A substation intelligent access control collaborative management method and system

Abstract

The application provides a substation intelligent access control collaborative management method and system, relates to the technical field of access control, and comprises the following steps: obtaining power work ticket whole-process state data and personnel qualification data; generating hierarchical access permission data of corresponding personnel according to the current process state of the power work ticket; the hierarchical access permission data comprises allowed access area information and valid time period information; real-time monitoring of the process state change of the power work ticket; when the process state of the power work ticket changes, synchronously updating the hierarchical access permission data of the corresponding personnel to maintain the real-time validity of the hierarchical access permission data; when a request for access is received, collecting personnel identity data, access control equipment state data and on-site behavior sensing data, and integrating the collected multi-type data into access verification data sets. The application can effectively improve the accuracy of substation access control and the identification accuracy of illegal behaviors, and can adapt to the high safety management needs of unattended substations.

Description

Technical Field

[0001] This invention relates to the field of access control technology, and in particular to a method and system for intelligent access control and collaborative management of substations. Background Technology

[0002] As the core hub of the power system responsible for voltage transformation, power distribution, and operational control, the operational safety of substations directly determines the power supply reliability of the regional power grid. With the widespread adoption of unmanned operation and maintenance models for power grids, the dispersed distribution of substation sites, the diverse types of personnel entering the stations, and the stringent requirements for work process control have placed higher standards on the refinement, intelligence, and reliability of access control at substation entrances and exits. Access control is the first line of defense for the physical security of substations and a core control link for regulating personnel work order and preventing illegal intrusion.

[0003] Existing substation access control systems generally adopt a static permission configuration mode, where access permissions are pre-set based solely on personnel identity. This fails to dynamically link with the entire process status of power work permits, making it prone to control loopholes such as permissions not being promptly cancelled after work is completed or permissions remaining effective during work interruptions. Furthermore, existing access control systems rely solely on single identity verification data for abnormal access detection, without combining access area restrictions, effective time period constraints, access control device status, and on-site behavior perception data for collaborative analysis. This makes it difficult to identify concealed violations such as legitimate identities exceeding designated areas or time periods, ultimately resulting in insufficient accuracy in access control and low accuracy in identifying violations, failing to fully meet the high-level security control requirements of unmanned substations. Summary of the Invention

[0004] In view of this, the present invention proposes a method and system for intelligent access control and collaborative management of substations, which can effectively improve the accuracy of access control and the identification accuracy of violations in substations, and can adapt to the high security control requirements of unattended substations.

[0005] The technical solution of this invention is implemented as follows: In a first aspect, the present invention provides a method for intelligent access control and collaborative management of substations, comprising the following steps: Acquire the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the permitted access area and the valid time period. Real-time monitoring of changes in the process status of power work permits; when the process status of power work permits changes, synchronously update the hierarchical access permission data of the corresponding personnel to maintain the real-time validity of the hierarchical access permission data. Upon receiving a pass request, the system collects personnel identity data, access control device status data, and on-site behavior perception data at the pass location, and integrates the collected data into a pass verification dataset. The system retrieves the currently effective hierarchical access permission data, matches the corresponding permissions based on the personnel identity in the access verification dataset, performs dual verification processing of allowed access area matching and valid time period matching, and generates permission verification results. By integrating the permission verification results with the access verification dataset, collaborative judgment and processing of abnormal access behavior is performed to generate abnormal judgment results; Based on the permission verification results and anomaly judgment results, corresponding control instructions are generated, and the control instructions are output to the access control device for execution. At the same time, access record data is generated and stored.

[0006] In one embodiment, generating and synchronously updating the hierarchical access permission data of corresponding personnel based on the current process status of the power work order specifically includes: The system pre-defines the permission status mapping rules corresponding to each process status of the power work order, and generates corresponding hierarchical access permission data that is in the pending-effective state based on the current process status of the power work order. When the power work order is detected to have been transferred to the permit status, the corresponding access permission data will be activated to the effective status. When the power work order is detected to be in an intermittent state, the corresponding access permission data will be frozen to a pause state. When the power work ticket is detected to have reached the final state, the corresponding hierarchical access permission data will be cancelled to the invalid state. When the power work permit is detected to be in an extended state, the valid time period information in the corresponding hierarchical access permission data is extended accordingly.

[0007] In one embodiment, the synchronous update of the hierarchical access permission data for the corresponding personnel specifically includes: Real-time monitoring of the validity status of the corresponding personnel's qualifications, including safety regulation assessment status, work qualification validity period, and safety briefing record status; When the validity status of any qualification exceeds the compliance range, the corresponding personnel's access permission data will be immediately adjusted to a temporary invalid status. Once the qualification status is restored to compliance, the corresponding access permission data will be restored to the effective state simultaneously.

[0008] In one embodiment, upon receiving a passage request, personnel identity data, access control device status data, and on-site behavior perception data are collected at the passage site. The collected data is then integrated into a passage verification dataset, specifically including: When a person is detected entering the access control area, a pass request is generated. Collect personnel identity data, access control device status data, and on-site behavior perception data at the passage site. The on-site behavior perception data includes data on the number of people passing through, data on clothing compliance, and data on passage time sequence. Personnel identification data, access control device status data, and on-site behavior perception data are timestamped and integrated into a pass verification dataset.

[0009] In one embodiment, the dual verification process of allowing passage area matching and valid time period matching specifically includes: Each access point in the substation is pre-assigned a corresponding area risk level. The area risk levels are divided into public areas, operation and maintenance areas, and high-voltage work areas from low to high. Each access point corresponds to its respective permitted access area. Retrieve the currently effective hierarchical access permission data and match the corresponding hierarchical access permission data based on the personnel identity in the access verification dataset; First, perform a valid time period matching check to determine whether the current passage time is within the range corresponding to the valid time period information; After the valid time period matching verification is passed, the allowed access area of ​​the current access control point is matched with the allowed access area information of the hierarchical access permission data in order of regional risk level from low to high. If both checks pass, a permission check pass result is generated; if either check fails, a permission check fail result is generated.

[0010] In one embodiment, the collaborative determination process for executing abnormal passage behavior specifically includes: The system pre-defines judgment rules, judgment weights, and anomaly levels for various types of abnormal passage behaviors. The anomaly levels are divided into general anomalies, severe anomalies, and emergency anomalies. Based on the permission verification results, the access control device status data and on-site behavior perception data are extracted from the access verification dataset. The on-site behavior perception data includes data on the number of people passing through, access time sequence data, and clothing compliance data. The extracted data of various types are matched with the corresponding rules for judging abnormal passage behavior, and a comprehensive judgment score is calculated. The corresponding anomaly level and anomaly type are determined based on the comprehensive judgment score, and an anomaly judgment result containing anomaly level information is generated.

[0011] In one embodiment, after the generated access record data is stored, the method further includes: Upon receiving an exit passage request, collect the exiting person's identity data and the corresponding access control point data; Obtain the hierarchical access permission data of the corresponding personnel, as well as the current process status of the power work order bound to that personnel; Verify whether the current process status of the corresponding power work order is in the terminated state. If it is not in the terminated state, generate an exit reminder message and push it to the corresponding personnel and management personnel. After a person exits the station, the exit status of the corresponding passage record data is updated to form a closed-loop record of the entire process from entry to exit.

[0012] Secondly, this invention provides a smart access control and collaborative management system for substations, comprising a permission generation module, a permission dynamic update module, a field data acquisition module, a permission verification module, an anomaly collaborative judgment module, and a management execution module, wherein... The permission generation module is used to obtain the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the allowed access area and the valid time period. The permission dynamic update module is used to monitor the changes in the process status of power work tickets in real time. When the process status of power work tickets changes, the hierarchical access permission data of the corresponding personnel is updated synchronously to maintain the real-time validity of the hierarchical access permission data. The on-site data acquisition module is used to collect personnel identity data, access control device status data and on-site behavior perception data when a passage request is received, and integrate the collected data into a passage verification dataset. The permission verification module is used to call the currently effective hierarchical access permission data, match the corresponding permissions based on the personnel identity in the access verification dataset, perform dual verification processing of allowed access area matching and valid time period matching, and generate permission verification results; The anomaly collaborative judgment module is used to integrate the permission verification results and the access verification dataset, perform collaborative judgment processing of abnormal access behavior, and generate anomaly judgment results. The control execution module is used to generate corresponding control instructions based on the permission verification results and anomaly judgment results, output the control instructions to the access control device for execution, and generate access record data for storage.

[0013] Thirdly, the present invention provides an electronic device, including a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the above-described substation intelligent access control collaborative management method.

[0014] Fourthly, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described substation intelligent access control collaborative management method.

[0015] The substation intelligent access control collaborative management method and system of the present invention have the following advantages over the prior art: 1. By acquiring the full-process status data of power work tickets and personnel qualification data, a hierarchical access permission system is generated, which includes the permitted access areas and valid time periods. The system monitors the process status changes of power work tickets in real time to update the hierarchical access permission synchronously, thereby solving the problem of the disconnect between static permission configuration and work process. When a access request is received, multiple types of data, such as personnel identity, access control device status, and on-site behavior perception, are integrated to form an access verification dataset. After matching the corresponding permissions based on personnel identity, dual verification of area and time sequence is performed. Then, the permission verification results are combined with the access verification dataset to conduct collaborative judgment of abnormal access behavior. Finally, control instructions are generated, executed, and access records are stored, which effectively improves the accuracy of substation access control and the accuracy of identifying violations, thereby adapting to the high-safety control requirements of unattended substations. 2. By pre-setting permission status mapping rules for each process status of the power work order, the hierarchical access permissions can be automatically managed throughout the entire lifecycle of pending activation, activation, freezing, cancellation, and validity extension as the work order flows. There is no need for manual adjustment of permission configuration, which not only simplifies the permission management operation of operation and maintenance personnel, but also avoids the problem of permission expiration and mismatch caused by manual configuration oversight, and significantly improves the real-time performance and compliance of permission control. 3. By pre-setting judgment rules, judgment weights and anomaly levels for multiple types of abnormal passage behaviors, multi-dimensional data in the passage verification dataset is extracted for rule matching and comprehensive score calculation, thereby determining the anomaly level and anomaly type. This changes the traditional crude mode of single-rule judgment, effectively reducing the false alarm rate of anomalies. At the same time, the hierarchical anomaly judgment results can support differentiated handling strategies, improving the response efficiency and handling rationality of abnormal events. Attached Figure Description

[0016] 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.

[0017] Figure 1 This is a flowchart illustrating the intelligent access control and collaborative management method for substations according to the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] like Figure 1 As shown, the substation smart access control collaborative management method of the present invention operates on a substation smart access control management platform. The management platform adopts a two-level deployment architecture combining local edge control nodes and a cloud management platform. The local edge nodes are deployed within the substation and are responsible for real-time access verification, equipment control, and local data caching. The cloud management platform is responsible for unified configuration of permissions for multiple sites, full data aggregation, and compliance analysis. The two communicate through a dedicated power network. In the event of a network interruption, the local node can independently complete access verification, ensuring the reliability of access control management.

[0020] The control platform can connect to the power production management system, personnel management system, and on-site access control terminals to achieve intelligent control of personnel access in unmanned substations. This method includes two parallel processing flows: the first is a background-resident permission lifecycle management flow, corresponding to steps S100 and S200, which continuously maintains the access permission status of all personnel; the second is a single-access event-triggered on-site verification and control flow, corresponding to steps S300 to S600, which is triggered by on-site access requests. The data of the two flows are synchronized in real time to jointly complete access control.

[0021] Step S100: Obtain the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the permitted access area and the valid time period.

[0022] The management and control platform connects to the power production management system through standardized data interfaces to obtain the full-process status data corresponding to the issued power work tickets, as well as the list of all operators associated with each work ticket; at the same time, it connects to the enterprise personnel management system to obtain the personnel qualification data of the corresponding operators.

[0023] The management and control platform uses a single power work order as the smallest management and control unit. Based on the current process status of the work order, it generates hierarchical access permission data for each associated operator.

[0024] Among them, the information on the permitted access areas corresponds one-to-one with the work coverage area approved by the work permit, the information on the valid time period corresponds one-to-one with the planned work time period specified in the work permit, and the hierarchical division of access permissions matches the scope of the work permissions of the operators, so as to achieve a precise correspondence between access permissions and actual work needs.

[0025] The tiered access permission system is based on the highest risk level of the area that personnel are allowed to enter, and is divided into three levels: Level 1 permission only allows entry into public areas, Level 2 permission allows entry into public areas and maintenance areas, and Level 3 permission allows entry into all three types of areas; the permission level corresponds one-to-one with the work area and personnel qualification level approved in the power work permit.

[0026] Step S200: Monitor the changes in the process status of the power work order in real time. When the process status of the power work order changes, update the hierarchical access permission data of the corresponding personnel synchronously to maintain the real-time validity of the hierarchical access permission data.

[0027] The management and control platform adopts an event monitoring mechanism to continuously subscribe to the status flow events of power work tickets in the power production management system.

[0028] When a change in the process status of any power work order is detected, the management platform immediately locates all the workers associated with that work order and adjusts the hierarchical access permission data of the corresponding workers in sync with the changed process status. This ensures that the permitted scope and effective time period of access permissions are always synchronized with the actual work status of the work order, avoiding a disconnect between the permission status and the work process, and guaranteeing the real-time and compliant nature of access permission control.

[0029] Step S300: Upon receiving a passage request, collect personnel identity data, access control device status data, and on-site behavior perception data at the passage site, and integrate the collected data into a passage verification dataset.

[0030] When access control terminals deployed at each entrance and exit of the substation detect a need for passage, they submit a passage request to the management and control platform.

[0031] After receiving the access request, the control platform sends synchronous data collection instructions to various terminal devices on site: the access control terminal's identity recognition module collects the personnel identity data of the personnel passing through, the access control device's built-in status detection unit collects the access control device's status data, and the on-site perception data is collected by the on-site deployed sensing and data collection devices.

[0032] After receiving the above three types of collected data, the management and control platform performs standardized format conversion on the data and integrates it into a unified structured access verification dataset, which serves as the unified data input for subsequent permission verification and anomaly judgment.

[0033] Step S400: Call the currently effective hierarchical access permission data, match the corresponding permissions based on the personnel identity in the access verification dataset, perform dual verification processing of allowed access area matching and valid time period matching, and generate permission verification results.

[0034] The management platform retrieves all currently active access permission data from the permission database, and based on the unique identifier of the person in the access verification dataset, searches for the corresponding access permission data.

[0035] After the permission matching is completed, the management platform performs two checks in sequence: first, the valid time period matching check, which compares the current access time with the valid time period information corresponding to the permission; second, the allowed access area matching check, which compares the area to which the current access control belongs with the allowed access area information corresponding to the permission.

[0036] After both checks are completed, the corresponding permission check results are generated, which include an indicator of whether the check passed or failed, as well as the corresponding permission details.

[0037] Step S500: Merge the permission verification result with the access verification dataset, perform collaborative judgment processing for abnormal access behavior, and generate anomaly judgment result.

[0038] The management and control platform uses the permission verification results as the basic basis for judgment, and combines the multi-dimensional on-site data collected in the access verification dataset to carry out collaborative judgment of abnormal access behavior.

[0039] Compared to the traditional judgment model that relies solely on single identity data, this step uses cross-validation and joint analysis of permission rule data and multi-source perception data on site to identify various violations during passage, thereby improving the comprehensiveness and accuracy of abnormal behavior identification and reducing the problems of missed judgments and misjudgments caused by a single data source.

[0040] After the judgment is completed, the corresponding anomaly judgment result is generated, which includes identification information indicating whether there is any abnormal passage behavior.

[0041] Step S600: Generate corresponding control instructions based on the permission verification results and anomaly judgment results, output the control instructions to the access control device for execution, and generate access record data for storage.

[0042] The management platform combines the permission verification results and the anomaly judgment results to generate corresponding access control instructions: when the permission verification passes and there is no abnormal access behavior, an access control instruction is generated to allow access; when the permission verification fails or there is abnormal access behavior, an access control instruction is generated to prohibit access.

[0043] The control platform sends control commands to the corresponding on-site access control devices, which then execute the corresponding opening and closing control actions.

[0044] Meanwhile, the management platform integrates the personnel identity information, corresponding work ticket identification information, permission verification results, anomaly judgment results, passage time information, and passage location information involved in this passage to generate structured passage record data, which is written to the local storage unit and the cloud database for persistent storage to support subsequent passage traceability, data statistics, and compliance verification needs.

[0045] In some embodiments, hierarchical access permission data for corresponding personnel is generated and updated synchronously based on the current process status of the power work order. The specific sub-steps further refine the permission generation process in step S100 and the permission update process in step S200. By pre-establishing mapping rules between the power work order process status and access permission status, hierarchical access permissions are automatically and accurately transferred along with all nodes of the work process, eliminating the lag and oversight risks of manual permission configuration. Specifically, this is divided into two parts: permission initialization generation and dynamic permission transfer.

[0046] In the permission initialization and generation part, it is necessary to sort out the core nodes of the entire power work ticket process in advance, establish a one-to-one mapping rule between each process node and the hierarchical access permission status, and clarify the effectiveness and control boundaries of permissions under different nodes.

[0047] Specifically, the five legally mandated process nodes of an electrical work permit—issuance, authorization, interruption, termination, and extension—are respectively mapped to five states of tiered access permissions: pending activation, activation, suspension, expiration, and extended validity. Electrical work has strict process compliance requirements. Work permit issuance only signifies approval of the work plan; personnel can only enter the work area after formal work permit authorization. During work interruptions, personnel must be restricted from freely entering and exiting the work site. Access permissions should be immediately revoked upon completion of the work. By solidifying safety regulations into automatically executed mapping rules, a strong binding between access control and work processes can be achieved, avoiding human error from manual permission adjustments.

[0048] Then, based on the current process status of the power work order, corresponding hierarchical access permission data that is in a pending state is generated.

[0049] Specifically, when the management platform obtains power work order data that has been issued but has not yet entered the licensing stage through the interface, it extracts the list of operators, work area scope, and planned work time information contained in the work order, generates corresponding hierarchical access permission data for each associated operator, and marks the initial status of the permission as pending activation.

[0050] Permissions in the pending state are not included in the valid permission verification database and do not have the effect of access control verification. They can only be activated and effective after the work ticket is issued, thus avoiding the compliance risk of workers entering the station in advance from the source.

[0051] In the dynamic flow of permissions, there are four states: permission activation in the work ticket permission state, permission freezing in the work ticket intermittent state, permission cancellation in the work ticket termination state, and permission validity extension in the work ticket extension state.

[0052] For the activation of permissions under the work permit permission status, when the power work permit is detected to have moved to the permission status, the corresponding hierarchical access permission data will be activated to the effective state. After the management platform captures the work permit permission instruction pushed by the power production management system through the event listening mechanism, it locates all pending hierarchical access permissions associated with the work permit, switches the permission status from pending to effective, and simultaneously updates the start time of the permission's effective period to the actual permission time. The activated permissions are synchronously added to the effective permission verification database and can be used immediately for on-site access control verification.

[0053] For access control freezes during work permit interruptions, when a power work permit is detected to be in an interrupted state, the corresponding access control data is frozen to a suspended state. When work interruption procedures are completed on-site and the work permit status is updated to interrupted, the management platform simultaneously switches the corresponding access control to a suspended state. Permissions in a suspended state are temporarily removed from the validity verification database, preventing personnel from passing access control verification and preventing unauthorized personnel from entering the work area during work interruptions, thus complying with the safety regulations for power work interruption management. When work resumes and the work permit is transferred to a resumption permit state, the permissions can be reactivated to an effective state.

[0054] For permission cancellation in the final state of a work order, when the power work order is detected to have reached the final state, the corresponding hierarchical access permission data is cancelled to an invalid state. Once all work is completed and the work order is officially terminated, the management platform immediately sets all hierarchical access permissions associated with that work order to an invalid state. Invalid permissions are permanently removed from the valid permission verification database and no longer participate in any access verification. This mechanism achieves complete synchronization between the permission lifecycle and the work lifecycle, fundamentally preventing unauthorized entry security risks caused by residual permissions after work completion.

[0055] For work permits in an extended status, the validity period of permissions is extended accordingly. When a power work permit is detected to be in an extended status, the valid time period information in the corresponding hierarchical access permission data is extended. After the work permit extension procedure is completed, the management platform obtains the approved extension duration of the work permit and automatically adjusts the valid time period information of the corresponding hierarchical access permission. Through the automatic extension mechanism, there is no need to manually reconfigure the permission validity period, which avoids the problem of personnel being unable to enter the station due to expired permissions during the extended work period, and ensures that the permission validity period is strictly consistent with the actual work period, eliminating the risk of permissions expiring.

[0056] If the extended power work permit is terminated before the end of the extended validity period, the system will still immediately cancel the corresponding access permission according to the rules. The actual validity period of the permission will be based on the actual end time of the work permit and will not be subject to the extension period.

[0057] In some embodiments, step S200 synchronously updates the hierarchical access permission data of the corresponding personnel. Based on the linkage of the power work ticket process status, a linkage verification mechanism for the validity status of personnel qualifications is introduced to jointly ensure the compliance of access control from two dimensions: work process and personnel qualifications. This further blocks the security loophole of personnel with non-compliant qualifications entering the station. Specifically, this can be achieved through sub-steps S201-S203.

[0058] Step S201: Monitor the validity status of the corresponding personnel's qualifications in real time. The validity status of qualifications includes the status of safety regulation assessment, the validity period of work qualification, and the status of safety briefing records.

[0059] The management platform connects to the enterprise's personnel qualification management system, safety regulation training and assessment system, and work safety briefing management system, and synchronizes the qualification validity status data of operators in real time. The qualification validity status includes three core dimensions: safety regulation assessment status, work qualification validity period, and safety briefing record status.

[0060] Data monitoring adopts a combination of daily full synchronization and real-time triggering of change events. The qualification file data of all personnel is fully synchronized at a fixed time every day. At the same time, the system monitors qualification status change events in each system. Once events such as qualification update, assessment completion, or handover completion occur, the latest status data of the corresponding personnel is retrieved in real time to ensure the real-time nature of qualification monitoring.

[0061] The Power Safety Work Regulations clearly stipulate that personnel entering the station for work must pass a valid safety regulations exam, possess valid work qualifications for the corresponding position, and complete the safety technical briefing for the current operation. These three conditions are the legal prerequisites for personnel to enter the station for work.

[0062] By incorporating it into the permission linkage verification dimension, the hard requirements of security procedures can be solidified into automatic system control rules, eliminating the security risks of unqualified personnel entering the site from the access stage, and achieving strong alignment between control rules and industry security standards.

[0063] Step S202: When the validity status of any qualification exceeds the compliance range, the corresponding personnel's hierarchical access permission data shall be immediately adjusted to a temporary invalid status.

[0064] The management platform pre-sets compliance judgment thresholds for various qualifications, including a 12-month validity period for safety regulation assessment results, which are deemed non-compliant if they expire; an expiration date specified on the certificate for operational qualifications, which are deemed non-compliant if they expire; and safety briefing records are only valid for the current operation and automatically expire after the operation is completed.

[0065] When any qualification status of a person is detected to exceed the compliance judgment threshold, the permission adjustment logic is immediately triggered, switching the corresponding hierarchical access permission data of the person from the effective status to the temporarily invalid status. The temporarily invalid permissions are simultaneously removed from the effective permission verification database and are no longer supported for on-site access verification.

[0066] As the status changes, the system automatically generates a qualification expiration reminder message and pushes it to the corresponding operators and maintenance managers, clearly informing them of the reason for the expiration and the rectification requirements.

[0067] The above settings clearly distinguish it from the "paused state" caused by the interruption of work tickets and the "invalid state" caused by the termination of work tickets. The three types of invalidity reasons correspond to different recovery conditions, which makes it easier to accurately determine the recovery basis when restoring permissions in the future, avoid confusion of permission status caused by different reasons, and reduce the control risk of accidental restoration.

[0068] Step S203: Once the qualification validity status is restored to compliance, the corresponding hierarchical access permission data will be restored to the effective status simultaneously.

[0069] To prevent the automatic activation of legacy permissions for terminated operations simply due to qualification restoration, further reduce loopholes in permission control, ensure that permissions always meet the two necessary conditions of operational validity and personnel compliance, and improve the rigor of permission control.

[0070] When the management platform detects that the personnel have completed the safety regulations re-examination and passed the test, completed the renewal of their work qualifications, and completed the corresponding work safety briefing, the validity status of the corresponding qualifications will be restored to the compliance range. The system will first execute the associated verification logic: verify whether the power work ticket bound to the personnel is still in an effective permit status.

[0071] If the associated work order is still in a valid permit state, the corresponding hierarchical access permission data will be restored from a temporarily invalid state to an effective state and re-included in the effective permission verification database to restore personnel access permissions; if the associated work order has been terminated, the permission will remain invalid, only the personnel qualification file data will be updated, and access permissions will not be restored.

[0072] If the same person is bound to multiple valid power work permits at the same time, the system will take the union of the allowed access areas and the union of the valid time periods of all corresponding effective permissions as the final effective access permissions for that person; if any work permit expires or the person's qualifications are not compliant, the scope of permissions will be reduced accordingly, and only the permissions that still meet the conditions for effectiveness will be retained.

[0073] In some embodiments, the process of on-site data collection and integration in step S300 is further refined by clarifying the access request triggering mechanism, standardizing the composition dimensions of multi-source collected data, and introducing timestamp alignment processing. This ensures that the input data for subsequent permission verification and anomaly determination are consistent in timing and complete in dimensions, thereby improving the accuracy and reliability of verification and determination. This is specifically achieved through the following sub-steps.

[0074] Step S301: When a person is detected entering the access control recognition area, a pass request is generated.

[0075] The human body sensor deployed on the access control terminal works in conjunction with the camera to detect when a person enters the preset identification and sensing area in front of the access control device. The distance can be set to 0.5 to 1.5 meters from the access control device. The access control terminal automatically generates a passage request and reports it to the management platform, without the need for personnel to actively swipe cards or press buttons to trigger operations.

[0076] By adopting an area-sensing automatic triggering mode, personnel can pass through without being notified, reducing the number of steps required for maintenance and repair personnel to enter the station and improving passage efficiency. At the same time, the unified triggering timing ensures that subsequent data collection is started synchronously under the same passage event, avoiding data collection timing deviations caused by manual triggering.

[0077] The same area sensing triggering mechanism is used for entry, exit, and cross-area access control within the station. Each access request generates a unique access event ID, which is bound to all data collected, permission verification results, and anomaly judgment results throughout the process, ensuring that the data of a single access event corresponds one-to-one across the entire chain.

[0078] Step S302: Collect personnel identity data, access control device status data, and on-site behavior perception data at the passage site. The on-site behavior perception data includes data on the number of people passing through, data on clothing compliance, and data on passage time sequence.

[0079] After the control platform issues a synchronous data collection instruction, multiple types of terminal devices collect data in parallel. Specifically, this includes collecting facial features and identity information of personnel through the facial recognition module of the access control terminal to form personnel identity data; collecting access control opening and closing status and lock working status through the door magnet and lock status detection unit built into the access control controller to form access control device status data; and collecting the number of people in the access control channel, personnel clothing characteristics, and the time nodes of personnel entry and exit through the binocular camera and behavior analysis unit of the access control channel to form data on the number of people passing through, clothing compliance data, and passage time sequence data. These three types of data together constitute on-site behavior perception data.

[0080] The number of people passing through is used to identify subsequent tailgating and intrusion anomalies; the clothing compliance data is used to verify whether personnel meet the clothing specifications for power operations; and the passage time sequence data is used to identify abnormal scenarios such as access control exceeding the time limit and abnormal loitering. These three types of data correspond to the core safety verification points of the power station's access control, and can provide comprehensive on-site data support for subsequent anomaly collaborative judgment, while avoiding the collection of redundant data and increasing the computational load.

[0081] Step S303: Perform timestamp alignment processing on personnel identity data, access control device status data, and on-site behavior perception data to integrate them into a pass verification dataset.

[0082] Based on the local synchronization clock of the access control terminal, the personnel identity data, access control device status data, and on-site behavior perception data collected synchronously are each stamped with a unified timestamp of the same moment. The raw data from different sources and in different formats are standardized and converted according to a unified data structure, and finally integrated into a pass verification dataset containing four types of fields: time identifier, personnel identifier, device status, and behavior characteristics, which serves as a unified input for subsequent permission verification and anomaly judgment.

[0083] Each data acquisition unit performs a synchronization calibration with the reference clock of the control platform at a fixed time every day, dynamically updating the clock deviation corresponding to each unit, eliminating clock drift errors caused by long-term operation of the equipment, and ensuring the continuous accuracy of timestamp alignment.

[0084] Specifically, because the local clocks of the personnel identification collection unit, access control status collection unit, and behavior perception collection unit each have inherent deviations, directly splicing the data will lead to timing misalignment. Therefore, it is necessary to calibrate the original timestamps of each source data using a unified reference clock to achieve timing alignment of the same access event. The calibration calculation satisfies the following formula:

[0085]

[0086] Among them, T iLet ΔT be the original local timestamp of the i-th type of collected data, where i corresponds to one of the three data sources: personnel identity data, access control device status data, and on-site behavior perception data; i This is the pre-calibrated clock deviation value between the i-th type of acquisition unit and the reference clock. The deviation value is pre-calibrated through the clock synchronization operation during system initialization. A positive value indicates that the local clock lags behind the reference clock, and a negative value indicates that the local clock leads the reference clock. To calibrate the unified timestamp after alignment, all data involved in the integration are marked with the calibrated unified timestamp.

[0087] The original data from different sources has inconsistent field structures and data types, and needs to be integrated into a dataset with a unified structure through mapping transformation. The transformation process satisfies the following structured mapping relationship:

[0088] Each field is generated by mapping the corresponding original data: The unified time field of the dataset takes the value of a calibrated unified timestamp. For personnel identity fields, the original identity data is collected and normalized using the identity identifier normalization function f. id The converted ID is uniformly used as a unique employee ID identifier. The access control device status field is obtained by converting the original analog data of door magnets and locks through the status mapping function \(f_s\), and is unified into three discrete status values: open, closed, and abnormal. This is a behavior perception field, extracted and generated from the original perception data, containing the number of people passing through, N. person Dress code S dress , Passage sequence node T seq Three types of subfields.

[0089] Through the above standardized mapping, the original data collected from multiple heterogeneous sources is converted into a consistent pass verification dataset, which is convenient for subsequent permission verification and anomaly detection modules to directly call without repeating data format parsing.

[0090] In some embodiments, the dual-authorization verification process in step S400 is further refined by introducing a substation area risk level classification mechanism. This involves a verification logic that first performs time-series verification, then area verification, and finally matches verification based on risk level. This achieves refined area authorization control while optimizing the execution efficiency of the verification process, adapting to application scenarios involving multiple sites and high-concurrency verification in unattended substations. Specifically, this includes the following sub-steps S401-S405.

[0091] Step S401: Pre-assign the corresponding area risk level to each access point in the substation. The area risk levels are divided into public area, operation and maintenance area and high voltage operation area from low to high. Each access point corresponds to the area to which it is allowed to pass.

[0092] The spatial distribution and functional areas of all access control points within the substation are pre-analyzed, and the areas are divided into three levels from low to high according to their safety risk level: public area, operation and maintenance area, and high-voltage operation area. Each access control point is associated with a corresponding area risk level, and a one-to-one mapping relationship is established between the access control point number and the area to which it is allowed to pass.

[0093] Among them, the public area corresponds to non-production areas such as the main entrance of the power station and the external reception area, with the lowest safety risk level; the operation and maintenance area corresponds to daily operation and maintenance areas such as the main control room, operation and maintenance passage, and data room, with a medium safety risk level; and the high-voltage operation area corresponds to live-line operation areas such as the high-voltage room, primary equipment area, and power distribution room, with the highest safety risk level.

[0094] The risks of electric shock, the importance of equipment, and the personnel access requirements vary significantly across different functional areas of a substation. Differentiated hierarchical management aligns with the regional management requirements of power safety work procedures. It can break away from the traditional extensive management model of universal access permissions across the entire station, achieve precise matching of access permissions with regional risk levels, and reduce control loopholes related to operations beyond the permitted scope.

[0095] Step S402: Call the currently effective hierarchical access permission data and match the corresponding hierarchical access permission data based on the personnel identity in the access verification dataset.

[0096] This step involves calling the currently effective tiered access permission database, retrieving the tiered access permission data corresponding to the person based on the unique identifier of the person in the access verification dataset, and extracting the valid time period information and allowed access area information corresponding to the permission as the basis for subsequent dual verification.

[0097] Step S403: First, perform a valid time period matching check to determine whether the current passage time is within the range corresponding to the valid time period information.

[0098] First, perform a valid time period matching and verification to obtain the system standard time corresponding to the current access request. Then, compare the current access time with the valid time period information in the hierarchical access permission data to determine whether the current access time is within the valid time period range.

[0099] The valid time period verification only requires logical comparison of time intervals, which has low computational complexity and fast response speed. Prioritizing execution can quickly intercept access requests during non-operational periods and directly terminate subsequent verification processes, reducing unnecessary regional matching calculations and significantly improving overall verification efficiency. The optimization effect is even more obvious in scenarios with parallel verification at multiple sites.

[0100] If the current passage time is within the valid time period, the valid time period matching verification is deemed successful, and the process proceeds to the subsequent area matching verification stage; if the current passage time exceeds the valid time period, the verification is deemed unsuccessful, a permission verification failure result is generated, and the subsequent area matching steps are not executed.

[0101] Step S404: After the valid time period matching verification is passed, match the allowed access area of ​​the current access control point with the allowed access area information of the hierarchical access permission data in order of regional risk level from low to high.

[0102] The permitted areas for tiered access permissions are marked with the highest accessible risk level. Personnel with high-level area permissions are automatically granted access to all low-risk areas, while personnel with low-level area permissions are not granted access to high-risk areas.

[0103] During verification, the area is compared level by level in the order of public area, operation and maintenance area, and high-voltage operation area. If the risk level of the current access control point does not exceed the highest level allowed by the authorization, the area matching verification is deemed to have passed; if it exceeds the highest level allowed by the authorization, the verification is deemed to have failed.

[0104] Using a step-by-step matching approach based on risk level from low to high aligns with the safety management logic of "easy access for low-risk and strict control for high-risk," which is consistent with the safety management philosophy of power operations. Furthermore, step-by-step verification can directly terminate the judgment when a low-level mismatch occurs, shortening the verification time for a single request. It can also accurately locate the level of the area that fails the verification, providing detailed evidence for subsequent anomaly judgment and log tracing.

[0105] The above-mentioned risk level matching rules apply to both entry and cross-regional access within the station; exit access only verifies the validity of personnel identity and basic area permissions, without mandatory verification of valid time periods, adapting to flexible access needs such as temporary departure of workers and material transfer.

[0106] Step S405: If both checks pass, a permission check pass result is generated; if either check fails, a permission check fail result is generated.

[0107] When both valid time period matching and permitted passage area matching checks pass, a permission verification pass result is generated; when either check fails, a permission verification fail result is generated, and the verification result includes a specific reason for the failure, including two categories: time period mismatch and area level mismatch.

[0108] The generated permission verification result is synchronously output to the anomaly collaborative judgment stage and stored in the process data of this passage for subsequent generation of passage records.

[0109] In some embodiments, the collaborative judgment process for abnormal passage behavior in step S500 is further refined by constructing a quantitative judgment model based on multi-factor weighted scoring and hierarchical threshold judgment. This model clarifies the extraction method, individual scoring rules, and weight allocation of each judgment factor, replacing the traditional coarse judgment based on a single rule. This effectively reduces the false alarm rate under cross-judgment of multi-source data and outputs hierarchical abnormal results to support differentiated handling strategies. This is specifically implemented through sub-steps S501-S504.

[0110] Step S501: Preset the judgment rules, judgment weights and abnormal levels corresponding to multiple types of abnormal passage behaviors. The abnormal levels are divided into general abnormality, severe abnormality and emergency abnormality.

[0111] Typical abnormal passage behaviors in substation access scenarios are identified in advance, and a judgment system containing 5 core judgment factors is established. For each type of judgment factor, corresponding judgment rules, single-item score calculation methods and weight coefficients are configured, and score thresholds corresponding to the three levels of abnormality are set.

[0112] Specifically, regarding the judgment factors and weight allocation, the system is built around authorization compliance as the core, combining multiple dimensions such as personnel behavior and equipment status, with a total weight coefficient of 1. In a specific example, the weight of authorization verification result is 0.35, the weight of matching number of personnel is 0.25, the weight of abnormality in access control status is 0.20, the weight of abnormality in access sequence is 0.15, and the weight of compliance in attire is 0.05. Whether personnel have legitimate authorization is the core prerequisite for access control, therefore authorization verification result has the highest weight; personnel tailgating and overcrowding are high-frequency violation scenarios in substations, therefore personnel matching has the second highest weight; abnormal equipment status and timing reflect abnormal behavior during access, and compliance in attire is a basic safety requirement, with the weight decreasing in that order.

[0113] Regarding the anomaly level and score threshold, the comprehensive judgment score ranges from 0 to 100 points, with higher scores indicating higher anomaly risk. In a specific example, this is divided into three levels: 0-30 points for no anomaly, 31-60 points for general anomaly, 61-90 points for severe anomaly, and 91-100 points for emergency anomaly.

[0114] Step S502: Based on the permission verification result, extract the access control device status data and on-site behavior perception data from the access verification dataset. The on-site behavior perception data includes the number of people passing through, the passage time sequence data, and the clothing compliance data.

[0115] For access control device status data, three types of raw data can be extracted from the access control device status field of the access verification dataset: access control opening time, access control closing time, and lock trigger status. The duration of continuous access control is calculated and used as the basis for calculating the access control status anomaly.

[0116] For on-site behavior perception data, the personnel target detection and statistical algorithms of the on-site binocular cameras can be used to track and count personnel targets in the passage in real time, and count the total number of personnel actually passing through in this passage event. At the same time, the number of personnel who passed the identity verification in this event can be extracted. The two together constitute the basis for calculating the personnel quantity matching degree. The time when personnel enter the recognition area and the time when personnel leave the passage area can be extracted. Combined with the access control opening time, a complete passage time node sequence can be formed as the basis for calculating the passage time sequence anomaly degree. The on-site image recognition model can be used to perform feature detection on the collected personnel images to identify whether personnel are wearing safety helmets and uniforms, and output a clothing compliance mark as the basis for judging the clothing compliance degree.

[0117] It should be noted that the statistical scope of the number of people passing through is the total number of people who have completely passed through the access control channel within a single access control opening cycle; this number is compared with the number of people who have completed identity verification within the same opening cycle, and the difference is the number of people who have not been verified, which serves as the core basis for judging abnormal tailgating.

[0118] Step S503: Match the extracted multi-class data with the corresponding judgment rules for abnormal passage behavior, and calculate the comprehensive judgment score.

[0119] The extracted raw data of various types are matched one by one with the preset judgment rules. First, the individual score of each judgment factor is calculated, and then the comprehensive judgment score is calculated by weighted summation.

[0120] In a specific example, the permission verification result score is s1. When the permission verification passes, the single item score s1 = 0 points; when the permission verification fails, the single item score s1 = 100 points. The matching degree score for the number of people passing through is s2, which is calculated as the difference between the actual number of people passing through and the number of people whose identity verification is passed. When the difference is 0, s2 = 0 points. For each additional person, the score increases by 40 points, with a maximum score of 100 points. For example, if 2 people actually pass through and only 1 person passes identity verification, the difference is 1, and s2 = 40 points. The access control status abnormality score is s3. The preset threshold for the normal access control opening time is T0, which can be set to 15 seconds by default. The actual opening time is T. d When T d When T ≤ T0, s3 = 0 points; when T d When T > T0, according to the formula s3 = (T d -T0) / T0×100 is calculated, with a maximum score of 100; the score for abnormal passage time is s4, with a preset threshold for normal passage time. When the time a person stays in the passage exceeds the threshold, the score is calculated according to the excess ratio; passage events during non-working hours are directly scored as 60 points, with a maximum score of 100 points; the score for compliance with dress code is s5. When both the safety helmet and work clothes are compliant, s5=0 points; when one item is missing, s5=50 points; when both items are missing, s5=100 points.

[0121] The overall score is calculated using a weighted summation formula: S = w1s1 + w2s2 + w3s3 + w4s4 + w5s5 Among them, w1~w5 correspond to the weight coefficients of the five factors, which can be set to 0.35, 0.25, 0.20, 0.15 and 0.05 respectively.

[0122] In a specific example, in a certain access event, the permission verification passed s1=0, 2 people actually passed, only 1 person's verification passed s2=40, the access control lasted 24 seconds s3=60, the access sequence was normal s4=0, and the attire was compliant s5=0. Substituting into the formula, we get: S=0.35×0+0.25×40+0.20×60+0.15×0+0.05×0=22 A score between 0 and 30 indicates no abnormality, corresponding to a normal scenario where personnel follow the moving equipment, thus avoiding misjudgments caused by differences in the number of individuals.

[0123] Step S504: Determine the corresponding anomaly level and anomaly type based on the comprehensive judgment score, and generate an anomaly judgment result containing anomaly level information.

[0124] The anomaly level determination adopts a combination mechanism of score matching and a minimum guarantee rule. When the permission verification result is unsuccessful, the minimum anomaly level is directly set to severe anomaly. If the combined score of other factors corresponds to a higher anomaly level, the higher level is taken as the final result, ensuring that core permission violation scenarios are matched with the corresponding control intensity. After assigning an anomaly level to the overall score, the anomaly type corresponding to the highest-scoring individual factor is taken as the primary anomaly type. Simultaneously, the individual scores of all factors are recorded as the basis for judgment. For example, if the overall score is 72 and the personnel quantity matching score is the highest, it is judged as a serious anomaly, with the anomaly type being personnel tailgating.

[0125] The generated anomaly determination results are synchronously output to the control and execution module, which is used to generate access control instructions and alarm push strategies of the corresponding level. Different anomaly levels correspond to different alarm levels and handling procedures.

[0126] In some embodiments, after the generated access record data is stored, a power work ticket status linkage verification and a closed-loop full-process recording are introduced at the exit access stage. This fills the control gap in the existing access control system, which only controls entry and lacks compliance verification at the exit stage. This enables traceability and verification of the entire lifecycle of personnel from entry to exit, further improving the compliance management level of substation operation access. This is specifically achieved through sub-steps S701-S704.

[0127] Step S701: Upon receiving an exit passage request, collect the exit personnel's identity data and corresponding access control point data.

[0128] When the access control terminal deployed at the substation exit detects a person's need to exit the station through human body sensing, it automatically triggers an exit access request and reports it to the management and control platform; the management and control platform simultaneously collects the identity identification data of the exiting person, as well as the current exit access control point number and the area information to which it belongs.

[0129] This step uses the same seamless triggering mode as the entry passage to ensure the efficiency of personnel exit passage, while providing a unified format of basic data for subsequent exit verification and record closure.

[0130] Step S702: Obtain the hierarchical access permission data of the corresponding personnel, as well as the current process status of the power work order bound to the personnel.

[0131] The control platform matches and retrieves the personnel's valid hierarchical access permission data for the day based on the personnel's identity identifier, and at the same time, it retrieves the corresponding bound power work ticket and pulls the current process status of the work ticket from the power production management system in real time.

[0132] By associating and matching the permissions and work ticket information at the time of entry, it is ensured that the exit verification and entry control are based on the same operational benchmark, thus guaranteeing the consistency of the control logic throughout the entire process.

[0133] Step S703: Verify whether the current process status of the corresponding power work order is in the terminated state. If it is not in the terminated state, generate an exit reminder message and push it to the corresponding personnel and management personnel.

[0134] The management platform compares the current status of the retrieved work order with its termination status. If the work order has been terminated, the exit is deemed compliant, and a release order is generated directly. If the work order has not been terminated, an exit reminder message is generated and pushed to the mobile terminal of the exiting worker and the management terminal of the corresponding work supervisor, reminding the worker to complete the work order termination procedure before leaving the site, thus avoiding the safety risks of the work order being suspended beyond its expiration date and the work site being unattended.

[0135] The reason for using reminders instead of mandatory blocking is that substation operation scenarios require multiple entries and exits, such as temporary departures and material transfers. Mandatory blocking would affect the efficiency of normal operations. The flexible reminder mechanism fulfills the obligation of compliance notification without hindering normal operation, thus balancing safety control and on-site operation flexibility.

[0136] Step S704: After the personnel have exited the station, update the exit status of the corresponding passage record data to form a closed-loop record of the entire process from entry to exit.

[0137] After the access control terminal confirms that the personnel have completed the exit passage, it reports the exit completion event to the management platform. The management platform locates the personnel's corresponding entry passage record for the day, supplements it with information such as exit time, exit access control point, and work ticket status verification result, and updates the status of the single passage record from "entered but not exited" to "exited", forming a closed-loop passage record containing information on all nodes from entry to exit.

[0138] Closed-loop records are uniformly stored in the access record database, which can support subsequent management needs such as compliance auditing of operations, personnel trajectory tracking, and work ticket verification and reconciliation, and realize full-process traceability of access control data.

[0139] The substation intelligent access control and collaborative management system of the present invention includes a permission generation module, a permission dynamic update module, a field data acquisition module, a permission verification module, an anomaly collaborative judgment module, and a management and control execution module.

[0140] The permission generation module is used to obtain the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the allowed access area and the valid time period.

[0141] The dynamic permission update module is used to monitor the changes in the process status of power work orders in real time. When the process status of a power work order changes, the hierarchical access permission data of the corresponding personnel is updated synchronously to maintain the real-time validity of the hierarchical access permission data.

[0142] The on-site data acquisition module is used to collect personnel identity data, access control device status data, and on-site behavior perception data when a passage request is received, and integrate the collected data into a passage verification dataset.

[0143] The permission verification module is used to call the currently effective hierarchical access permission data, match the corresponding permissions based on the personnel identity in the access verification dataset, perform dual verification processing of allowed access area matching and valid time period matching, and generate permission verification results.

[0144] The anomaly collaborative judgment module is used to integrate the permission verification results and the access verification dataset, perform collaborative judgment processing of abnormal access behavior, and generate anomaly judgment results.

[0145] The control execution module is used to generate corresponding control instructions based on the permission verification results and anomaly judgment results, output the control instructions to the access control device for execution, and generate access record data for storage.

[0146] The electronic device of the present invention includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the above-described intelligent access control collaborative management method for substations.

[0147] The present invention provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described substation intelligent access control collaborative management method.

[0148] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0149] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0151] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0153] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0154] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. 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 collaborative control of intelligent access control in substations, characterized in that, Includes the following steps: Acquire the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the permitted access area and the valid time period. Real-time monitoring of changes in the process status of power work permits; when the process status of power work permits changes, synchronously update the hierarchical access permission data of the corresponding personnel to maintain the real-time validity of the hierarchical access permission data. Upon receiving a pass request, the system collects personnel identity data, access control device status data, and on-site behavior perception data at the pass location, and integrates the collected data into a pass verification dataset. The system retrieves the currently effective hierarchical access permission data, matches the corresponding permissions based on the personnel identity in the access verification dataset, performs dual verification processing of allowed access area matching and valid time period matching, and generates permission verification results. By integrating the permission verification results with the access verification dataset, collaborative judgment and processing of abnormal access behavior is performed to generate abnormal judgment results; Based on the permission verification results and anomaly judgment results, corresponding control instructions are generated, and the control instructions are output to the access control device for execution. At the same time, access record data is generated and stored.

2. The substation intelligent access control collaborative management method as described in claim 1, characterized in that, Based on the current process status of the power work order, generate and synchronously update the hierarchical access permission data for the corresponding personnel, specifically including: The system pre-defines the permission status mapping rules corresponding to each process status of the power work order, and generates corresponding hierarchical access permission data that is in the pending-effective state based on the current process status of the power work order. When the power work order is detected to have been transferred to the permit status, the corresponding access permission data will be activated to the effective status. When the power work order is detected to be in an intermittent state, the corresponding access permission data will be frozen to a pause state. When the power work ticket is detected to have reached the final state, the corresponding hierarchical access permission data will be cancelled to the invalid state. When the power work permit is detected to be in an extended state, the valid time period information in the corresponding hierarchical access permission data is extended accordingly.

3. The substation intelligent access control collaborative management method as described in claim 1, characterized in that, The synchronous update of the hierarchical access permission data for the corresponding personnel specifically includes: Real-time monitoring of the validity status of the corresponding personnel's qualifications, including safety regulation assessment status, work qualification validity period, and safety briefing record status; When the validity status of any qualification exceeds the compliance range, the corresponding personnel's access permission data will be immediately adjusted to a temporary invalid status. Once the qualification status is restored to compliance, the corresponding access permission data will be restored to the effective state simultaneously.

4. The substation intelligent access control and collaborative management method as described in claim 1, characterized in that, Upon receiving a passage request, the system collects personnel identity data, access control device status data, and on-site behavior perception data from the passage site. The collected data is then integrated into a passage verification dataset, specifically including: When a person is detected entering the access control area, a pass request is generated. Collect personnel identity data, access control device status data, and on-site behavior perception data at the passage site. The on-site behavior perception data includes data on the number of people passing through, data on clothing compliance, and data on passage time sequence. Personnel identification data, access control device status data, and on-site behavior perception data are timestamped and integrated into a pass verification dataset.

5. The substation intelligent access control collaborative management method as described in claim 1, characterized in that, The dual verification process of matching allowed passage areas and valid time periods specifically includes: Each access point in the substation is pre-assigned a corresponding area risk level. The area risk levels are divided into public areas, operation and maintenance areas, and high-voltage work areas from low to high. Each access point corresponds to its respective permitted access area. Retrieve the currently effective hierarchical access permission data and match the corresponding hierarchical access permission data based on the personnel identity in the access verification dataset; First, perform a valid time period matching check to determine whether the current passage time is within the range corresponding to the valid time period information; After the valid time period matching verification is passed, the allowed access area of ​​the current access control point is matched with the allowed access area information of the hierarchical access permission data in order of regional risk level from low to high. If both checks pass, a permission check pass result is generated; if either check fails, a permission check fail result is generated.

6. The substation intelligent access control collaborative management method as described in claim 1, characterized in that, The collaborative determination and processing of abnormal passage behavior specifically includes: The system pre-defines judgment rules, judgment weights, and anomaly levels for various types of abnormal passage behaviors. The anomaly levels are divided into general anomalies, severe anomalies, and emergency anomalies. Based on the permission verification results, the access control device status data and on-site behavior perception data are extracted from the access verification dataset. The on-site behavior perception data includes data on the number of people passing through, access time sequence data, and clothing compliance data. The extracted data of various types are matched with the corresponding rules for judging abnormal passage behavior, and a comprehensive judgment score is calculated. The corresponding anomaly level and anomaly type are determined based on the comprehensive judgment score, and an anomaly judgment result containing anomaly level information is generated.

7. The substation intelligent access control collaborative management method as described in claim 1, characterized in that, After the generated access record data is stored, the method further includes: Upon receiving an exit passage request, collect the exiting person's identity data and the corresponding access control point data; Obtain the hierarchical access permission data of the corresponding personnel, as well as the current process status of the power work order bound to that personnel; Verify whether the current process status of the corresponding power work order is in the terminated state. If it is not in the terminated state, generate an exit reminder message and push it to the corresponding personnel and management personnel. After a person exits the station, the exit status of the corresponding passage record data is updated to form a closed-loop record of the entire process from entry to exit.

8. A smart access control and collaborative management system for substations, characterized in that, It includes a permission generation module, a dynamic permission update module, a field data acquisition module, a permission verification module, an anomaly collaborative judgment module, and a control execution module. The permission generation module is used to obtain the full-process status data and personnel qualification data of the power work order, and generate the corresponding hierarchical access permission data for the personnel based on the current process status of the power work order. The hierarchical access permission data includes information on the allowed access area and the valid time period. The permission dynamic update module is used to monitor the changes in the process status of power work tickets in real time. When the process status of power work tickets changes, the hierarchical access permission data of the corresponding personnel is updated synchronously to maintain the real-time validity of the hierarchical access permission data. The on-site data acquisition module is used to collect personnel identity data, access control device status data and on-site behavior perception data when a passage request is received, and integrate the collected data into a passage verification dataset. The permission verification module is used to call the currently effective hierarchical access permission data, match the corresponding permissions based on the personnel identity in the access verification dataset, perform dual verification processing of allowed access area matching and valid time period matching, and generate permission verification results; The anomaly collaborative judgment module is used to integrate the permission verification results and the access verification dataset, perform collaborative judgment processing of abnormal access behavior, and generate anomaly judgment results. The control execution module is used to generate corresponding control instructions based on the permission verification results and anomaly judgment results, output the control instructions to the access control device for execution, and generate access record data for storage.

9. An electronic device, characterized in that, It includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the substation smart access control collaborative management method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the substation intelligent access control collaborative management method as described in any one of claims 1-7.

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