New energy intelligent safety team system

Abstract

The invention discloses a new energy intelligent safety team system, and relates to the technical field of new energy, the new energy intelligent safety team system comprises a central regulation and control module, the central regulation and control module is in communication connection with a field operation management module, an educational training module, a risk pre-control module, a hidden danger checking and emergency management module and an intelligent hardware integration module, and the field operation management module is used for providing operation guidance for team personnel through the intelligent terminal, pushing safety risk information in an operation environment in real time, and performing task allocation, progress tracking and completion condition feedback. According to the invention, by monitoring key information such as the working state of team personnel, the equipment operation condition and the environmental parameters in real time, abnormal or potential risks are found in time, and related information is automatically pushed to management personnel, so that the safety management capability of the team is enhanced, safety accidents are effectively prevented, and the safety of personnel and property is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a new energy smart safety team system. Background Art

[0002] The new energy smart safety team is a team management model that adapts to the development needs of the new energy field and has significant application effects. This management model integrates information technology such as "management platform + smart terminal + APP" to intelligently manage each link of the team's safety construction, operation plan, risk control, hidden danger investigation, etc. The team, as the cornerstone of production and operation activities in the new energy power generation industry, plays the most basic and vital role. Its management efficiency and operation level are not only a direct reflection of the company's execution strength, production and operation management level and market competitiveness, but also profoundly affect the company's overall operating efficiency and safety and stability.

[0003] In the existing technology, the work of new energy teams is generally decentralized, and they often face multiple risks such as falling from heights, electric shock, traffic accidents, lifting injuries and mechanical injuries. Especially in the wind power industry, production safety accidents occasionally occur, which makes EHS management face huge challenges. At present, the team's production safety management is fragmented and scattered, and lacks a systematic and standardized management system. This not only affects the team's safe operation efficiency, but also restricts the improvement of the company's overall safety management level. Therefore, building a systematic and standardized team production safety management system has become an important issue that needs to be urgently solved in the new energy power generation industry. Summary of the invention

[0004] The purpose of the present invention is to provide a new energy intelligent safety team system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] The new energy smart safety team system includes a central control module, which is communicatively connected to a field operation management module, an education and training module, a risk pre-control module, a hidden danger investigation and emergency management module, and an intelligent hardware integration module, wherein electrical signals are connected between the modules;

[0007] The field operation management module is used to provide operation guidance to the team members through intelligent terminals such as tablet computers and smart phones, push safety risk information in the operation environment in real time, and perform task allocation, progress tracking and completion status feedback to achieve closed-loop management of tasks. At the same time, it manages the organization and coordination of third-party personnel related to the project, such as contractors and suppliers, as well as the application, approval, maintenance and scheduling of the use of field tools and vehicles to ensure efficient use of resources. Among them, risk information, including environmental risks, equipment failure risks, human operation risks, etc., improves the risk awareness of operators;

[0008] The education and training module is used to formulate training plans according to the needs of the team, including safety training, skills training, etc., and supports various training forms such as online learning and video tutorials. It also manages team safety activities, such as regular safety meetings and emergency drills, to ensure that the activities are carried out in an orderly manner, and records and archives safety activity materials for subsequent review and summary. At the same time, it regularly conducts performance evaluations on teams and individuals, including work performance, safety performance and other dimensions, to provide a basis for rewards and punishments;

[0009] The risk pre-control module is used to accurately identify and evaluate the safety risks in the operation process through data analysis and model prediction, and to issue early warnings for the identified risks and give corresponding prevention and control measures to ensure that the risks are effectively controlled. At the same time, it is linked with the hidden danger investigation and emergency management module to timely discover and report potential safety hazards and avoid the occurrence of safety accidents;

[0010] The hidden danger investigation and emergency management module is used to establish a hidden danger database, register, circulate and manage hidden dangers in a closed loop online to ensure that hidden dangers are rectified in a timely manner, and formulate and implement online sharing of emergency plans, emergency team and material management and emergency drill plans. When an emergency occurs, it can quickly respond and implement emergency plans to reduce accident losses;

[0011] The intelligent hardware integration module is used to integrate with the intelligent safety helmet and intelligent lock hardware devices to achieve data synchronization and intelligent control.

[0012] A further improvement of the technical solution of the present invention is that: the field operation management module includes a pre-shift and post-shift meeting unit, a task management unit, a tool management unit, a vehicle management unit and a related party management unit, wherein the units are connected by electrical signals;

[0013] The pre-shift and post-shift meeting unit is used to push the team's daily tasks, tasks assigned by superior departments, and the team's weekly and monthly work plans through smart terminals;

[0014] The task management unit is used to assign work tasks according to the skills of team members, monitor the progress of task execution in real time, collect and display the task completion status, so that the management can understand the project progress;

[0015] The tool management unit is used to support team members to apply for required tools online, automate the approval process, reduce waiting time, and record the maintenance history and current status of tools to arrange scheduling reasonably;

[0016] The vehicle management unit is used to reasonably arrange vehicle use according to operational requirements, and record vehicle maintenance records and maintenance plans to ensure good vehicle performance, while also performing real-time safety monitoring of vehicles to prevent traffic accidents;

[0017] The stakeholder management unit is used to communicate with third parties, coordinate work progress and resource allocation, manage contract information of stakeholders, ensure compliance, and promptly respond to and resolve issues arising from cooperation with third parties.

[0018] The further improvement of the technical solution of the present invention is that: the process of performance evaluation of teams and individuals is: according to the development strategy of the enterprise, the needs of the department and the development needs of the individual employees, the specific goals of the training are clarified;

[0019] Upload learning materials for the safety day activities in a specific time period, including documents, videos, PPT and other forms. Team members can view the learning materials through smart terminals and choose and reserve the activity time and location according to their own needs.

[0020] A further improvement of the technical solution of the present invention is that: the process of early warning of the identified risks is:

[0021] Collecting work site data, including equipment operation data, environmental data, personnel operation records, historical accident data, and pre-processing the collected work site data;

[0022] Clean and integrate the collected equipment operation data, environmental data, personnel operation records, and historical accident data to form a unified data set;

[0023] Based on the pre-processed work site data, the abnormal risk factors associated with the work site data are extracted, where the abnormal risk factors include equipment failure factors, environmental abnormality factors and human operation error factors. The historical accident data is analyzed and combined with the abnormal risk factors to build a risk prediction model, obtain the equipment failure index, environmental abnormality index and human operation error index, and predict the probability of occurrence and potential impact of safety risks.

[0024] Based on the acquired equipment failure index, environmental anomaly index and human operation error index, the risk assessment coefficient is obtained, and combined with historical accident data, different risk levels of safety risk situations are determined, and risk assessment thresholds are set for different risk levels;

[0025] Combine risk warning with hidden danger investigation, focus on investigating high-risk areas and links in warning, and promptly discover and report potential safety hazards;

[0026] Use the constructed risk prediction model to quantitatively assess the safety risks in the operation process, determine the risk level of the current safety risk, obtain the risk assessment results, generate corresponding early warning information according to the corresponding risk level, and formulate and implement corresponding prevention and control measures.

[0027] A further improvement of the technical solution of the present invention is that the process of collecting the work site data is as follows:

[0028] Collect real-time operating parameters of equipment, such as temperature, pressure, vibration, etc., as well as equipment maintenance and fault records;

[0029] Use environmental monitoring equipment, such as temperature and humidity sensors, gas concentration sensors, etc., to collect environmental parameters at the work site, including weather conditions, noise levels, lighting conditions, air quality, etc.;

[0030] Track personnel location and operation behavior, including operation time, operation content, operator identity, etc., through video surveillance, RFID and manual records, and store them in the database;

[0031] Organize and analyze past accident cases, including the causes of the accidents, scope of impact, handling measures and results.

[0032] A further improvement of the technical solution of the present invention is that the process of predicting the probability of occurrence and potential impact of security risks is:

[0033] Perform feature encoding on the associated data of equipment failure factors, environmental anomaly factors, and human operation error factors, build a risk prediction model, and use the data set to train the risk prediction model;

[0034] The integrated data set is divided into a training set, a validation set, and a test set. The risk prediction model is trained using the training set data, and the trained risk prediction model is validated using the validation set and the test set data to evaluate the performance of the risk prediction model.

[0035] Use the trained model and pre-processed job site data to obtain the equipment failure index, environmental anomaly index, and human operation error index, and analyze the correlation between equipment failure, environmental anomaly, and human operation error;

[0036] The calculation formula of the equipment failure index is:

[0037]

[0038] Among them, FI is the equipment failure index, Fc is the number of equipment failures, F r is the equipment failure rate, λ is the failure rate constant, and t is the actual value;

[0039] The calculation formula of the environmental anomaly index is:

[0040]

[0041] Among them, EI is the environmental anomaly index, E i is the actual measured value of the i-th environmental parameter, E s is the standard value of the environmental parameter, n is the number of environmental parameters, T is the current temperature, T s is the standard temperature, θ is the temperature sensitivity coefficient;

[0042] The calculation formula of the personnel operation error index is:

[0043]

[0044] Among them, HI is the human operation error index, N is the number of human operation errors in the past month, N is the total number of operations, and P r is the current operation error rate, P s is the standard operating error rate.

[0045] A further improvement of the technical solution of the present invention is that the process of setting risk assessment thresholds for different risk levels is as follows:

[0046] Combine the equipment failure index, environmental anomaly index, human operation error index and historical accident data to analyze the correlation between safety risks and equipment failure factors, environmental anomaly factors and human operation error factors;

[0047] And perform weighted calculations on the equipment failure index, environmental anomaly index and human operation error index to obtain the risk assessment coefficient;

[0048] According to the pre-processed work site data, the safety risk conditions in the historical accident data are matched to determine different risk levels, namely low risk level, medium risk level, high risk level and extremely high risk level, among which the safety risk conditions of the risk level increase step by step from low risk level to extremely high risk level;

[0049] The determined different risk levels are matched with the results of the risk assessment coefficients, and corresponding risk assessment thresholds are set for different risk levels;

[0050] The calculation formula of the risk assessment coefficient is:

[0051]

[0052] Among them, RAI is the risk assessment coefficient, α is the weight coefficient, β is the attenuation factor, γ is the risk growth rate, δ is the standard deviation adjustment factor, FI is the equipment failure index, EI is the environmental abnormality index, and HI is the personnel operation error index;

[0053] The multiple risk levels correspond to the multiple risk assessment thresholds satisfying the following relationship:

[0054] Low risk level 0≤RAI <D A ;

[0055] Medium risk level D A ≤RAI <D B ;

[0056] High risk level D B ≤RAI <D C ;

[0057] Very high risk level D C ≤RAI≤1;

[0058] Among them, RAI is the risk assessment coefficient, D A is the upper threshold corresponding to the low risk level and the lower threshold corresponding to the medium risk level, D B is the upper threshold corresponding to the medium risk level and the lower threshold corresponding to the high risk level, D C is the upper threshold corresponding to the high risk level and the lower threshold corresponding to the extremely high risk level, D A =0.2, D B =0.5, D C =0.8.

[0059] A further improvement of the technical solution of the present invention is that the process of formulating and implementing corresponding prevention and control measures is:

[0060] The pre-processed characteristic data of equipment failure, environmental anomaly and human operation error are input into the risk prediction model to calculate the equipment failure index, environmental anomaly index and human operation error index respectively;

[0061] Combine the calculation results of equipment failure index, environmental abnormality index and human operation error index to calculate the value of risk assessment coefficient, match the preset risk assessment threshold and determine the corresponding risk level;

[0062] Prepare corresponding early warning information based on the determined risk level. The early warning information should include the risk level, risk description, possible scope of impact and recommended initial response measures. At the same time, the early warning information should be sent to relevant personnel in a timely manner, including on-site operators, safety managers and departments or personnel that may be affected, to implement corresponding prevention and control measures to mitigate or eliminate risks.

[0063] A further improvement of the technical solution of the present invention is that the process of formulating and executing online sharing of emergency plans, emergency team and material management, and emergency drill plans is as follows:

[0064] Through daily inspections, regular inspections and special inspections, we collect information on potential safety hazards inside and outside the enterprise, and classify, screen and evaluate the collected information to build a potential safety hazard database;

[0065] Establish emergency electronic files based on the safety hazard database, including emergency team management, emergency plan management, emergency drill plan, and emergency drill material management.

[0066] A further improvement of the technical solution of the present invention is that: the process of integrating the intelligent hardware integration module with the intelligent helmet and the intelligent lock hardware device is as follows;

[0067] Determine the intelligent hardware devices that need to be integrated, and evaluate the communication protocols, data interfaces, and functional characteristics of the devices;

[0068] Connect the intelligent hardware integration module with the communication interface of the intelligent helmet and the communication interface of the intelligent lock to achieve remote control and status monitoring;

[0069] The integrated module is deployed to the actual scenario, and permission management is set according to actual needs to centrally control and manage smart helmets and smart locks.

[0070] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0071] 1. The present invention provides a new energy smart safety team system, which monitors the working status of team members, equipment operation status, environmental parameters and other key information in real time through the built-in safety monitoring and early warning mechanism of the system, promptly discovers abnormalities or potential risks, and automatically pushes relevant information to management personnel, thereby enhancing the safety management capabilities of the team, effectively preventing the occurrence of safety accidents, and ensuring the safety of personnel and property.

[0072] 2. The present invention provides a new energy intelligent safety team system, which realizes all-round and real-time monitoring of the work site by integrating high-tech equipment such as smart safety helmets and smart electronic locks, and realizes functions such as precise positioning of smart safety helmets, safety warnings, and hat-removal alarms, as well as emergency unlocking and illegal opening alarms of smart electronic locks, which reduces safety risks in the operation process, ensures the personal safety of team members, and significantly improves the safety production level of new energy sites.

[0073] 3. The present invention provides a new energy intelligent safety team system, which uniformly manages and dispatches team members. Team members can share work information, exchange work experience, and collaboratively solve problems in real time, thereby improving the efficiency of team collaborative work. At the same time, the system also provides a wealth of management tools and reporting functions to help managers easily grasp the team's work dynamics, discover and solve problems in a timely manner, and improve overall management efficiency.

[0074] 4. The present invention provides a new energy smart safety team system, which uses information and intelligent means to centrally monitor and intelligently manage team operations. The work site situation can be grasped in real time through a computer or mobile phone, and remote guidance and decision-making can be carried out, which not only reduces labor costs, but also improves management efficiency, making team management more efficient and convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0076] Figure 1 It is a module diagram of the present invention;

[0077] Figure 2 It is a flow chart of risk warning of the present invention;

[0078] Figure 3 A flowchart for obtaining the probability of occurrence of the safety risk of the present invention;

[0079] Figure 4 The figure is a flow chart for obtaining the risk assessment coefficient of the present invention. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] Embodiment 1, as Figure 1-4 As shown, the present invention provides a new energy smart safety team system, including a central control module, which is communicatively connected to a field operation management module, an education and training module, a risk pre-control module, a hidden danger investigation and emergency management module and an intelligent hardware integration module, wherein the modules are connected by electrical signals;

[0082] The field operation management module is used to provide operation guidance to team members through smart terminals such as tablets and smart phones, push safety risk information in the operation environment in real time, and perform task allocation, progress tracking and completion status feedback to achieve closed-loop management of tasks. At the same time, it manages the organization and coordination of third-party personnel related to the project, such as contractors and suppliers, as well as the application, approval, maintenance and scheduling of field tools and vehicles to ensure efficient use of resources. Among them, risk information, including environmental risks, equipment failure risks, human operation risks, etc., improves the risk awareness of operators;

[0083] Furthermore, the on-site operation management module includes a pre-shift and post-shift meeting unit, a task management unit, a tool management unit, a vehicle management unit, and a related party management unit, wherein each unit is connected by electrical signals;

[0084] The pre-shift and post-shift meeting unit is used to push the team's daily tasks, tasks assigned by superiors, and weekly and monthly work plans through smart terminals. At the same time, the team leader adjusts the plan according to the actual situation to form the team's daily work plan, and conducts online roll call and sign-in through smart terminals. At the same time, a safety check and confirmation of mental state and clothing is carried out. The task risks are automatically identified through intelligent algorithms and ranked by risk level. At the same time, audio and video recordings are made during the class meeting to ensure the traceability of the meeting content. The work tasks are pushed to the team members' smart terminals. Team members view the task details and risk warnings, and provide feedback on the task completion status through audio, photos, and text. The team leader can check the task feedback in real time through the terminal and provide a standardized work completion status template. The team members fill in and submit it according to the actual situation. When the team leader is in a meeting, the system automatically calls the content of the pre-shift meeting and compares it with the content filled in the post-shift meeting to display the work completion status and problems. The team leader comments on the team members' reports in the system and fills in relevant opinions. The system automatically generates a work log based on the content of the pre-shift meeting, post-shift meeting and the comments of the team leader, and saves it in the system for subsequent review and audit. The team leader scores the team members according to the completion quality and task volume of the work tasks, and counts the completed task volume and task scores on a monthly basis to provide a basis for performance appraisal;

[0085] The task management unit is used to assign work tasks according to the skills of team members, monitor the progress of task execution in real time, collect and display task completion status, and facilitate management to understand project progress;

[0086] Managers issue weekly and monthly work plans through the management platform to ensure that the team is aware of and ready to execute them in a timely manner. After receiving the plan, the team creates subtasks and accurately pushes these subtasks to specific operators to achieve refined task management. Operators perform tasks according to task requirements and feedback the completion status of tasks through the system to achieve real-time closed-loop management of work tasks. The system classifies and manages work tasks according to projects. Teams enter regular work tasks based on actual conditions and set reminders to ensure that tasks are completed on time. The system automatically records the completion status and related data of tasks to provide a basis for subsequent evaluation and improvement. For regular work tasks, the system automatically pushes relevant work risks and preventive measures to pre-shift meetings according to established cycles to provide early warnings and improve the safety awareness and response capabilities of the team.

[0087] The tool management unit is used to support team members to apply for the required tools online, automate the approval process, reduce waiting time, and record the maintenance history and current status of tools to arrange scheduling reasonably;

[0088] The whole life cycle management of the team's tools, including the whole process from storage, borrowing, maintenance, inspection to scrapping, records the detailed information of tools, forms a visual registration account, and is easy to query and track at any time. It generates records of key links such as borrowing, maintenance, and inspection, reduces manual operations, improves accuracy, and issues early warnings for inspections that are about to expire to ensure the safety and reliability of tools. At the same time, it uploads training materials on the use of dangerous tools to facilitate team members to learn at any time. By watching training videos or reading materials, team members can master the use methods, skills and precautions of tools, conduct sufficient learning and preparation before use, and reduce safety risks caused by improper use;

[0089] The vehicle management unit is used to reasonably arrange vehicle use according to operational needs, and record vehicle maintenance records and maintenance plans to ensure good vehicle performance. At the same time, it conducts real-time safety monitoring of vehicles to prevent traffic accidents;

[0090] Users can view the real-time status of project vehicles online through the system, including dispatch, repair, maintenance, idle and other statuses, to ensure the rational allocation and use of vehicle resources. Fill in the vehicle application form online through the mobile APP, and fill in the vehicle demand, expected use time, destination and other information in detail. The system will intelligently recommend the most suitable vehicle based on the reported vehicle application information and the real-time status of the vehicle, combined with the mileage of the month / week / day. After the initial review, the vehicle application will be pushed to the approver for approval. If it involves extreme weather conditions or nighttime use, the system will push the application to the superior person in charge for secondary approval after the approval is completed to ensure the safety and compliance of the vehicle. After approval, the system will push the application to the corresponding driver. After confirmation, the driver will perform the vehicle dispatch task. At the same time, the system will register the vehicle mileage, refueling information, etc. online to form a detailed vehicle ledger for subsequent management and auditing.

[0091] When vehicles are dispatched and used, the online application and approval process of vehicle demand is realized. After the application is submitted through the system, the relevant management personnel can approve it immediately to improve the approval efficiency. At the same time, it supports mobile approval. No matter where the management personnel are, they can check and process the vehicle application in time to ensure the smooth progress of the approval process. The driver needs to check the vehicle before driving to ensure that the vehicle is in good condition. At the same time, the system supports real-time monitoring and control of the vehicle dispatch process to ensure the safe driving of the vehicle. In the entire vehicle management process, all operations are recorded to form a complete management record. The system automatically generates a vehicle ledger, including vehicle application, approval, vehicle dispatch record, mileage, refueling information, etc., to provide strong support for vehicle management;

[0092] The stakeholder management unit is used to communicate with third parties, coordinate work progress and resource allocation, manage the contract information of stakeholders, ensure compliance, and promptly respond to and resolve issues arising from cooperation with third parties;

[0093] Require on-site personnel to upload skill certificates, training certificates, etc. to ensure that each on-site personnel has the corresponding professional capabilities and safety knowledge, and use the APP to edit and review information in real time, complete on-site registration, and automatically generate an account. At the same time, organize safety training and online examinations to form process data files. After the task is completed, the personnel apply for exit through the APP, and the account is closed and the information is recorded after review.

[0094] In addition, personnel automatically upload real-time positioning data through the APP, set up electronic fences in the system, define the scope of the work area and risk locations, and managers can view the positioning of individuals and teams in the electronic fences through the APP. When personnel approach the risk area, the system automatically issues an early warning notification. Multiple administrators can view the real-time positioning distribution of all personnel in the construction area through the system.

[0095] The education and training module is used to formulate training plans according to the needs of the team, including safety training, skills training, etc. It supports various training forms such as online learning and video tutorials, and manages team safety activities, such as safety meetings and emergency drills, to ensure that the activities are carried out in an orderly manner, record and archive safety activity materials for subsequent review and summary, and regularly conduct performance evaluations on teams and individuals, including work performance, safety performance and other dimensions, to provide a basis for rewards and punishments. The process of performance evaluation of teams and individuals is as follows: according to the company's development strategy, department needs and the development needs of individual employees, clarify the specific goals of the training, upload safety day activity learning materials for a specific time period, including documents, videos, PPT and other forms, and team members view the learning materials through smart terminals, and choose and reserve the time and place of the activity according to their own needs;

[0096] The risk pre-control module is used to accurately identify and evaluate safety risks in the operation process through data analysis and model prediction, and to issue early warnings for identified risks and provide corresponding prevention and control measures to ensure that risks are effectively controlled. At the same time, it is linked with the hidden danger investigation and emergency management modules to timely discover and report potential safety hazards and avoid the occurrence of safety accidents;

[0097] The hidden danger investigation and emergency management module is used to establish a hidden danger database, register, transfer and manage hidden dangers in a closed loop online to ensure that hidden dangers are rectified in a timely manner, and formulate and implement online sharing of emergency plans, emergency team and material management and emergency drill plans. When an emergency occurs, the emergency plan can be quickly responded to and implemented to reduce accident losses; the process of formulating and implementing online sharing of emergency plans, emergency team and material management and emergency drill plans is: through daily inspections, regular inspections and special inspections, collect safety hidden danger information inside and outside the enterprise, and classify, screen and evaluate the collected information to build a safety hidden danger database, and establish emergency electronic files based on the safety hidden danger database, including emergency team management, emergency plan management, emergency drill plan, and emergency drill material management;

[0098] Among them, emergency team management and emergency drill material management are to establish an emergency team and material information database in the system, including team members, contact information, material types, quantities, etc., and update the status information of emergency teams and materials in real time to ensure rapid response when emergencies occur;

[0099] Emergency plan management is to formulate detailed emergency plans, including emergency response process, rescue measures, resource allocation, etc. Employees can view and learn emergency plans through the system to improve emergency response capabilities. The system supports exporting and printing plans, which is convenient for employees to check at any time when needed;

[0100] Emergency drill plan: formulate an emergency drill plan, which includes drill objectives, content, time, location, participants and other elements, organize emergency drill activities according to the plan, and simulate emergency scenarios for actual combat drills. During the drill, record key information and problem points to provide a basis for subsequent summary and improvement;

[0101] The intelligent hardware integration module is used to integrate with the intelligent helmet and intelligent lock hardware devices to achieve data synchronization and intelligent control; the process of integrating the intelligent hardware integration module with the intelligent helmet and intelligent lock hardware devices is as follows;

[0102] Determine the intelligent hardware devices that need to be integrated, and evaluate the communication protocols, data interfaces, and functional characteristics of the devices;

[0103] Connect the intelligent hardware integration module with the communication interface of the intelligent helmet and the communication interface of the intelligent lock to achieve remote control and status monitoring;

[0104] The integrated module is deployed to the actual scenario, and permission management is set according to actual needs to centrally control and manage smart helmets and smart locks;

[0105] Furthermore, through the network camera, GPS / Beidou positioning, Bluetooth and other functions of the smart safety helmet, real-time monitoring, precise positioning and safety warning of the work site can be achieved. At the same time, it supports full-process safety management and control of pre-emptive prevention, in-process alarm and post-event backtracking, and realizes centralized monitoring management, emergency management, intelligent linkage and statistical analysis of smart locks and electronic keys, effectively preventing people from accidentally entering live intervals and preventing personal electric shock casualties.

[0106] Embodiment 2, as Figure 1-4 As shown, based on Example 1, the present invention provides a technical solution: Preferably, the process of early warning of the identified risks is:

[0107] Collecting work site data, including equipment operation data, environmental data, personnel operation records, historical accident data, and pre-processing the collected work site data; the process of collecting work site data is: collecting real-time operating parameters of equipment, such as temperature, pressure, vibration, etc., as well as equipment maintenance and fault records, using environmental monitoring equipment, such as temperature and humidity sensors, gas concentration sensors, etc., to collect environmental parameters of the work site, including weather conditions, noise levels, lighting conditions, air quality, etc., through video monitoring, RFID and manual records, tracking personnel location and operation behavior, including operation time, operation content, operator identity, etc., and storing them in the database, sorting and analyzing past accident cases, including accident causes, impact scope, treatment measures and results

[0108] Clean and integrate the collected equipment operation data, environmental data, personnel operation records, and historical accident data to form a unified data set;

[0109] Based on the preprocessed job site data, the abnormal risk factors associated with the job site data are extracted, wherein the abnormal risk factors include equipment failure factors, environmental abnormality factors and human operation error factors, and the historical accident data are analyzed and combined with the abnormal risk factors to build a risk prediction model, obtain the equipment failure index, environmental abnormality index and human operation error index, and predict the probability of occurrence and potential impact of safety risks; the process of predicting the probability of occurrence and potential impact of safety risks is: feature encoding the associated data in the equipment failure factor, environmental abnormality factor and human operation error factor, building a risk prediction model, and using the data set to train the risk prediction model, dividing the integrated data set into a training set, a validation set and a test set, using the training set data to train the risk prediction model, and using the validation set and test set data to verify the trained risk prediction model, evaluating the performance of the risk prediction model, using the trained model, combined with the preprocessed job site data, to obtain the equipment failure index, environmental abnormality index and human operation error index, and analyzing the correlation between equipment failure, environmental abnormality and human operation error;

[0110] Based on the acquired equipment failure index, environmental anomaly index and human operation error index, a risk assessment coefficient is obtained, and combined with historical accident data, different risk levels of safety risk situations are determined, and risk assessment thresholds are set for different risk levels; the process of setting risk assessment thresholds for different risk levels is: combining the equipment failure index, environmental anomaly index and human operation error index with historical accident data, analyzing the degree of correlation between safety risk and equipment failure factors, environmental anomaly factors and human operation error factors, and performing weighted calculations on the equipment failure index, environmental anomaly index and human operation error index to obtain a risk assessment coefficient, matching the safety risk situation in the historical accident data with the pre-processed work site data, and determining different risk levels, which are low risk level, medium risk level, high risk level and extremely high risk level, wherein the safety risk situation of the risk level increases step by step from low risk level to extremely high risk level, and the determined different risk levels are matched with the results of the risk assessment coefficient, and corresponding risk assessment thresholds are set for different risk levels;

[0111] Combine risk warning with hidden danger investigation, focus on investigating high-risk areas and links in warning, and promptly discover and report potential safety hazards;

[0112] Use the constructed risk prediction model to quantitatively evaluate the safety risks in the operation process, determine the risk level of the current safety risk, obtain the risk assessment results, and generate corresponding warning information according to the corresponding risk level, and formulate and implement corresponding prevention and control measures; the process of formulating and implementing corresponding prevention and control measures is: input the pre-processed characteristic data of equipment failure, environmental anomaly and personnel operation error into the risk prediction model, calculate the equipment failure index, environmental anomaly index and personnel operation error index respectively, combine the calculation results of the equipment failure index, environmental anomaly index and personnel operation error index, calculate the value of the risk assessment coefficient, and match the preset risk assessment threshold to determine the corresponding risk level, and prepare the corresponding warning information according to the determined risk level. The warning information should include the risk level, risk description, possible impact range and recommended preliminary response measures. At the same time, the warning information will be sent to relevant personnel in a timely manner, including on-site operators, safety management personnel and potentially affected departments or personnel, to implement corresponding prevention and control measures to mitigate or eliminate risks.

[0113] Embodiment 2, as Figure 1-4 As shown, based on Example 2, the present invention provides a technical solution: Preferably, the calculation formula of the equipment failure index is:

[0114]

[0115] Among them, FI is the equipment failure index, F c is the number of equipment failures, F r is the equipment failure rate, λ is the failure rate constant, and t is the actual value;

[0116] The calculation formula of the environmental anomaly index is:

[0117]

[0118] Among them, EI is the environmental anomaly index, E i is the actual measured value of the i-th environmental parameter, E s is the standard value of the environmental parameter, n is the number of environmental parameters, T is the current temperature, T s is the standard temperature, θ is the temperature sensitivity coefficient;

[0119] The calculation formula of the human operation error index is:

[0120]

[0121] Among them, HI is the human operation error index, N is the number of human operation errors in the past month, N is the total number of operations, and P r is the current operation error rate, P s is the standard operating error rate;

[0122] Furthermore, the calculation formula of the risk assessment coefficient is:

[0123]

[0124] Among them, RAI is the risk assessment coefficient, α is the weight coefficient, β is the attenuation factor, γ is the risk growth rate, δ is the standard deviation adjustment factor, FI is the equipment failure index, EI is the environmental abnormality index, and HI is the personnel operation error index;

[0125] Multiple risk levels correspond to multiple risk assessment thresholds that satisfy the following relationship:

[0126] Low risk level 0≤RAI <D A ;

[0127] Medium risk level D A ≤RAI <D B ;

[0128] High risk level D B ≤RAI <D C ;

[0129] Very high risk level D C ≤RAI≤1;

[0130] Among them, RAI is the risk assessment coefficient, D A is the upper threshold corresponding to the low risk level and the lower threshold corresponding to the medium risk level, D B is the upper threshold corresponding to the medium risk level and the lower threshold corresponding to the high risk level, D C is the upper threshold corresponding to the high risk level and the lower threshold corresponding to the extremely high risk level, D A =0.2, D B =0.5, D C =0.8.

[0131] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. New energy intelligent safety team system, including a central control module, characterized by: The central control module is communicatively connected to the field operation management module, the education and training module, the risk pre-control module, the hidden danger investigation and emergency management module and the intelligent hardware integration module, wherein the electrical signals between the modules are connected; The field operation management module is used to provide operation guidance to the team members through the intelligent terminal, push the safety risk information in the operation environment in real time, and perform task allocation, progress tracking and completion status feedback, and manage the organization and coordination of third-party personnel related to the project, as well as the application, approval, maintenance and scheduling of the use of field tools and vehicles; The education and training module is used to develop training plans based on team needs, manage team safety activities, record and archive safety activity data, and regularly conduct performance evaluations on teams and individuals; The risk pre-control module is used to accurately identify and evaluate safety risks in the operation process through data analysis and model prediction, and to issue early warnings for identified risks and provide corresponding prevention and control measures; The hidden danger investigation and emergency management module is used to establish a hidden danger database, register, transfer and manage hidden dangers online, and formulate and implement online sharing of emergency plans, emergency team and material management, and emergency drill plans; The intelligent hardware integration module is used to integrate with the intelligent helmet and intelligent lock hardware devices.

2. The new energy intelligent safety team system according to claim 1 is characterized by: The field operation management module includes a pre-shift and post-shift meeting unit, a task management unit, a tool management unit, a vehicle management unit, and a related party management unit, wherein each unit is connected by electrical signals; The pre-shift and post-shift meeting unit is used to push the team's daily tasks, tasks assigned by superior departments, and the team's weekly and monthly work plans through smart terminals; The task management unit is used to assign work tasks according to the skills of team members, monitor the progress of task execution in real time, and collect and display the task completion status; The tool management unit is used to support team members to apply for required tools online, automate the approval process, and record the maintenance history and current status of tools to arrange scheduling reasonably; The vehicle management unit is used to arrange vehicle use according to operational requirements, record vehicle maintenance records and maintenance plans, and perform real-time safety monitoring of vehicles to prevent traffic accidents; The related party management unit is used to communicate with the third party, coordinate the work progress and resource allocation, and manage the contract information of the related parties.

3. The new energy intelligent safety team system according to claim 2 is characterized by: The process of performance evaluation for teams and individuals is as follows: Clarify the specific objectives of training according to the company's development strategy, departmental needs and individual employee development needs; Upload learning materials for the safety day activities in a specific time period. Team members can view the learning materials through smart terminals and choose and reserve the activity time and location according to their own needs.

4. The new energy intelligent safety team system according to claim 1 or 3, characterized in that: The process of early warning of identified risks is as follows: Collecting work site data, including equipment operation data, environmental data, personnel operation records, historical accident data, and pre-processing the collected work site data; Clean and integrate the collected equipment operation data, environmental data, personnel operation records, and historical accident data to form a unified data set; Based on the pre-processed work site data, the abnormal risk factors associated with the work site data are extracted, where the abnormal risk factors include equipment failure factors, environmental abnormality factors and human operation error factors. The historical accident data is analyzed and combined with the abnormal risk factors to build a risk prediction model, obtain the equipment failure index, environmental abnormality index and human operation error index, and predict the probability of occurrence and potential impact of safety risks. Based on the acquired equipment failure index, environmental anomaly index and human operation error index, the risk assessment coefficient is obtained, and combined with historical accident data, different risk levels of safety risk situations are determined, and risk assessment thresholds are set for different risk levels; Combine risk warning with hidden danger investigation, focus on investigating high-risk areas and links in warning, and promptly discover and report potential safety hazards; Use the constructed risk prediction model to quantitatively assess the safety risks in the operation process, determine the risk level of the current safety risk, obtain the risk assessment results, generate corresponding early warning information according to the corresponding risk level, and formulate and implement corresponding prevention and control measures.

5. The new energy intelligent safety team system according to claim 4 is characterized by: The process of collecting work site data is as follows: Collect real-time operating parameters of equipment, as well as maintenance and fault records of equipment; Use environmental monitoring equipment to collect environmental parameters at the work site; Track personnel location and operation behavior, including operation time, operation content, operator identity, etc., through video surveillance, RFID and manual records, and store them in the database; Organize and analyze past accident cases, including the causes of the accidents, scope of impact, handling measures and results.

6. The new energy intelligent safety team system according to claim 5 is characterized by: The process of predicting the probability of occurrence and potential impact of security risks is as follows: Perform feature encoding on the associated data of equipment failure factors, environmental anomaly factors, and human operation error factors, build a risk prediction model, and use the data set to train the risk prediction model; The integrated data set is divided into a training set, a validation set, and a test set. The risk prediction model is trained using the training set data, and the trained risk prediction model is validated using the validation set and the test set data to evaluate the performance of the risk prediction model. Use the trained model and pre-processed job site data to obtain the equipment failure index, environmental anomaly index, and human operation error index, and analyze the correlation between equipment failure, environmental anomaly, and human operation error. The calculation formula of the equipment failure index is: Among them, FI is the equipment failure index, F c is the number of equipment failures, F r is the equipment failure rate, λ is the failure rate constant, and t is the actual value; The calculation formula of the environmental anomaly index is: Among them, EI is the environmental anomaly index, E i is the actual measured value of the i-th environmental parameter, E s is the standard value of the environmental parameter, n is the number of environmental parameters, T is the current temperature, T s is the standard temperature, θ is the temperature sensitivity coefficient; The calculation formula of the personnel operation error index is: Among them, HI is the human operation error index, N is the number of human operation errors in the past month, N is the total number of operations, and P r is the current operation error rate, P s is the standard operating error rate.

7. The new energy intelligent safety team system according to claim 6 is characterized by: The process of setting risk assessment thresholds for different risk levels is as follows: Combine the equipment failure index, environmental anomaly index, human operation error index and historical accident data to analyze the correlation between safety risks and equipment failure factors, environmental anomaly factors and human operation error factors; And perform weighted calculations on the equipment failure index, environmental anomaly index and human operation error index to obtain the risk assessment coefficient; According to the pre-processed work site data, the safety risk conditions in the historical accident data are matched to determine different risk levels, namely low risk level, medium risk level, high risk level and extremely high risk level, among which the safety risk conditions of the risk level increase step by step from low risk level to extremely high risk level; The determined different risk levels are matched with the results of the risk assessment coefficients, and corresponding risk assessment thresholds are set for different risk levels; The calculation formula of the risk assessment coefficient is: Among them, RAI is the risk assessment coefficient, α is the weight coefficient, β is the attenuation factor, γ is the risk growth rate, δ is the standard deviation adjustment factor, FI is the equipment failure index, EI is the environmental abnormality index, and HI is the personnel operation error index; The multiple risk levels correspond to the multiple risk assessment thresholds satisfying the following relationship: Low risk level 0≤RAI <D A ; Medium risk level D A ≤RAI <D B ; High risk level D B ≤RAI <D C ; Very high risk level D C ≤RAI≤1; Among them, RAI is the risk assessment coefficient, D A is the upper threshold corresponding to the low risk level and the lower threshold corresponding to the medium risk level, D B is the upper threshold corresponding to the medium risk level and the lower threshold corresponding to the high risk level, D C is the upper threshold corresponding to the high risk level and the lower threshold corresponding to the extremely high risk level, D A =0.2, D B =0.5, D C =0.

8.

8. The new energy intelligent safety team system according to claim 7 is characterized by: The process of formulating and implementing corresponding prevention and control measures is as follows: The pre-processed characteristic data of equipment failure, environmental anomaly and human operation error are input into the risk prediction model to calculate the equipment failure index, environmental anomaly index and human operation error index respectively; Combine the calculation results of equipment failure index, environmental abnormality index and human operation error index to calculate the value of risk assessment coefficient, match the preset risk assessment threshold and determine the corresponding risk level; According to the determined risk level, prepare corresponding early warning information, and send the early warning information to relevant personnel in a timely manner to implement corresponding prevention and control measures.

9. The new energy intelligent safety team system according to claim 8 is characterized by: The process of developing and implementing online sharing of emergency plans, emergency team and material management, and emergency drill plans is as follows: Through daily inspections, regular inspections and special inspections, we collect information on potential safety hazards inside and outside the enterprise, and classify, screen and evaluate the collected information to build a potential safety hazard database; Establish emergency electronic files based on the safety hazard database, including emergency team management, emergency plan management, emergency drill plan, and emergency drill material management.

10. The new energy intelligent safety team system according to claim 9 is characterized by: The process of integrating the intelligent hardware integration module with the intelligent helmet and intelligent lock hardware devices is as follows: Determine the intelligent hardware devices that need to be integrated, and evaluate the communication protocols, data interfaces, and functional characteristics of the devices; Connect the intelligent hardware integration module with the communication interface of the intelligent helmet and the communication interface of the intelligent lock to achieve remote control and status monitoring; The integrated module is deployed to the actual scenario, and permission management is set according to actual needs to centrally control and manage smart helmets and smart locks.

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