Digital tool management method for electric power warehouse

Abstract

The invention discloses a digital tool management method for an electric power warehouse, and the method comprises the following steps: S1, recording tool basic information through an RFID tag, inputting personnel information through a biological recognition system, generating a unique identity identification code, and achieving the digital management of tools and personnel; s2, deploying an intelligent access control system combined with AI face recognition at the entrance of the warehouse, automatically verifying the identity of a person, recording the entering and exiting time, and binding tool information to realize the automation of a tool receiving process; s3, a return detection point is configured, the return state of the tool is monitored through RFID scanning, and reminding and access control limitation are carried out on the tool which is not returned; s4, analyzing tool use behaviors based on an artificial intelligence algorithm, calculating abnormal scores, identifying high-risk users and limiting permissions; s5, performing multi-level reminding by the tool for overdue return, and exciting timely return through an integral reward mechanism; and S6, generating a tool use efficiency report through algorithm optimization and data analysis, and providing support for a management strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of power tool management, and in particular to a digital tool management method for a power warehouse. Background Art

[0002] With the continuous development of modern power systems, the use and management of power equipment and tools plays a vital role in ensuring the safety and reliability of power supply. Especially in power warehouses, the efficient management of tools not only directly affects the efficiency of equipment use, but also affects the safety of staff and the reasonable allocation of warehouse materials. At present, the traditional tool management model mainly relies on manual registration and manual inspection, which has many shortcomings, such as: 1. The defects of traditional tool management model; In traditional power warehouse tool management, the collection and return of tools are usually recorded and monitored manually. When picking up tools, staff need to manually fill in information such as tool number and collection time, and when returning tools, they also rely on manual verification to see if they are returned on time. This method is not only prone to human errors, but also unable to obtain the tool usage status in real time, resulting in an inability to accurately grasp the tool usage and difficulty in discovering potential problems such as expiration, damage or loss. What's more serious is that due to the limitations of manual management, the efficiency of tool use is low, and there is a lack of necessary safety protection measures, which may affect work progress.

[0003] 2. Insufficient personnel management; At present, personnel management in power warehouses mostly relies on manual records or simple identity verification systems, which cannot accurately and real-timely verify the identity of personnel entering the warehouse, especially in an environment with multiple personnel and multiple tools, which is prone to operational errors or confusion in authority management. Although some intelligent access control systems have been introduced in the prior art, most systems have not yet been deeply integrated with tool management, and cannot effectively and automatically record and associate the status of tool collection and return, resulting in a lag in tool management information and affecting overall management efficiency.

[0004] 3. Tool expiration and lack of monitoring mechanism; For tools that are borrowed for a long time, there is a lack of effective overdue monitoring mechanisms. At the same time, it is difficult to conduct in-depth analysis of personnel behavior, unable to identify frequent overdue behaviors, lacking effective risk identification and control measures, and often unable to timely discover the overdue use of tools. Some existing technologies only rely on basic overdue reminders, and have not formed an effective reminder and control mechanism, making it difficult to promote timely return and reasonable use of tools by staff. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] Therefore, in order to solve these problems in the traditional power warehouse tool management, the present invention proposes a digital tool management method based on the combination of RFID technology, artificial intelligence algorithm and biometric technology. This method can realize the automation, digitization and intelligent management of the whole process of tool management by installing RFID tags on tools, deploying intelligent access control system in the warehouse, and applying artificial intelligence analysis tools to collect and return data; The specific steps include: S1: Install RFID tags on warehouse tools and enter basic information. At the same time, establish a personnel management system, enter authorized personnel information and generate a unique identity code through biometrics to achieve comprehensive digital management of tools and personnel; S2: Deploy an intelligent access control system combined with AI facial recognition at the warehouse entrance, equipped with RFID reading devices to automate personnel identity verification and tool collection processes, including real-time binding of tool information and reminder sending; S3: Configure a return detection point at the warehouse access control, confirm the tool return status through RFID scanning, update the record in real time and push reports to the administrator, and implement access control restrictions and reminder mechanisms for unreturned tools; S4: Use artificial intelligence algorithm analysis tools to collect and return data, identify abnormal behavior, generate risk level reports and push them to administrators, and implement permission restrictions for high-risk users; S5: Implement a multi-level reminder strategy to remind multiple times of tools that are about to be overdue, trigger a credit point deduction mechanism, and give points to recipients who return them in time. The points can be used to redeem warehouse benefits. S6: Regularly update RFID and AI analysis system algorithms, expand database storage capacity, introduce improved functions based on user feedback, and automatically generate tool usage efficiency reports to continuously optimize system management and performance.

[0007] As a preferred solution of the digital tool management method for power warehouses described in the present invention, the basic information of the tool includes the tool number, model, purpose and maintenance cycle; the information of the authorized personnel entered includes name, work number, contact information and authority level, which is used for subsequent data binding and operation records.

[0008] As a preferred solution of the digital tool management method for the power warehouse described in the present invention, the access control system verifies the identity through facial recognition and records the entry and exit time of relevant personnel in the power warehouse; when picking up tools, personnel scan the required tools through RFID reading equipment, and the system automatically binds the recipient information and tool information, and prompts the usage time limit and sends a usage agreement reminder.

[0009] As a preferred solution of the digital tool management method for power warehouses of the present invention, an artificial intelligence algorithm is used to calculate an abnormality score based on tool collection and return data, and the abnormality score is calculated according to the following formula: ; in, , , , is the weight parameter obtained through historical data training, is the number of overtimes, is the total duration of the overdue period, The frequency of receiving tools, is the number of unreturned tools, The total duration of the statistical period.

[0010] As a preferred solution of the digital tool management method for power warehouses described in the present invention, a threshold representing an abnormality score is set. When the abnormality score exceeds the preset threshold, the system marks the user as a high-risk user. The system automatically restricts the high-risk user's authority to obtain new tools and generates a detailed report. The report includes the abnormality score and specific indicator values ​​(such as the number of overdue times, duration, etc.).

[0011] As a preferred solution of the digital tool management method for power warehouses described in the present invention, the threshold of the abnormal score is dynamically adjusted according to the tool usage and historical data, and a comprehensive evaluation is performed in combination with multi-dimensional user behavior.

[0012] As a preferred solution of the digital tool management method for power warehouses described in the present invention, authority restrictions include but are not limited to restricting high-risk users from receiving new tools, extending the time limit for returning their tools, or restricting them from receiving specific tools.

[0013] As a preferred solution of the digital tool management method for power warehouses described in the present invention, the multi-level reminder strategy includes sending SMS and email reminders to the recipient 24 hours, 12 hours and the last hour when the tool is about to expire and not returned, and notifying the warehouse manager to intervene.

[0014] As a preferred solution of the digital tool management method for power warehouses described in the present invention, warehouse benefits include priority in receiving scarce tools or exchanging other warehouse benefits, such as additional tool usage time limit.

[0015] As a preferred solution of the digital tool management method for power warehouses described in the present invention, the system automatically generates tool usage efficiency reports through real-time analysis of tool usage, so that administrators can optimize tool configuration and management strategies.

[0016] Beneficial effects of the present invention: 1. Through the application of RFID tags and the deployment of intelligent access control systems, the present invention realizes the digital management of tool information and the accurate verification of personnel identities, so that the tool collection and return process is fully automated, reducing manual intervention and improving management efficiency.

[0017] 2. The present invention combines RFID technology and artificial intelligence algorithms to track the use of tools in real time, automatically record and update the collection and return status of tools, avoid errors in manual records, and ensure the real-time and accuracy of information.

[0018] 3. The present invention analyzes tool usage data through artificial intelligence algorithms. The present invention can automatically identify abnormal behaviors (such as overdue, frequent collection, etc.), generate risk level reports, and push them to administrators in a timely manner, thereby improving the security and reliability of tool management.

[0019] 4. The present invention can effectively encourage staff to return tools on time through multi-level reminders and point incentive mechanisms, while providing rewards for staff who comply with the return rules, thus forming a benign incentive mechanism.

[0020] 5. The artificial intelligence algorithm in the present invention can be dynamically optimized according to actual needs, supporting the system to adjust the tool management strategy according to historical data, thereby continuously improving system performance and management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0025] Example 1 Reference Figure 1 , which is the first embodiment of the present invention, provides a digital tool management method for a power warehouse, comprising the following steps: S1: Digital management of tools and personnel information; Specifically, RFID tags are installed on warehouse tools, basic information of the tools (such as tool number, model, purpose, maintenance cycle) is entered, and the tool status is automatically identified through RFID reading equipment. At the same time, a personnel management system is established to enter the information of authorized personnel (such as name, work number, contact information, authority level), and a unique identity code is generated through biometrics for subsequent data binding and operation records.

[0026] Application example: In a large-scale power construction project, RFID tags are bound to all power equipment (such as high-voltage testers and torque wrenches), and fingerprint or face recognition information is entered for on-site engineers to achieve comprehensive digital binding of tools and personnel.

[0027] S2: Automation of smart access control and tool collection process; Specifically, an intelligent access control system combined with AI facial recognition is deployed at the warehouse entrance to automatically record the entry and exit time of personnel through personnel identity verification, and combine the information of the collection tool bound by the RFID reading device to send reminders to the recipient in real time.

[0028] Application example: In a power maintenance center, when a person enters the warehouse, the access control system confirms his or her identity through facial recognition and automatically records it. The system also sends the recipient instructions on how to use the tools and a reminder on when to return them in real time.

[0029] S3: Real-time monitoring and reminder of tool return status; Specifically, a return detection point is configured at the warehouse access control, and the RFID scanning tool information is used to confirm the return status. The records are updated in real time and pushed to the administrator. At the same time, access control restrictions and multi-level reminders are implemented for unreturned tools.

[0030] Application example: After a user returns a tool, the system detects that the tool is in good condition and completes the record; if the return is overdue, the system will notify the administrator and record the overdue period.

[0031] S4: Artificial intelligence algorithm analysis and abnormal behavior monitoring; Specifically, the artificial intelligence algorithm analysis tool is used to collect and return data, and the anomaly score is calculated according to the following formula: ; in, , , , is the weight parameter obtained through historical data training, is the number of overtimes, is the total duration of the overdue period, The frequency of receiving tools, is the number of unreturned tools, The total duration of the statistical period.

[0032] When the anomaly score exceeds the preset threshold, the system generates a risk level report and pushes it to the administrator, and imposes permission restrictions on high-risk users.

[0033] Application example: If a user frequently returns tools beyond the due date, his abnormal score exceeds the threshold, and the system automatically marks him as high risk, restricts him from receiving new tools, and generates a behavior report for the administrator to review; Example scenario: Assume that the following users receive and return data: User ID: U001 Pick-up and return records: Tool A: Collection time: 2025-01-01 08:00, return time: 2025-01-03 10:00 (2 hours overdue); Tool B: Collection time 2025-01-04 14:00, return time 2025-01-07 18:00 (10 hours overdue); Tool C: collected on 2025-01-08 09:00, not returned.

[0034] The calculation steps are as follows: First extract the following features: (Number of overdue times: Tool A and Tool B); hours (total duration of overdue period); (frequency of picking up tools within 30 days, i.e. number of pick-ups); (Number of tools not returned); Then calculate the anomaly score: the weight is set to , , , ; Next, due to the total length of the system's statistical cycle The total time is 720 hours. Substituting the above data into the scoring formula, the calculation process is as follows:

[0035] Finally, the judgment results are as follows: Setting Thresholds , because the above calculation results Greater than At this time, the system marks user U001 as high risk; Subsequent processing: The system sends a return reminder to user U001 and restricts him from receiving new tools; At the same time, administrators receive exception reports, including overdue tools, scoring details, etc., to facilitate subsequent processing.

[0036] S5: Multi-level reminder strategy and incentive mechanism; Specifically, a multi-level reminder strategy is designed to send SMS and email reminders 24 hours, 12 hours, and the last hour before the tool expires. Points are awarded to recipients who return the tools on time, and the points can be exchanged for warehouse benefits (such as priority to receive scarce tools or extend the tool usage period).

[0037] Application example: A recipient returns a critical device in a timely manner, and the system rewards him with additional points, which can be exchanged for additional tool use priority.

[0038] S6: System performance optimization; Specifically, RFID and AI algorithms are updated regularly, database storage capacity is expanded, and system functions are continuously optimized based on user feedback. At the same time, tool usage efficiency reports are automatically generated to assist administrators in optimizing warehouse management strategies.

[0039] Application example: A power warehouse generates tool usage efficiency reports in real time and finds that the utilization rate of some tools is too low. The administrator adjusts the tool configuration accordingly.

[0040] Example 2 This is the second embodiment of the present invention, which is different from the first embodiment in that: in order to verify the advantages of a digital tool management method for a power warehouse based on RFID and artificial intelligence algorithm in improving tool management efficiency, reducing overdue tool returns, and optimizing tool usage behavior warnings, this embodiment simulates a typical power company warehouse for experiments, and compares the effects of our invention with the prior art in tool management, especially in terms of tool collection, return, overdue management, and abnormal behavior warnings.

[0041] 1. Test preparation is as follows: Tool management system: A digital management system invented by us, including RFID tags, smart access control system, and artificial intelligence analysis platform.

[0042] RFID tags: RFID tags are installed on 200 tools in the warehouse, and each tag has a unique identification.

[0043] Biometric technology: Install a facial recognition access control system at the warehouse entrance, combining RFID tags with facial recognition technology to achieve personnel identity verification.

[0044] Artificial Intelligence Algorithm: Logistic regression and anomaly scoring algorithms are used to analyze the collection and return behaviors of the tool and evaluate high-risk behaviors.

[0045] Comparison system: It is the existing technology, using traditional manual recording of tool collection and return status, manual verification of tool expiration, and no AI analysis and automatic reminder functions.

[0046] 2. Experimental scene setting: Test cycle: The simulation test cycle is set to 60 days.

[0047] Experimental environment: The environment in which tools are used daily in the power warehouse, including on-site operators, warehouse managers and management systems.

[0048] Tool usage scenarios: including daily equipment maintenance, temporary projects, etc., simulating different tool collection and return behaviors.

[0049] 3. Implementation process: Tool information entry and tool collection: All tools are identified by RFID tags. When picking up tools, staff members use facial recognition and RFID scanning to authenticate their identities. The system automatically records the time the tools were picked up, the personnel information and the type of tool.

[0050] Compared with the existing technology, this system fully automates the tool collection process through the combination of smart access control and RFID, avoids manual recording errors, and can synchronize to the management platform in real time.

[0051] Tool return and overdue management: When the tool is returned, the RFID scan identifies the returned tool and confirms the integrity and status of the tool. If the tool is not returned in time, the system automatically generates an overdue reminder and reminds the recipient through multiple channels such as SMS and email.

[0052] Our invention uses artificial intelligence algorithms to analyze the collection behavior of tools, and calculates abnormal scores based on historical collection data to identify high-risk users. Existing technologies only rely on manual verification, which has the risk of information lag and underreporting.

[0053] Artificial Intelligence Algorithm Analysis: The tool collection and return data collected by the system is used to calculate the anomaly score using a preset algorithm. The specific formula is as follows: .

[0054] Abnormal behavior warning: For high-risk users, when the system scores reach the set threshold, it will restrict them from getting the tool again and notify the administrator to intervene. Such efficient automatic warning is not achieved in the existing technology, and problems are discovered manually.

[0055] By implementing the above steps, the test comparing the prior art and our invention was completed, and each data was recorded. The specific situation is shown in the following table: project Existing technology (manual management) Our invention (digital management) Advantages (Differences) Tool collection efficiency (average time per person) 5 minutes / person 1 minute / person Our system automatically processes and saves time Number of overdue tools (unit: piece) 20 5 Our system reduces overdue payments through real-time reminders and warnings Success rate of abnormal behavior warning (%) 40% 90% Our system uses AI analysis to accurately identify high risks Tool collection frequency (times / week) 150 times 150 times No difference Tool return timeliness rate (%) 75% 98% Our system improves return rate through multi-level reminders Number of administrator interventions (times / month) 10 2 Our system intelligent management reduces manual intervention It can be clearly seen from the above table that the digital management method invented by us has significant advantages over the existing technology in many aspects: 1. Tool collection efficiency: In the existing technology, since the tool collection requires manual registration and verification, the time for a single tool collection is relatively long (5 minutes per person). However, our invention realizes automated processing by combining RFID and facial recognition with the access control system, significantly reducing the time for a single tool collection to 1 minute per person, and increasing efficiency by 400%.

[0056] 2. Number of overdue tools: In the existing technology, the number of overdue tools is relatively large, mainly due to the lack of effective reminder and early warning mechanisms, which leads to the tools being occupied for a long time. By introducing our multi-level reminders and artificial intelligence analysis, the number of overdue tools has been reduced from 20 to 5, a reduction of 75%, which shows that our system has significant advantages in tool overdue management.

[0057] 3. Success rate of abnormal behavior warning: Our system uses artificial intelligence algorithms to analyze tool collection and return data, which can accurately identify high-risk users and has a 90% success rate in warning abnormal behavior. In comparison, existing technologies have only a 40% success rate in warning, and manual verification is prone to underreporting.

[0058] 4. Timely return rate of tools: Our system ensures that tools are returned in a timely manner through a timely multi-level reminder mechanism. The timely return rate is increased from 75% of the existing technology to 98%, demonstrating the innovation of our invention in optimizing return efficiency.

[0059] 5. Number of administrator interventions: Since most operations in the existing technology rely on manual processing, administrators intervene frequently, averaging 10 times per month. However, our invention greatly reduces the number of administrator interventions through digital management and intelligent early warning, only requiring 2 times, reducing 80% of manual intervention and improving the level of management automation.

[0060] Based on the above data analysis, the innovation of our invention in tool management is reflected in the application of intelligence and automation, especially in abnormal behavior warning, tool return management and overdue management. These advantages make our invention have great potential in improving tool management efficiency, reducing management costs and improving management quality.

[0061] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A digital tool management method for a power warehouse, characterized by: The specific steps include: S1: Install RFID tags on warehouse tools and enter basic information. At the same time, establish a personnel management system, enter authorized personnel information and generate a unique identity code through biometrics to achieve comprehensive digital management of tools and personnel; S2: Deploy an intelligent access control system combined with AI facial recognition at the warehouse entrance, equipped with RFID reading devices to automate personnel identity verification and tool collection processes, including real-time binding of tool information and reminder sending; S3: Configure a return detection point at the warehouse access control, confirm the tool return status through RFID scanning, update the record in real time and push reports to the administrator, and implement access control restrictions and reminder mechanisms for unreturned tools; S4: Use artificial intelligence algorithm analysis tools to collect and return data, identify abnormal behavior, generate risk level reports and push them to administrators, and implement permission restrictions for high-risk users; S5: Implement a multi-level reminder strategy to remind multiple times of tools that are about to be overdue, trigger a credit point deduction mechanism, and give points to recipients who return them in time. The points can be used to redeem warehouse benefits. S6: Regularly update RFID and AI analysis system algorithms, expand database storage capacity, introduce improved functions based on user feedback, and automatically generate tool usage efficiency reports to continuously optimize system management and performance.

2. The digital tool management method for power warehouse according to claim 1, characterized in that: The basic information of the tool includes the tool number, model, purpose and maintenance cycle; the information of the authorized personnel entered includes name, work number, contact information and authority level, which is used for subsequent data binding and operation records.

3. The digital tool management method for power warehouse according to claim 2, characterized in that: The access control system verifies the identity through facial recognition and records the entry and exit time of relevant personnel in the power warehouse; when picking up tools, personnel scan the required tools through RFID reading equipment, and the system automatically binds the recipient information and tool information, and prompts the usage time limit and sends a usage agreement reminder.

4. The digital tool management method for power warehouse according to claim 3, characterized in that: The AI ​​algorithm is used to calculate an anomaly score based on the tool pickup and return data, which is calculated according to the following formula: Among them, ω1, ω2, ω3, and ω4 are weight parameters obtained through historical data training, and N overdue is the number of overdue times, T overdue is the total overdue time, F borrow is the tool collection frequency, N not_returned is the number of unreturned tools, T total The total duration of the statistical period.

5. The digital tool management method for power warehouse according to claim 4, characterized in that: Set S threshold represents the threshold of the anomaly score. When the anomaly score S abnormal Exceeding the preset threshold S threshold When an abnormality occurs, the system marks the user as a high-risk user, automatically restricts the high-risk user's access to new tools, and generates a detailed report including the abnormality score and specific indicator values.

6. The digital tool management method for power warehouse according to claim 5, characterized in that: The threshold S for anomaly scoring threshold Dynamically adjust based on tool usage and historical data, and conduct comprehensive evaluation based on multi-dimensional user behavior.

7. The digital tool management method for power warehouse according to claim 6, characterized in that: Authority restrictions include limiting high-risk users’ access to new tools, extending the time limit for returning their tools, and limiting their access to specific tools.

8. The digital tool management method for power warehouse according to claim 7, characterized in that: The multi-level reminder strategy includes sending SMS and email reminders to the recipient within 24 hours, 12 hours and the last hour when the tool is about to expire and not returned, and notifying the warehouse manager to intervene.

9. The digital tool management method for power warehouse according to claim 8, characterized in that: Warehouse benefits include priority access to scarce tools or exchange for other warehouse benefits, such as additional tool usage time.

10. The digital tool management method for power warehouse according to claim 9, characterized in that: The system automatically generates tool usage efficiency reports by analyzing tool usage in real time, allowing administrators to optimize tool configuration and management strategies.

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