Electric power tool intelligent storage system

Abstract

The application relates to an intelligent power tool storage system, which comprises: preset toolboxes, which are classified according to work types, and each of the preset toolboxes is preset with several tools required by work; an interactive terminal, which is used for inputting work task information including work types, outputting tool carrying final suggestion information and real-time pushing alarm information; a multi-dimensional data acquisition system, which comprises an environment sensing device for acquiring environment state information and a state sensing device for acquiring tool use state information; and a cloud management platform, which is used for acquiring work task information, environment state information, tool use state information and historical data of work tasks, and pushing tool carrying final suggestion information and alarm information to the interactive terminal after generation. The application can reduce the dependence on manual operation, realize the intelligentization of power tool storage, improve work efficiency, reduce the risk of tool loss or damage and reduce cost.

Description

Technical Field

[0001] This invention relates to the field of continuous operation, and more specifically to an intelligent storage system for electrical tools used in continuous operation. Background Technology

[0002] The storage and use of electrical tools for non-live-line work typically follows this model: tools are stored in a power warehouse, where warehouse staff record their entry and exit information using paper registers or Excel spreadsheets. Before work begins, workers manually select the necessary tools (e.g., insulating gloves, voltage detectors) based on the task, counting and signing for each item. After work, when returning the tools, warehouse staff manually verify the quantity and condition and register them; a full warehouse check is also conducted daily. Each electrical tool is equipped with an RFID tag, and RFID readers scan the tags to generate entry and exit registration information. Therefore, current technology for storing and managing electrical tools relies on manual operation, resulting in low efficiency, high tool loss rates, high safety risks, and high management costs. Furthermore, the existing storage and use model for electrical tools cannot provide intelligent management tailored to specific work situations, also affecting the success of live-line work. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent storage system for power tools that can intelligently store and manage power tools, improve work efficiency and accuracy, reduce the risk of tool loss or damage, and reduce costs.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] An intelligent storage system for electrical tools, comprising:

[0006] A pre-set toolbox is provided, which is divided into several categories according to the type of work. Each category of the pre-set toolbox contains several tools and implements required for the work.

[0007] An interactive terminal is used by operators to input task information including the type of work, output final suggestions on carrying tools to operators, and push alarm information to operators in real time during the work process.

[0008] A multi-dimensional data acquisition system, comprising an environmental sensing device for acquiring environmental state information and a state sensing device set in the preset toolbox for acquiring the usage state information of the tools.

[0009] The cloud management platform communicates with the pre-set toolbox, the interactive terminal, the environmental sensing device, the status sensing device, and the external EAM system to obtain the job task information, the environmental status information, the usage status information of the tools, and the historical data of the job task. After generating the final suggestion information and the alarm information carried by the tools, it pushes them to the interactive terminal.

[0010] According to one embodiment of the present invention, the cloud management platform includes:

[0011] The information acquisition module is used to acquire the job task information from the interactive terminal, the environmental status information from the environmental sensing device, the usage status information of the tools from the status sensing device, and the historical data of the job task from the EAM system.

[0012] The risk assessment module is used to perform a multi-dimensional risk assessment of the task based on the task information, the environmental status information, and the historical data of the task, and to obtain a graded risk assessment result and a corresponding graded response strategy.

[0013] The tool and equipment demand prediction module is used to predict preliminary suggestions for carrying tools and equipment based on the work task information, the historical data of the work task, and the tool and equipment demand prediction model.

[0014] The cost-benefit analysis module is used to calculate the cost of the tool carrying preliminary suggestion information based on the work task information and the historical data of the work task to obtain cost information.

[0015] The suggestion generation module is used to integrate the graded risk assessment results, the graded response strategy, the preliminary suggestion information carried by the tool and the cost information to obtain the final suggestion information carried by the tool and push it to the interactive terminal.

[0016] A real-time early warning module is used to generate alarm information based on the environmental status information and the usage status information of the tools and push it to the interactive terminal.

[0017] Preferably, in the risk assessment module, the method for conducting multi-dimensional risk assessment is as follows: multiple risk levels are pre-divided according to the level of the comprehensive risk index and a response strategy corresponding to each risk level is specified; the comprehensive risk score of the current task is assessed based on the working voltage level, working environment risk, and worker risk; the comprehensive risk score of the current task is assigned to the corresponding risk level, thereby obtaining the graded risk assessment result and the corresponding graded response strategy.

[0018] Further preferably, risk scores are obtained for the operating voltage level, the operating environment risk, and the operator risk, respectively. A weighted summation method is used to calculate the comprehensive risk score. The risk score corresponding to the operating voltage level increases with the increase of the operating voltage level. If the operating environment humidity reaches a preset humidity threshold, the risk score corresponding to the operating voltage level is increased by the corresponding set value. If the insulation state index of the tools reaches a preset insulation state threshold, the risk score corresponding to the operating voltage level is increased exponentially. If the ambient temperature reaches a preset high temperature threshold, the operating height reaches a preset height threshold, or the weather is rainy or snowy, the risk score corresponding to the operating environment risk is increased by the corresponding set value. If the operator's years of service are lower than a set years threshold or the number of operators is lower than a preset number of operators threshold, the risk score corresponding to the operator risk is increased by the corresponding set value.

[0019] A preferred embodiment is that the tool and equipment demand prediction module adopts a tool and equipment demand prediction model based on Bayesian networks. The output of the tool and equipment demand prediction model includes the basic demand quantity, suggested redundancy quantity, and total carrying quantity for each type of tool and equipment.

[0020] In one embodiment, the basic required quantity of each tool is determined according to the job type, the preliminary recommended redundancy quantity of each tool is determined using environmental risk factors, and the preliminary recommended redundancy quantity of each tool is adjusted based on historical data of tool damage and loss, job terrain conditions, and the years of experience of the workers to obtain the output recommended redundancy quantity of each tool.

[0021] Furthermore, in the suggestion generation module, based on the graded risk assessment results, the graded response strategy, and the cost information, the preliminary suggestion information for tool carrying is optimized to obtain the final suggestion information for tool carrying.

[0022] Preferably, the cloud management platform also automatically adjusts and optimizes parameters based on historical data of the task.

[0023] Preferably, the cloud management platform is also used to perform data cleaning and feature construction on the environmental status information and the usage status information of the tools; and to perform data cleaning on the environmental status information using a sliding window mid-value filtering method.

[0024] Furthermore, the pre-installed toolbox includes a box body, an inner liner disposed within the box body, and an RFID module disposed within the box body capable of RFID scanning the tools.

[0025] Due to the application of the above technical solutions, the present invention has the following advantages compared with the prior art: the present invention improves the storage method of electrical tools, reduces the reliance on manual operation, realizes intelligent storage of electrical tools, improves work efficiency, reduces the risk of tool loss or damage, and also reduces costs. Attached Figure Description

[0026] Appendix Figure 1 This is a schematic diagram of the cloud management platform architecture in the intelligent storage system for power tools of the present invention.

[0027] Appendix Figure 2 This is a schematic diagram of the internal structure of the pre-set toolbox in the intelligent storage system for power tools of the present invention.

[0028] Appendix Figure 3 This is a schematic diagram of the antenna distribution of the pre-set toolbox in the intelligent storage system for power tools of the present invention.

[0029] Appendix Figure 4 This is a schematic diagram of the internal structure of the insulating operation box in the intelligent storage system for power tools of the present invention.

[0030] Appendix Figure 5 This is a schematic diagram of the structure of the insulating operation box and insulating blanket in the intelligent storage system for power tools of the present invention.

[0031] Appendix Figure 6 This is a schematic diagram of the structure of the insulating operation box and insulating clamp in the intelligent storage system for power tools of the present invention.

[0032] Appendix Figure 7 This is a schematic diagram of the structure of the insulated operation box and the insulated scissors in the intelligent storage system for power tools of the present invention.

[0033] Appendix Figure 8 This is a schematic diagram of the measuring box and digital multimeter in the intelligent storage system for power tools of the present invention. Detailed Implementation

[0034] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0035] Example 1: An intelligent storage system for power tools includes a pre-set toolbox, an interactive terminal, a multi-dimensional data acquisition system, and a cloud management platform, wherein the pre-set toolbox, the interactive terminal, and the multi-dimensional data acquisition system can all interact with the cloud management platform.

[0036] Pre-positioned toolboxes are used to store electrical tools, enabling the issuance and return of entire boxes of electrical tools from the warehouse. Pre-positioned toolboxes are categorized according to job type, with each category containing several tools required for the job. Multiple boxes of each category are provided for use. For example, based on the job types in the power industry, three standardized pre-positioned toolboxes are defined: Insulation Operation Box, Measuring Box, and Emergency Repair Box. The Insulation Operation Box contains 12 types / pieces of tools required for insulation operations, such as insulating gloves, insulating rods, and insulating blankets. The Measuring Box contains 8 types / pieces of tools required for measuring operations, such as clamp meters, multimeters, and infrared thermometers. The Emergency Repair Box contains 15 types / pieces of tools required for emergency repair operations, such as cable connectors, insulating tape, and screwdriver sets.

[0037] The pre-assembled toolbox includes a box body 1, an inner liner 2 housed within the box body, and an RFID module housed within the box body 1 capable of scanning RFID tags on tools. The box body 1 is made of multi-layered sheet metal, while the inner liner 2 is made of custom-made EVA foam material, molded to fit the shape of each tool, with corresponding slots for each tool. The tools inserted into the corresponding slots are in an interference fit with the EVA foam liner 2, ensuring zero displacement during transportation. The sheet metal, from the outside in, comprises an outer carbon fiber layer, an XPS foam layer, a shielding layer, an inner carbon fiber layer, and a cushioning layer. The shielding layer includes a copper-nickel alloy layer and a copper mesh layer. The RFID module in the box body can also communicate with RFID readers in the power warehouse.

[0038] As attached Figure 2 As shown, the inner lining 2 includes a shock-absorbing and protective area 3 that fits snugly against the box body and a filling area 4 divided into multiple zones. An RFID module is located in the electronic control area 5 within this area. (See attached diagram) Figure 3 As shown, the RFID module is equipped with four sets of UHF RFID antennas 6, ensuring that its signal completely covers the interior space of the enclosure 1. (See attached diagram.) Figure 4As shown, the insulated operating box is equipped with tools such as an insulating blanket (7), insulating large scissors (8), a set of insulating grippers (9), a shielding cover, and an insulating locking rod (10). (See attached...) Figure 5 As shown, an RFID tag 11 is attached to one corner of the insulating blanket 7. (See attached image) Figure 6 As shown, an RFID tag 12 is attached to one side of the clamping jaw 9. A set of insulating jaws 9 is housed within the casing 1 of the insulating operation box. This allows for easy handling and management of the entire set of insulating jaws 9, preventing them from becoming scattered. (See attached...) Figure 7 As shown, the insulated large scissors 8 have an RFID chip 13 installed on their handle. (See attached image) Figure 8 As shown, the RFID chip 15 is installed on the main board of the multimeter 14.

[0039] In addition, the following structures can be configured for the pre-installed toolbox: a vibration sensor (e.g., a gyroscope built into the main control board for vibration detection) can be installed inside the toolbox to detect vibrations and thus determine the handling and use of tools. For digital multimeters, dedicated probe bays and probe anti-loss slots are provided. Insulating tape storage slots are equipped with tape fixing brackets to prevent rolling, and a gravity sensor can also be added to weigh the insulating tape to prevent loss. Cable connector assemblies are configured with modular trays, with bolts embedded in magnetic bases for easy retrieval as a whole.

[0040] The interactive terminal is located in the power storage room or carried by the operators. It is used by the operators to input work task information, including the type of work, to output final suggestions on tool carrying, and to push alarm information to the operators in real time during the work process. The interactive terminal can be implemented using a smart device with corresponding programs written into it.

[0041] The multi-dimensional data acquisition system is used to collect data and upload it to the cloud management platform. It mainly includes environmental sensing devices for collecting environmental status information and status sensing devices installed in a pre-set toolbox for collecting the usage status information of tools and equipment. Environmental sensing devices include temperature detection devices and humidity detection devices. Status sensing devices include positioning devices (including GPS and / or 4G positioning), RFID / NFC chips, strain gauges, and accelerometers for obtaining the location of the pre-set toolbox.

[0042] The cloud management platform communicates with the pre-built toolbox, interactive terminal, environmental sensing device, status sensing device, and external EAM system. It is used to obtain job task information, environmental status information, tool usage status information, and historical data of job tasks. After generating tools carrying final suggestion information and alarm information, it pushes them to the interactive terminal.

[0043] As attached Figure 1As shown in this embodiment, the cloud management platform includes an information acquisition module, a risk assessment module, a tool and equipment demand forecasting module, a cost-benefit analysis module, and a suggestion generation module connected in sequence, and also includes a real-time early warning module.

[0044] The information acquisition module is used to acquire job task information from the interactive terminal, environmental status information from the environmental sensing device, usage status information of tools and equipment from the status sensing device, and historical data of job tasks from the EAM system.

[0045] The risk assessment module is used to conduct multi-dimensional risk assessments of work tasks based on task information, environmental status information, and historical data, resulting in tiered risk assessment results and corresponding tiered response strategies. Specifically, the multi-dimensional risk assessment method in the risk assessment module is as follows: Multiple risk levels are pre-defined according to the comprehensive risk index, and corresponding response strategies are specified for each risk level. Based on the voltage level, environmental risk, and personnel risk, the comprehensive risk score of the current task is assessed, and this score is then assigned to the corresponding risk level, thus obtaining the tiered risk assessment results and corresponding tiered response strategies.

[0046] For example, for operating voltage levels, a risk score is set according to the operating voltage level (10kV / 20kV / 35kV, etc.), and the risk score increases as the operating voltage level increases. If the ambient humidity reaches a preset humidity threshold (e.g., 80%), the insulation risk increases, and the risk score corresponding to the operating voltage level increases by the corresponding set value. If the insulation condition index of the tools reaches a preset insulation condition threshold, the risk score corresponding to the operating voltage level increases exponentially. For operating environment risks, if the ambient temperature reaches a preset high temperature threshold (e.g., 38℃), the operating height reaches a preset height threshold (e.g., 5m), or the weather is rainy or snowy, the risk of heat dissipation from electrical equipment increases, the risk of working at height increases, or the risk of slippery conditions increases, and the risk score corresponding to the operating environment risk increases by the corresponding set value. For personnel risks, if the number of years of service of the personnel is less than a set service life threshold (e.g., 2 years) or the number of personnel is less than a preset number of personnel threshold, the risk score corresponding to the personnel risk increases by the corresponding set value. Finally, risk scores were obtained for each of the following: operating voltage level, operating environment risk, and operator risk. A weighted sum was then used to calculate the overall risk score. To reflect the characteristics of the power industry, the weighting is typically 40% for operating voltage level, 30% for operating environment risk, 20% for operator risk, and 10% for management risk.

[0047] The pre-defined risk levels are divided into three categories: high risk, medium risk, and low risk, with each level corresponding to a range of comprehensive risk scores. For high risk, response strategies include dual-person monitoring and work suspension. For medium risk, response strategies include increased patrols and shortened shift rotation cycles. For low risk, normal operations should be performed. Additionally, improvement suggestions can be set, such as "checking the dryness of insulated tools" and "carrying portable cooling devices."

[0048] The tool and equipment demand prediction module is used to predict preliminary suggestions for tool and equipment carrying based on job task information, historical data of the job tasks, and a tool and equipment demand prediction model. In this embodiment, the tool and equipment demand prediction module uses a Bayesian network-based tool and equipment demand prediction model. The output of the tool and equipment demand prediction model includes the basic demand quantity, suggested redundancy quantity, and total carrying quantity for each type of tool and equipment.

[0049] For example, the main inputs of the tool and equipment demand forecasting model include: current job type (insulation operation, measurement and testing or emergency repair), real-time environmental parameters (temperature, humidity, altitude, weather), historical data (average damage rate and loss rate of tools and equipment under similar operations), and work team information (number of personnel, average work experience, safety score). (1) Determine the basic demand quantity of each tool and equipment according to the job type. (2) Determine the preliminary recommended redundancy quantity of each tool and equipment using environmental risk factors. For example, when the ambient temperature is >35℃ or the humidity is >80%, increase the redundancy quantity of the relevant tools and equipment. (3) Adjust the preliminary recommended redundancy quantity of each tool and equipment based on the historical data of tool and equipment damage and loss, the work terrain conditions and the years of work experience of the workers, and obtain the recommended redundancy quantity of each tool and equipment output. Specifically, this includes: deriving a baseline failure rate based on historical data and further amplifying the probability of loss by considering current terrain complexity (e.g., mountainous areas, waterways); setting a minimum safety redundancy: for critical tools involving personal safety (e.g., insulated gloves, voltage detectors), mandatory 100% backup is required; considering differences in personnel capabilities: if the average experience of team members is less than 2 years, overall redundancy configuration is increased to compensate for the risk of operational errors due to insufficient skills. Based on this, the final output yields the basic required quantity, recommended redundancy quantity, and total quantity carried for each type of tool. Redundancy coefficients can be set, adjusted based on the above principles, and finally, the redundancy quantity of tools is calculated based on the redundancy coefficients.

[0050] The cost-benefit analysis module is used to calculate the cost of preliminary suggestions for tool carrying based on job task information and historical data. The module includes a built-in lifecycle cost accounting model covering the following cost items: tool purchase cost; routine maintenance and inspection costs; expected damage loss (based on historical damage rate × unit price × usage frequency); and expected loss loss (based on historical loss rate × unit price × number of visits). Cost calculations are performed separately for the basic tool carrying plan (basic required quantity) and the suggested plan (suggested redundancy quantity and total carrying quantity).

[0051] The suggestion generation module integrates the results of tiered risk assessment, tiered response strategies, preliminary suggestions for tool carrying, and cost information to obtain final suggestions for tool carrying, which are then pushed to the interactive terminal. Within this module, the preliminary suggestions for tool carrying are optimized based on the tiered risk assessment results, tiered response strategies, and cost information to arrive at the final suggestions. Key steps include: receiving basic configuration suggestions from the tool demand forecasting module; enhancing the configuration for high-risk projects based on the conclusions of the risk assessment module; introducing a cost control mechanism: for non-critical general-purpose tools, appropriately reducing the number carried to save costs while meeting minimum safety redundancy; comparing the cost-effectiveness of different configuration schemes and recommending the most cost-effective solution; generating a structured report containing a tool list, safety tips, special instructions, etc., and pushing it to the operator's interactive terminal.

[0052] Based on the above system, the outbound process for electrical tools is as follows: Operators submit task information via an interactive terminal. The system automatically performs risk assessment, tool demand forecasting, cost-benefit analysis, and ultimately generates recommendations. It automatically pushes matching pre-configured toolboxes (e.g., "Insulation Operation Task" → Insulation Operation Box) to the operator and provides final tool carrying recommendations for confirmation. Operators carry the pre-configured toolbox through the power warehouse access control system. The entire box is automatically scanned by an RFID reader (no need to open the box). The system automatically records the outbound information of the corresponding pre-configured toolbox, and the positioning module within the toolbox is simultaneously activated, uploading the location to the cloud management platform in real time. The return process for electrical tools is as follows: The pre-configured toolbox is placed back in the designated area of ​​the power warehouse. RFID automatically triggers a scan, comparing the current tool status with the RFID module of the corresponding pre-configured list, confirming any abnormalities, and triggering an alarm if an abnormality is detected. The RFID module scans the tools and equipment in the pre-set toolbox when the lid is closed. During operation after the lid is open, the RFID module scans the tools and equipment at predetermined intervals. The scan results are used only as a record of the usage process and are applied to calculate and evaluate the breakage rate of different tools and the wear and tear at different work locations and types. After scanning, the data is automatically archived, and a work report is generated, realizing the identification and status update of all tools and equipment in the box.

[0053] The positioning module in the pre-set toolbox can be used to prevent loss. If the pre-set toolbox is not returned within the time limit or leaves the work area, an alarm can be triggered and the last location point can be displayed.

[0054] During uninterrupted power supply operations using tools and equipment, the real-time early warning module of the cloud management platform generates alarm information and pushes it to the interactive terminal based on environmental status information and tool usage status information. The cloud management platform receives various data in real time to determine whether there are any "sudden environmental changes" or "equipment malfunctions." If a significant deviation is detected (such as a temperature rise exceeding 5°C / 10 minutes or a certain insulating tool nearing the end of its lifespan), an alarm is immediately triggered; it automatically generates response suggestions, such as "suspend work," "replace with a spare tool," or "dispatch additional monitoring personnel"; and pushes the instructions to the on-site interactive terminal to remind the operators to respond promptly.

[0055] The cloud-based management platform can also automatically adjust and optimize parameters based on historical data of job tasks. The system periodically reviews completed tasks, evaluating the accuracy of initial predictions and their consistency with actual results, primarily focusing on aspects such as safety performance, cost deviations, efficiency performance, and tool and equipment compatibility. Based on this feedback data, the system automatically identifies poorly performing prediction dimensions (such as the underestimated impact of humidity on insulating tools) and achieves self-optimization by adjusting model parameters (such as increasing the weight of the humidity factor). Through continuous system evolution, it can continuously improve prediction accuracy with data accumulation, truly becoming "smarter with use," aligning with the development trend of artificial intelligence systems.

[0056] Due to the complex working environment of power plants (such as strong electromagnetic interference, sudden weather changes, and human error), raw data collection often contains outliers, drift, and missing values. Therefore, the cloud management platform is also used for data cleaning and feature construction of environmental status information and tool usage status information. For environmental status information collected by sensors, such as parameters affected by interference like temperature, humidity, and GPS signals, a sliding window midpoint filtering method is used for data cleaning, and a reasonable threshold range conforming to power industry standards is set (e.g., temperature -20℃ to 60℃). Data outside the range is considered invalid and replaced with the nearest valid value. Insulating tool status marking: Based on the last inspection date of the tool and its usage frequency, it is automatically determined whether it is in an "overdue inspection" or "high-frequency use" state, generating a binary risk flag. Geographic coordinate mapping: GPS coordinates are matched in real time to the nearest power distribution line segment or tower number to achieve accurate spatial attribution. Feature construction: Several key feature variables are derived from the raw data, such as "high temperature exposure duration," "proportion of insulating tools used in high humidity environments," and "proportion of operations in mountainous terrain," for subsequent modeling.

[0057] The above solution addresses issues such as unreasonable tool configuration, delayed safety risk warnings, and serious resource waste in traditional live-line work.

[0058] A specific application example is as follows: A power supply company in a certain city plans to carry out live-line work on a 10kV overhead line during the high temperature of summer. The location is in the suburban mountainous area, and the expected working height is about 8 meters. The work will be carried out by a young team with an average of 1.5 years of experience.

[0059] System operation process:

[0060] 1. After obtaining the task information, the system retrieves the local weather forecast: the highest temperature that day reaches 39℃, and the relative humidity is 78%;

[0061] 2. Historical data shows that the damage rate of insulating gloves in similar summer operations in this area over the past three years reached 12%, which is higher than the average level;

[0062] 3. The risk assessment model classifies this operation as "high-risk," primarily due to: high temperature, high humidity, inexperienced work crew, and working at height.

[0063] 4. Tool and equipment requirements model recommendation: In addition to the standard configuration, carry two extra pairs of the same model of insulating gloves as backups, and equip a portable air cooler;

[0064] 5. Cost analysis shows that although the investment increases by about 600 yuan, it can reduce the risk of returning to pick up equipment midway by more than 80%, and the overall benefits are significant.

[0065] 6. After the operation began, the system detected that the temperature rose to 41°C within half an hour and immediately issued a red alert: "Immediately activate the rotation mechanism and change the operators every 20 minutes."

[0066] 7. The final operation was completed successfully without any safety incidents or damage to the tools.

[0067] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. An intelligent storage system for electrical tools, characterized in that: The intelligent storage system for electrical tools includes: A pre-set toolbox is provided, which is divided into several categories according to the type of work. Each category of the pre-set toolbox contains several tools and implements required for the work. An interactive terminal is used by operators to input task information including the type of work, output final suggestions on carrying tools to operators, and push alarm information to operators in real time during the work process. A multi-dimensional data acquisition system, comprising an environmental sensing device for acquiring environmental state information and a state sensing device set in the preset toolbox for acquiring the usage state information of the tools. The cloud management platform communicates with the pre-set toolbox, the interactive terminal, the environmental sensing device, the status sensing device, and the external EAM system to obtain the job task information, the environmental status information, the usage status information of the tools, and the historical data of the job task. After generating the final suggestion information and the alarm information carried by the tools, it pushes them to the interactive terminal. The cloud management platform includes: The information acquisition module is used to acquire the job task information from the interactive terminal, the environmental status information from the environmental sensing device, the usage status information of the tools from the status sensing device, and the historical data of the job task from the EAM system. The risk assessment module is used to perform a multi-dimensional risk assessment of the task based on the task information, the environmental status information, and the historical data of the task, and to obtain a graded risk assessment result and a corresponding graded response strategy. The tool and equipment demand prediction module is used to predict preliminary suggestions for carrying tools and equipment based on the work task information, the historical data of the work task, and the tool and equipment demand prediction model. The cost-benefit analysis module is used to calculate the cost information by performing cost accounting on the preliminary suggestion information for carrying the tools and equipment based on the work task information and the historical data of the work task. The suggestion generation module is used to integrate the graded risk assessment results, the graded response strategy, the preliminary suggestion information carried by the tool and the cost information to obtain the final suggestion information carried by the tool and push it to the interactive terminal. A real-time early warning module is used to generate alarm information based on the environmental status information and the usage status information of the tools and push it to the interactive terminal.

2. The intelligent storage system for power tools according to claim 1, characterized in that: In the risk assessment module, the method for conducting multi-dimensional risk assessment is as follows: multiple risk levels are pre-divided according to the level of the comprehensive risk index and a response strategy corresponding to each risk level is specified. The comprehensive risk score of the current task is assessed based on the working voltage level, working environment risk, and worker risk. The comprehensive risk score of the current task is then assigned to the corresponding risk level to obtain the graded risk assessment result and the corresponding graded response strategy.

3. The intelligent storage system for power tools according to claim 2, characterized in that: Risk scores are obtained for the operating voltage level, the operating environment risk, and the operator risk, respectively. A weighted summation of these risk scores yields the overall risk score. The risk score corresponding to the operating voltage level increases with increasing voltage level. If the ambient humidity reaches a preset humidity threshold, the risk score corresponding to the operating voltage level increases by the corresponding set value. If the insulation state index of the tools reaches a preset insulation state threshold, the risk score corresponding to the operating voltage level increases exponentially. If the ambient temperature reaches a preset high temperature threshold, the operating height reaches a preset height threshold, or the weather is rainy or snowy, the risk score corresponding to the operating environment risk increases by the corresponding set value. If the operator's years of experience are lower than a preset years threshold or the number of operators is lower than a preset number of operators threshold, the risk score corresponding to the operator risk increases by the corresponding set value.

4. The intelligent storage system for power tools according to claim 1, characterized in that: The tool and equipment demand prediction module employs a Bayesian network-based tool and equipment demand prediction model. The output of the tool and equipment demand prediction model includes the basic demand quantity, suggested redundancy quantity, and total carrying quantity for each type of tool and equipment.

5. The intelligent storage system for electrical tools according to claim 4, characterized in that: The basic required quantity of each tool is determined based on the type of work. An initial recommended redundancy quantity for each tool is determined using environmental risk factors. The initial recommended redundancy quantity for each tool is adjusted based on historical data of tool damage and loss, work terrain conditions, and the years of experience of the workers to obtain the output recommended redundancy quantity for each tool.

6. The intelligent storage system for power tools according to claim 1, characterized in that: In the suggestion generation module, based on the graded risk assessment results, the graded response strategy, and the cost information, the preliminary suggestion information for tool carrying is optimized to obtain the final suggestion information for tool carrying.

7. The intelligent storage system for power tools according to claim 1, characterized in that: The cloud management platform also automatically adjusts and optimizes parameters based on historical data of the job tasks.

8. The intelligent storage system for power tools according to claim 1, characterized in that: The cloud management platform is also used to perform data cleaning and feature construction on the environmental status information and the usage status information of the tools; and to perform data cleaning on the environmental status information using a sliding window mean filtering method.

9. The intelligent storage system for power tools according to claim 1, characterized in that: The pre-installed toolbox includes a box body, an inner liner disposed in the box body, and an RFID module disposed in the box body and capable of RFID scanning the tools.

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