎡" to collect the relative humidity in the air in real time (measurement range 0~100%RH, accuracy ±2%RH). The data is transmitted to the area edge controller via a LoRa low-power network. The edge controller takes the average of the humidity data from multiple sensors in the same area as the real-time ambient humidity of all distribution cabinets in that area. Finally, it is uploaded to the digital twin platform to provide an environmental basis for threshold optimization (such as tightening the nameplate matching threshold when humidity ≥60%RH).

[0041] For the basic threshold of closed-loop electrical parameters: if the real-time temperature of a certain distribution cabinet is ≥70℃, tighten the voltage deviation and current deviation thresholds by 20%; if the partial discharge value is >5pC, tighten the voltage deviation and current deviation thresholds by 15%, and at the same time increase the verification frequency to twice the original frequency; if the real-time voltage / current is between 80% and 100% of the rated value, tighten the corresponding deviation threshold by 10%. For the basic threshold of closed-loop spatial attitude: real-time electrical parameters have no direct impact on the closed-loop spatial attitude, and the basic threshold remains unchanged.

[0042] Regarding the basic threshold for spatial attitude closed-loop: If the wear of the target operation corresponding to a certain distribution cabinet is ≥0.5mm, the positioning accuracy threshold is tightened by 30%; if the cabinet deformation is >1mm, the positioning reference is recalibrated using a digital twin model, and the positioning accuracy threshold is tightened by 20%; if the wear of the target operation is <0.5mm and the cabinet has no deformation, the basic threshold for spatial attitude closed-loop remains unchanged. Regarding the basic threshold for electrical parameter closed-loop: Real-time physical state parameters have no direct impact on electrical parameter closed-loop, and the basic threshold remains unchanged.

[0043] Regarding the basic thresholds for spatial attitude closed-loop control: If the ambient humidity is ≥60%RH, the nameplate matching threshold will be increased by 0.2%; the total load rate has no direct impact on spatial attitude closed-loop control, and the positioning accuracy threshold remains unchanged. Regarding the basic thresholds for electrical parameter closed-loop control: If the total load rate is ≥80%, the voltage deviation and current deviation thresholds for all distribution cabinets will be tightened by 30%; if the total load rate is <50%, the voltage deviation and current deviation thresholds for non-core load distribution cabinets will be relaxed by 10%, while the thresholds for core load distribution cabinets will remain unchanged; if the ambient humidity is ≥60%RH, the thresholds for insulation-related parameters will be tightened by 10%.

[0044] In a specific embodiment, the evaluation process for whether each power distribution cabinet needs to trigger a fault tolerance mechanism is as follows: real-time monitoring of the working status of each sensor in each power distribution cabinet in the sensing subsystem, including the working status of 3D vision sensors, LiDAR, voltage and current sensors, and generating sensor status logs.

[0045] For spatial attitude closed loop: Based on sensor status logs, if a power distribution cabinet detects that a single sensor is in a faulty or abnormal data state, and the status of other redundant sensors in the same closed loop is normal and the data integrity is ≥95%, it is assessed that the spatial attitude closed loop fault tolerance mechanism needs to be triggered; if a power distribution cabinet detects ≥2 sensors that are simultaneously in a faulty or abnormal data state, or the data integrity of redundant sensors is <95%, it is assessed that the fault tolerance mechanism has failed.

[0046] For closed-loop electrical parameters: Based on sensor status logs, if a distribution cabinet detects that the main voltage / current sensor is in a faulty or abnormal data state, and the backup sensor is in a normal state, supports seamless switching, and the data error after switching is ≤1%, then it is assessed that the closed-loop fault tolerance mechanism for electrical parameters needs to be triggered; if the main and backup sensors of a distribution cabinet are both in a faulty or abnormal data state, or the data error after switching the backup sensor is >1%, then it is assessed that the fault tolerance mechanism has failed.

[0047] Summarize the evaluation results of the spatial attitude closed loop and electrical parameter closed loop of a certain power distribution cabinet: If any closed loop requires triggering the fault tolerance mechanism and the other closed loop does not, then the overall output of the power distribution cabinet requires triggering the fault tolerance mechanism; if any closed loop is determined to have failed the fault tolerance mechanism, then the overall output fault tolerance mechanism of the power distribution cabinet fails; if neither closed loop requires triggering the fault tolerance mechanism, then the output of the power distribution cabinet does not need to trigger the fault tolerance mechanism; if the output of a certain power distribution cabinet requires triggering the fault tolerance mechanism or the fault tolerance mechanism fails, then analyze the corresponding handling measures for the power distribution cabinet.

[0048] In a specific embodiment, if the output of a certain power distribution cabinet needs to trigger the fault tolerance mechanism or the fault tolerance mechanism fails, the corresponding handling measures for the power distribution cabinet are analyzed. The specific analysis process is as follows: If the output of a certain power distribution cabinet needs to trigger the fault tolerance mechanism, a processing scheme of redundant data fusion + digital twin assistance is adopted.

[0049] It should be noted that when the power distribution cabinet output needs to trigger the fault tolerance mechanism, redundant data retrieval and digital twin model collaborative verification are immediately initiated to ensure that the verification process is uninterrupted and the results are accurate. When the spatial attitude closed loop triggers fault tolerance, the faulty sensor is disabled, and the remaining redundant sensors carried by the power supply robot are called (if 3D vision failure occurs, LiDAR + force control sensor is used). The LiDAR scans the cabinet outline and compares it with the 3D model pre-stored in the digital twin platform to confirm its identity. The force control sensor corrects the positioning deviation of the operation target through contact feedback. The fused data of the two completes the verification according to the final optimized threshold. When the electrical parameter closed loop triggers fault tolerance, the backup voltage / current sensor is automatically switched to within 100ms to synchronously collect auxiliary parameters such as temperature and partial discharge value in the same circuit. Combined with the electrical tolerance limit data of the equipment in the digital twin model for cross-verification, misjudgment caused by the abnormality of a single sensor is eliminated. If both closed loops trigger fault tolerance, the corresponding redundant verification is performed separately, and the results are summarized after independent judgment. At the same time, the faulty sensor model, fault tolerance data source and other information are uploaded to the blockchain for evidence storage.

[0050] If the fault tolerance mechanism of the power distribution cabinet fails, a full-process handling solution of suspending operation, issuing graded alarms, locating the root cause, precise handling, and restoring verification will be implemented.

[0051] It should be noted that when the fault tolerance mechanism of the distribution cabinet fails, all work processes on that distribution cabinet are immediately suspended, and operating permissions are locked to prevent accidental restarts. Subsequently, tiered alarms are triggered according to risk level: a level 1 alarm is triggered by a dual-loop failure or a core electrical sensor malfunction, with audible and visual signals pushed to the maintenance duty station and the on-duty supervisor; if there is no response within 5 minutes, it is automatically escalated to the dispatch center; a level 2 alarm is triggered by a single closed-loop failure, only pushed to the maintenance duty station. Next, the digital twin platform is invoked to invert the sensor failure process, combining historical maintenance data with the real-time power grid environment to locate the root cause of the fault (hardware damage, electromagnetic interference, or software anomaly). Maintenance personnel, carrying insulation testing tools, go to the site for precise handling: for hardware damage, replace the spare sensor and calibrate it through the edge controller; for electromagnetic interference, investigate and remove interference sources near the sensor; for software anomalies, restart the sensing subsystem or update the algorithm. After the handling is completed, the verification is re-executed according to the double closed-loop pre-verification process. If the verification passes, the unlocking operation process is completed. If the problem still cannot be resolved after 3 handling attempts, the distribution cabinet is locked, and a fault report containing the alarm cause, handling record and failed items is generated and transferred to the professional maintenance team for in-depth investigation.

[0052] In a specific embodiment, the determination process for whether each distribution cabinet meets the pre-operation safety conditions for power outage and restoration is as follows: Spatial attitude closed-loop verification: If a distribution cabinet does not require triggering a fault-tolerance mechanism, the nameplate information of the distribution cabinet collected by the 3D vision sensor and the coordinates of the operation target located by the lidar are directly compared with the final optimized threshold. If the nameplate matching degree is ≥ the threshold, the positioning deviation is ≤ the threshold, and the wear of the operation target and the deformation of the cabinet are ≤ the safety threshold, then the spatial attitude closed-loop is determined to be passed; if a distribution cabinet requires triggering a fault-tolerance mechanism, the redundant data fusion verification results are used. If the threshold requirements are met, it is determined to be passed; otherwise, it is determined to be failed.

[0053] Electrical parameter closed-loop verification: If a distribution cabinet does not require triggering a fault-tolerant mechanism, the voltage, current, temperature, and partial discharge values ​​of the distribution cabinet collected by the main circuit sensors are compared with the final optimized thresholds. If the values ​​comply with the power outage and restoration safety logic, the current before the power outage operation is ≤0A, there is no short-circuit current before the power restoration operation, and the grounding switch has been opened, then the electrical parameter closed-loop verification is considered successful. If a distribution cabinet requires triggering a fault-tolerant mechanism, the results of the backup circuit sensors and auxiliary parameters are cross-verified. If the results meet the thresholds and safety logic, the verification is considered successful; otherwise, the verification is considered unsuccessful.

[0054] If both types of closed loops of a power distribution cabinet pass the test, and the digital twin platform inputs the real-time data and final optimization threshold of the power distribution cabinet, and the pre-simulation of the power outage and restoration operation process has no path interference or electrical logic conflict, then the pre-conditions for power outage and restoration operation are deemed to be met. If any closed loop of a power distribution cabinet fails, or the fault tolerance mechanism fails, or there is a risk in the model simulation, then the pre-conditions for power outage and restoration operation are deemed not to be met.

[0055] Automated operation execution module: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, the module drives the power outage and restoration robot to perform the mechanical operation on that power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the module immediately suspends the operation process for that power distribution cabinet and, after handling the situation according to the levels of emergency intervention, data supplementation, and parameter optimization, re-executes the dual closed-loop pre-verification. The operation can only be restarted after the verification is passed. If the verification still fails after handling, the power distribution cabinet is locked and a fault report is generated.

[0056] In a specific embodiment, after the graded handling of emergency intervention, data supplementation and parameter optimization, the double closed-loop pre-verification is re-executed. The specific handling process is as follows: the safety risk level, fault impact range and data anomaly degree of the power distribution cabinet are mapped to the corresponding table of first-level risk, second-level risk and third-level risk classification.

[0057] If a power distribution cabinet has a safety risk level of Class I, a fault impact range of Class A, and a data anomaly level of Class X, it is determined to be a Level 1 risk, and emergency intervention and handling should be carried out for the power distribution cabinet.

[0058] If a power distribution cabinet has a safety risk level of Class III, a fault impact range of Class C, and a data anomaly level of Class Y, it is determined to be a Level II risk, and data supplementation and processing will be carried out for the power distribution cabinet.

[0059] If a power distribution cabinet has a safety risk level of Class IV, a fault impact range of Class C, and a data anomaly level of Class Z, it is determined to be a Level 3 risk, and parameter optimization measures will be taken for the power distribution cabinet.

[0060] It should be noted that the digital twin platform automatically extracts the dual closed-loop verification data, sensor status logs, and power grid topology information of the distribution cabinet. First, based on the quantified values ​​of electrical parameters (voltage / current deviation, temperature, partial discharge value) and physical conditions (wear of operating targets, cabinet deformation, nameplate matching degree), a safety risk level is generated by comparing it with the preset Class I (fatal risk) to Class IV (low risk) judgment criteria. Then, combined with its location in the power grid topology (such as bus tie cabinet / area cabinet / single cabinet) and fault type (whether the abnormal electrical parameters affect the same bus section, whether the abnormal physical condition affects adjacent equipment), the fault impact range of global impact (Class A), regional impact (Class B), or single cabinet impact (Class C) is matched. At the same time, by analyzing the sensor data jump amplitude, redundant data integrity, and environmental correlation, the degree of data anomaly is determined as severe anomaly (Class X), moderate anomaly (Class Y), or slight anomaly (Class Z). Subsequently, the platform calls the preset classification mapping table and uses the above three results as indexes for mapping: if the security risk level is Class I, the fault impact range is Class A, and the data anomaly degree is Class X, it is mapped to Level 1 risk; if the security risk level is Class III, the fault impact range is Class C, and the data anomaly degree is Class Y, it is mapped to Level 2 risk; if the security risk level is Class IV, the fault impact range is Class C, and the data anomaly degree is Class Z, it is mapped to Level 3 risk. Finally, the classification result is output and the corresponding handling process is triggered.

[0061] Dual-loop post-verification and data storage module: After each power distribution cabinet completes the mechanical operation of power outage and restoration, it collects the physical status data and electrical parameter data of each power distribution cabinet after the operation, and completes a second dual-loop verification based on the dynamic adaptive verification threshold to verify whether the operation effect meets the standard.

[0062] In a specific embodiment, the second double closed-loop verification based on the dynamic adaptive verification threshold is performed to verify whether the operation effect meets the standard. The specific verification process is as follows: After the operation is completed, the sensing subsystem collects the post-operation data of each power distribution cabinet again: the multimodal sensing module collects physical state data; the wireless electrical sensing module collects post-operation electrical parameter data. The data is preprocessed by the edge controller and then uploaded to the digital twin platform.

[0063] Secondary verification of spatial attitude closed loop: The final optimized threshold of each distribution cabinet is called to verify that the status of the opening and closing indicator lights is consistent with the operation command and that the position of the handcart meets the preset standard. If the fault tolerance mechanism is triggered, the verification is assisted by comparing the redundant sensor data and the digital twin model. If the requirements are met, the secondary verification of spatial attitude closed loop is determined to be passed.

[0064] Electrical parameter closed-loop secondary verification: The final optimized threshold of each distribution cabinet is called to verify that the electrical parameters meet the operation target after the operation. After the power outage operation, the voltage ≤ 0V and the current ≤ 0A; after the power restoration operation, the voltage / current is stable within the rated range, the deviation ≤ the final optimized threshold, the temperature ≤ the equipment tolerance upper limit, and the partial discharge value ≤ the safety threshold. If the fault tolerance mechanism is triggered, the backup sensor + auxiliary parameter cross-verification is adopted. If the requirements are met, the electrical parameter closed-loop secondary verification is judged to be passed.

[0065] If both types of closed-loop secondary verifications of a power distribution cabinet pass, the operation effect is deemed to meet the standard; if any closed loop of a power distribution cabinet fails, a secondary alarm is triggered, prompting manual intervention to check the operation quality, equipment status and sensor data of the power distribution cabinet. After handling, the secondary verification is performed again until the standard is met or the equipment is locked.

[0066] Examples of embodiments of the present invention Figure 2 As shown, a method for safe operation of high and low voltage distribution cabinets based on dual verification mechanism includes the following steps: Step 1: Power grid data acquisition and networking: Collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, deploy a collaborative autonomous network of edge controller and digital twin platform in each distribution cabinet, and build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform.

[0067] Step 2, Dual Closed-Loop Pre-Verification: Obtain real-time data for each distribution cabinet, initially set the dual closed-loop verification threshold for each distribution cabinet, and analyze the final optimized threshold corresponding to the dual closed-loop verification for each distribution cabinet. This will help assess whether each distribution cabinet needs to trigger a fault-tolerant mechanism and determine whether each distribution cabinet meets the pre-operation safety conditions for power outage and restoration.

[0068] Step 3: Automated Operation Execution: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, the power outage and restoration robot will be driven to perform the power outage and restoration mechanical operation on that power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the operation process for that power distribution cabinet will be immediately suspended. After handling the situation according to the classification of emergency intervention, data supplementation, and parameter optimization, the dual closed-loop pre-verification will be re-executed. The operation can only be restarted after the verification is passed. If the verification is still not passed after handling, the power distribution cabinet will be locked and a fault report will be generated.

[0069] Step 4: Dual-loop post-verification and data storage: After each distribution cabinet completes the mechanical operation of power supply and shutdown, the physical status data and electrical parameter data of each distribution cabinet after the operation are collected again. Based on the dynamic adaptive verification threshold, a second dual-loop verification is completed to verify whether the operation effect meets the standard.

[0070] The examples described in this invention are not limited to the specific embodiments listed above. The examples are merely illustrative to facilitate understanding of the invention and do not constitute a limitation on the scope of protection of this invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of this invention should be included within the scope of protection.

[0071] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A safe operation system for power outage and restoration of high and low voltage distribution cabinets based on a dual-verification mechanism, characterized in that, Includes the following modules: Power grid data acquisition and networking module: used to collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, a collaborative autonomous network of edge controllers and digital twin platforms is deployed in each distribution cabinet to build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform. Dual closed-loop pre-verification module: used to acquire real-time data corresponding to each power distribution cabinet, initially set the dual closed-loop verification threshold for each power distribution cabinet, and analyze the final optimized threshold corresponding to the dual closed-loop verification of each power distribution cabinet, thereby evaluating whether each power distribution cabinet needs to trigger the fault tolerance mechanism and determining whether each power distribution cabinet meets the pre-safety conditions for power outage and restoration operations. The analysis of the final optimized threshold corresponding to the dual closed-loop verification of each distribution cabinet is as follows: The system acquires real-time electrical parameters, real-time physical status parameters, and real-time power grid environment parameters for each distribution cabinet. The real-time electrical parameters include: current voltage, current, temperature, and partial discharge value; the real-time physical status parameters include: wear of the operating target and cabinet deformation; and the real-time power grid environment parameters include: total load factor and ambient humidity. For the basic threshold of closed-loop electrical parameters: if the real-time temperature of a certain distribution cabinet is ≥70℃, tighten the voltage deviation and current deviation thresholds by 20%; if the partial discharge value is >5pC, tighten the voltage deviation and current deviation thresholds by 15%, and at the same time increase the verification frequency to twice the original frequency; if the real-time voltage / current is between 80% and 100% of the rated value, tighten the corresponding deviation threshold by 10%. For the basic threshold of closed-loop spatial attitude: real-time electrical parameters have no direct impact on the closed-loop spatial attitude, and the basic threshold remains unchanged. Regarding the basic threshold for spatial attitude closed-loop: if the wear of the operation target corresponding to a certain distribution cabinet is ≥0.5mm, the positioning accuracy threshold will be tightened by 30%; if the cabinet deformation is >1mm, the positioning reference will be recalibrated in conjunction with the digital twin model, and the positioning accuracy threshold will be tightened by 20%; if the wear of the operation target is <0.5mm and the cabinet is not deformed, the basic threshold for spatial attitude closed-loop remains unchanged. Regarding the basic threshold for electrical parameter closed-loop: real-time physical state parameters have no direct impact on electrical parameter closed-loop, and the basic threshold remains unchanged. Regarding the basic thresholds for spatial attitude closed-loop control: If the ambient humidity is ≥60%RH, the nameplate matching threshold will be increased by 0.2%; the total load rate has no direct impact on spatial attitude closed-loop control, and the positioning accuracy threshold remains unchanged. Regarding the basic thresholds for electrical parameter closed-loop control: If the total load rate is ≥80%, the voltage deviation and current deviation thresholds for all distribution cabinets will be tightened by 30%; if the total load rate is <50%, the voltage deviation and current deviation thresholds for non-core load distribution cabinets will be relaxed by 10%, while the thresholds for core load distribution cabinets will remain unchanged; if the ambient humidity is ≥60%RH, the thresholds for insulation-related parameters will be tightened by 10%. Automated operation execution module: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, it drives the power outage and restoration robot to perform the power outage and restoration mechanical operation on the power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the operation process for the power distribution cabinet is immediately suspended. After handling the situation according to the levels of emergency intervention, data supplementation and parameter optimization, the dual closed-loop pre-verification is re-executed. The operation can only be restarted after the verification is passed. If the verification is still not passed after handling, the power distribution cabinet is locked and a fault report is generated. Dual-loop post-verification and data storage module: After each power distribution cabinet completes the mechanical operation of power outage and restoration, it collects the physical status data and electrical parameter data of each power distribution cabinet after the operation, and completes a second dual-loop verification based on the dynamic adaptive verification threshold to verify whether the operation effect meets the standard.

2. The high and low voltage distribution cabinet power outage and restoration safety operation system based on a dual verification mechanism according to claim 1, characterized in that, The specific deployment process for the collaborative autonomous network of edge controllers and digital twin platforms deployed in each power distribution cabinet is as follows: The digital twin platform is deployed on the cloud server of the target power plant, configured with a global data storage module and an ultra-real-time simulation engine, and connects to the power plant's grid dispatch system to obtain the topology and load basic data of each distribution cabinet in the target power plant. The edge controller is deployed on-site in the distribution room of the target power plant. According to the principle of regional division, each distribution cabinet in the target power plant is divided into several control groups. Each group contains 3-5 edge controllers corresponding to adjacent distribution cabinets. Each group establishes a dedicated communication link with the digital twin platform, and the edge controllers in the same group build a P2P communication subnet.

3. The high and low voltage distribution cabinet power outage and restoration safety operation system based on a dual verification mechanism according to claim 2, characterized in that, The initial setting process for the dual closed-loop verification threshold of each power distribution cabinet is as follows: The operating years and historical number of failures of each distribution cabinet in the target power plant are obtained and divided into three scenarios. If the operating years and historical failure count of a certain power distribution cabinet are: operating years ≤ 2 years, historical failure count = 0, then it is classified as newly commissioned equipment. If the operating years and historical failure count of a certain power distribution cabinet are: 2 years < operating years ≤ 8 years, historical failure count ≤ 3 times, then it is classified as conventional equipment. If the operating years and historical failure count of a certain power distribution cabinet are: operating years > 8 years, historical failure count > 3 times, then it is classified as old equipment. Basic thresholds are set for spatial attitude closed-loop: positioning accuracy of newly commissioned equipment ≤ ±2mm, nameplate matching degree ≥ 99.8%; positioning accuracy of conventional equipment ≤ ±1.5mm, nameplate matching degree ≥ 99.5%; positioning accuracy of old equipment ≤ ±1mm, nameplate matching degree ≥ 99.8%. For closed-loop electrical parameter settings, the basic thresholds are as follows: voltage deviation ≤ ±1% and current deviation ≤ ±1% for newly commissioned equipment; voltage deviation ≤ ±2% and current deviation ≤ ±2% for conventional equipment; and voltage deviation ≤ ±0.8% and current deviation ≤ ±0.8% for older equipment.

4. The high and low voltage distribution cabinet power outage and restoration safety operation system based on a dual verification mechanism according to claim 1, characterized in that, The specific evaluation process for determining whether each distribution cabinet needs to trigger a fault-tolerance mechanism is as follows: Real-time monitoring of the operating status of each sensor in each power distribution cabinet of the sensing subsystem, including the operating status of 3D vision sensors, LiDAR, voltage and current sensors, and generation of sensor status logs; For spatial attitude closed loop: Based on sensor status logs, if a power distribution cabinet detects that a single sensor is in a faulty or abnormal data state, and the status of other redundant sensors in the same closed loop is normal and the data integrity is ≥95%, it is assessed that the spatial attitude closed loop fault tolerance mechanism needs to be triggered; if a power distribution cabinet detects ≥2 sensors that are simultaneously in a faulty or abnormal data state, or the data integrity of redundant sensors is <95%, it is assessed that the fault tolerance mechanism has failed. For closed-loop electrical parameters: Based on sensor status logs, if a distribution cabinet detects that the main voltage / current sensor is in a faulty or abnormal data state, and the backup sensor is in a normal state, supports seamless switching, and the data error after switching is ≤1%, then it is assessed that the closed-loop fault tolerance mechanism for electrical parameters needs to be triggered; if both the main and backup sensors of a distribution cabinet are in a faulty or abnormal data state, or the data error after switching of the backup sensor is >1%, then it is assessed that the fault tolerance mechanism has failed. Summarize the evaluation results of the spatial attitude closed loop and electrical parameter closed loop of a certain power distribution cabinet: If any closed loop requires triggering the fault tolerance mechanism and the other closed loop does not, then the overall output of the power distribution cabinet requires triggering the fault tolerance mechanism; if any closed loop is determined to have failed the fault tolerance mechanism, then the overall output fault tolerance mechanism of the power distribution cabinet fails; if neither closed loop requires triggering the fault tolerance mechanism, then the output of the power distribution cabinet does not need to trigger the fault tolerance mechanism; if the output of a certain power distribution cabinet requires triggering the fault tolerance mechanism or the fault tolerance mechanism fails, then analyze the corresponding handling measures for the power distribution cabinet.

5. A high- and low-voltage distribution cabinet power outage and restoration safety operation system based on a dual-verification mechanism according to claim 4, characterized in that, If a power distribution cabinet needs to trigger a fault tolerance mechanism or the fault tolerance mechanism fails, the corresponding handling measures for that power distribution cabinet will be analyzed. The specific analysis process is as follows: If a power distribution cabinet output needs to trigger a fault tolerance mechanism, a redundant data fusion + digital twin-assisted processing solution is adopted. If the fault tolerance mechanism of the power distribution cabinet fails, a full-process handling solution of suspending operation, issuing graded alarms, locating the root cause, precise handling, and restoring verification will be implemented.

6. A high- and low-voltage distribution cabinet power outage and restoration safety operation system based on a dual-verification mechanism according to claim 5, characterized in that, The specific determination process for whether each distribution cabinet meets the pre-operation safety conditions for power outage and restoration work is as follows: Spatial attitude closed-loop verification: If a power distribution cabinet does not require triggering a fault tolerance mechanism, the nameplate information of the power distribution cabinet collected by the 3D vision sensor and the coordinates of the operation target located by the LiDAR are directly compared with the final optimized threshold. If the nameplate matching degree is ≥ the threshold, the positioning deviation is ≤ the threshold, and the wear of the operation target and the deformation of the cabinet are ≤ the safety threshold, then the spatial attitude closed-loop is judged to have passed. If a power distribution cabinet requires triggering a fault tolerance mechanism, redundant data is used to fuse the verification results. If the threshold requirements are met, it is judged to have passed; otherwise, it is judged to have failed. Electrical parameter closed-loop verification: If a distribution cabinet does not require triggering the fault tolerance mechanism, the voltage, current, temperature, and partial discharge values ​​of the distribution cabinet collected by the main circuit sensors are compared with the final optimized thresholds. If the values ​​comply with the power outage and restoration safety logic, the current before the power outage operation is ≤0A, there is no short-circuit current before the power restoration operation, and the grounding switch has been opened, then the electrical parameter closed-loop verification is considered successful. If a distribution cabinet requires triggering the fault tolerance mechanism, the results of the backup circuit sensors and auxiliary parameters are cross-verified. If the thresholds and safety logic are met, the verification is considered successful; otherwise, the verification is considered unsuccessful. If both types of closed-loop tests of a power distribution cabinet pass, and the digital twin platform inputs the real-time data and final optimization threshold of the power distribution cabinet, and the pre-running and power restoration operation process has no path interference and no electrical logic conflict, then it is determined that the pre-running and power restoration operation safety conditions are met. If any closed loop of a power distribution cabinet fails, or the fault tolerance mechanism fails, or there is a risk in the model simulation, then the prerequisite safety conditions are not met.

7. A high- and low-voltage distribution cabinet power outage and restoration safety operation system based on a dual-verification mechanism according to claim 6, characterized in that, After the tiered handling process of emergency intervention, data replenishment, and parameter optimization, the dual closed-loop pre-verification is re-executed. The specific handling process is as follows: Map the safety risk level, fault impact range, and data anomaly degree of the power distribution cabinet to the corresponding table of Level 1, Level 2, and Level 3 risk classifications; If a power distribution cabinet has a safety risk level of Class I, a fault impact range of Class A, and a data anomaly level of Class X, it is determined to be a Level 1 risk and emergency intervention is carried out for the power distribution cabinet. If a power distribution cabinet has a safety risk level of Class III, a fault impact range of Class C, and a data anomaly level of Class Y, it is determined to be a Level II risk, and data supplementation and processing shall be carried out for the power distribution cabinet. If a power distribution cabinet has a safety risk level of Class IV, a fault impact range of Class C, and a data anomaly level of Class Z, it is determined to be a Level 3 risk, and parameter optimization measures will be taken for the power distribution cabinet.

8. A high- and low-voltage distribution cabinet power outage and restoration safety operation system based on a dual-verification mechanism according to claim 7, characterized in that, The secondary double-loop verification based on the dynamic adaptive verification threshold is performed to verify whether the operation effect meets the standard. The specific verification process is as follows: After the operation is completed, the sensing subsystem collects post-operation data from each power distribution cabinet again: the multimodal sensing module collects physical state data; the wireless electrical sensing module collects post-operation electrical parameter data, and the data is uploaded to the digital twin platform after being preprocessed by the edge controller. Secondary verification of spatial attitude closed loop: The final optimized threshold of each distribution cabinet is called to verify that the status of the opening and closing indicator lights is consistent with the operation command and that the position of the handcart meets the preset standard. If the fault tolerance mechanism is triggered, the redundant sensor data + digital twin model comparison results are used to assist in the verification. If the requirements are met, the secondary verification of spatial attitude closed loop is judged to be passed. Electrical parameter closed-loop secondary verification: Call the final optimized threshold of each distribution cabinet to verify that the electrical parameters after the operation meet the operation target. After the power outage operation, the voltage ≤ 0V and the current ≤ 0A; after the power restoration operation, the voltage / current is stable within the rated range, the deviation ≤ the final optimized threshold, the temperature ≤ the upper limit of equipment tolerance, and the partial discharge value ≤ the safety threshold. If the fault tolerance mechanism is triggered, the backup sensor + auxiliary parameter cross-verification is adopted. If the requirements are met, the electrical parameter closed-loop secondary verification is deemed to have passed. If both types of closed-loop secondary verifications of a power distribution cabinet pass, the operation effect is deemed to meet the standard; if any closed loop of a power distribution cabinet fails, a secondary alarm is triggered, prompting manual intervention to check the operation quality, equipment status and sensor data of the power distribution cabinet. After handling, the secondary verification is performed again until the standard is met or the equipment is locked.

9. A method for performing a power outage and restoration safety operation system for high and low voltage distribution cabinets based on a dual-verification mechanism as described in any one of claims 1-8, characterized in that, Includes the following steps: Step 1: Power Grid Data Acquisition and Networking: Collect physical status data and electrical parameter data of each distribution cabinet in the target power plant. At the same time, deploy a collaborative autonomous network of edge controllers and digital twin platforms in each distribution cabinet, and build a bidirectional communication hybrid protocol network between the sensing subsystem and the edge controller, and between the edge controller and the digital twin platform. Step 2, Dual Closed-Loop Pre-Verification: Obtain real-time data corresponding to each distribution cabinet, initially set the dual closed-loop verification threshold for each distribution cabinet, and analyze the final optimized threshold corresponding to the dual closed-loop verification of each distribution cabinet to evaluate whether each distribution cabinet needs to trigger the fault tolerance mechanism and determine whether each distribution cabinet meets the pre-safety conditions for power outage and restoration operations. Step 3: Automated Operation Execution: If a power distribution cabinet meets the pre-operation safety conditions for power outage and restoration, the power outage and restoration robot will be driven to perform the power outage and restoration mechanical operation on the power distribution cabinet. If a power distribution cabinet does not meet the pre-operation safety conditions for power outage and restoration, the operation process for that power distribution cabinet will be immediately suspended. After handling the situation according to the classification of emergency intervention, data supplementation and parameter optimization, the dual closed-loop pre-verification will be re-executed. The operation can only be restarted after the verification is passed. If the verification is still not passed after handling, the power distribution cabinet will be locked and a fault report will be generated. Step 4: Dual-loop post-verification and data storage: After each distribution cabinet completes the mechanical operation of power supply and shutdown, the physical status data and electrical parameter data of each distribution cabinet after the operation are collected again. Based on the dynamic adaptive verification threshold, a second dual-loop verification is completed to verify whether the operation effect meets the standard.

Images