Digital twinborn visual monitoring and early warning system based on production management

Abstract

The invention relates to the technical field of safety production management, and discloses a digital twinborn visual monitoring and early warning system based on production management, which comprises a data acquisition module, a data processing module, a digital twinborn visual module, a safety monitoring and early warning module, an emergency management module and an application module, the data acquisition module acquires total factor data in the enterprise production process, and the digital twinborn visual monitoring and early warning system based on production management constructs an intelligent monitoring and early warning system covering production total factors through deep fusion of digital twinborn, big data, artificial intelligence and three-dimensional GIS technologies. According to the method, efficient integration and intelligent analysis of production data, full-process three-dimensional visual management and control, dynamic risk grading early warning and emergency disposal cooperative linkage are achieved, the intelligence and precision level of enterprise safety production is remarkably improved, the method can be widely applied to high-risk industries, the accident rate is effectively reduced, and remarkable economic benefits and social benefits are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of safe production management, and in particular to a digital twin visualization monitoring and early warning system based on production management. Background Art

[0002] In traditional production safety management, production safety is a crucial link. As enterprises expand in scale and production processes become more complex, it becomes difficult for enterprises to fully and real-time grasp all kinds of information in the production process. They also lack effective prediction and accurate decision-making methods for potential safety risks. With the development of digital technology, digital twin technology is gradually being applied to the field of production safety. At present, some digital twin-based monitoring and early warning systems on the market still have certain defects in data integration capabilities, visualization effects, and emergency response mechanisms. Data fragmentation makes it difficult to identify potential risks in advance through data correlation analysis; traditional production management relies on two-dimensional charts or scattered monitoring screens, which makes it difficult to intuitively present the dynamic correlation of the entire process and all elements of the factory. Managers cannot grasp the spatial distribution and evolution trends of production processes, equipment status and safety situations in real time through a unified interface, resulting in a lack of linkage support between spatial geographic information and production processes in emergency decision-making, and cannot fully meet the company's needs for full-factor management of safe production. Summary of the Invention

[0003] The purpose of the present invention is to provide a digital twin visualization monitoring and early warning system based on production management to solve the problems raised in the above background technology in terms of insufficient data integration capabilities, visualization effects and emergency response mechanisms of existing production safety management systems.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: a digital twin visualization monitoring and early warning system based on production management, comprising a data acquisition module, a data processing module, a digital twin visualization module, a safety monitoring and early warning module, an emergency management module, and an application module; The data acquisition module collects all-factor data in the enterprise's production process; The data processing module is used to clean, convert and fuse the collected data, integrate multi-source heterogeneous data into a unified format, establish a logical database, a business database, a real-time database and a cache database to classify and store management data, and ensure data integrity, consistency and availability; The digital twin visualization module uses 3D modeling technology to construct a digital twin model of the factory area, associates the processed data, and presents all elements of the entire process of the entire factory area in the form of visualization and virtual reality, realizing the centralized and unified management and control of the entire production operation process through 3D visualization. The safety situation, production process, equipment status and other information are displayed in real time on the monitoring screen and announcement screen. The safety monitoring and early warning module uses big data and artificial intelligence technology to build a comprehensive safety protection system for safety monitoring and early warning throughout the production process; The emergency management module is used to deeply integrate 3D GIS geographic maps and big data technology, integrate enterprise emergency management multi-source information and business data, and realize the integration of risk prevention and control, emergency rescue and early warning disposal; The application module is used by users to conduct information management of all factors of safe production through PC and mobile terminals.

[0005] The adoption of the above technical solutions facilitates the comprehensive and accurate collection and efficient processing of production data, provides reliable data support for subsequent management and decision-making, and lays the foundation for digital management.

[0006] As the preferred technical solution of the present invention, the data acquisition module includes collecting key safety parameters such as temperature, dust concentration, combustible gas concentration, power consumption, temperature and humidity of the electrical room through sensors; obtaining video images of the enterprise site through cameras; and tracking the location of personnel through positioning equipment.

[0007] The above technical solution makes it easier to obtain multi-type data covering key production safety indicators, on-site conditions and personnel dynamics, ensuring that no information is missed in each link of the production process, and providing rich and authentic data basis for production management and safety control.

[0008] As a preferred technical solution of the present invention, the data processing module adopts a filtering algorithm to remove abnormal values and noise interference in the data when cleaning the data.

[0009] The adoption of the above technical solutions can effectively improve data quality, make the data more realistically reflect the actual production situation, ensure the accuracy and reliability of data processing results, and avoid decision-making errors caused by interference from abnormal data.

[0010] As a preferred technical solution of the present invention, the safety monitoring and early warning module includes a safety situation comprehensive analysis module, a safety perception monitoring and early warning module, a dual prevention monitoring and early warning module and a fire simulation module; The security situation comprehensive analysis module is used to conduct a comprehensive analysis of the integrated data, using big data analysis and artificial intelligence algorithms to evaluate and predict the enterprise's security situation, and generate a security situation analysis report, allowing managers to intuitively understand the enterprise's security status and provide a basis for decision-making; The safety perception monitoring and early warning module is used for real-time monitoring and early warning of various scenarios; The dual prevention monitoring and early warning module is used to dynamically monitor risk changes in real time. Through comprehensive risk monitoring, regional hidden danger investigation and treatment monitoring, control measures monitoring and risk event monitoring, with risk as the core, it realizes the whole process management from risk identification to hidden danger investigation and treatment, and promptly finds out the possible deficiencies and loopholes in risk control, controls risks before hidden dangers form, and eliminates hidden dangers before accidents occur. The fire simulation module is used to set parameters such as flame type, temperature, direction, medium type, etc. for storage tanks and warehouse areas according to the hazardous chemicals media on site of the enterprise, and realize simulation calculation of fire burning speed, scope, loss, casualties and other data.

[0011] The adoption of the above technical solutions makes it easier to build a comprehensive, multi-level safety protection system, from macro-situation prediction to micro-scenario monitoring, from risk source control to accident simulation and deduction, to comprehensively improve the company's safety management level and reduce the possibility of accidents.

[0012] As a preferred technical solution of the present invention, the safety perception monitoring and early warning module includes a high-risk operation monitoring and early warning module, a fire monitoring and early warning module, a boiler pipeline monitoring and early warning module, an emergency facility monitoring and early warning module, a dust explosion monitoring and early warning module, a combustible gas monitoring and early warning module, an electricity monitoring and early warning module, and a violation monitoring and early warning module; The high-risk operation monitoring and early warning module is used to collect statistics on high-risk operation plans, areas, operation trends, operation classifications, operation units, etc., to achieve intelligent monitoring and early warning of high-risk operation processes; The fire monitoring and early warning module is used to monitor the enterprise's smoke sensors, fire water tanks, fire hydrant water pressure, fire detection and other fire data in real time, and to realize alarm tracking of events such as enterprise fire conditions, fire equipment failures, and expired fire special hidden danger treatment; The boiler pipeline monitoring and early warning module is used to achieve real-time online monitoring and early warning of enterprise boiler and pipeline safety risks by accessing enterprise pipeline and boiler pressure, temperature and other sensing equipment, and realize early warning and safety risk control measures, video monitoring, and AI intelligent analysis linkage disposal; The emergency facility monitoring and early warning module is used to collect and analyze key information such as emergency facility inspection, maintenance, and expiration, and to implement early warning tracking of maintenance, expiration, and other events; The dust explosion monitoring and early warning module is used to monitor the real-time concentration of dust explosion areas. Through the risk management and assessment model, combined with the real-time concentration monitoring sensor, it can dynamically sort and remind the regional dust explosion risk assessment in real time, and realize the alarm tracking of dust concentration, dust hazard control, equipment failure and other events; The combustible gas monitoring and early warning module is used to achieve real-time gas concentration monitoring in key combustible gas monitoring areas by connecting to the enterprise's GDS system (gas detection and alarm system). Through the risk management and assessment model, combined with the real-time concentration monitoring sensor, it can dynamically sort and remind the regional combustible gas explosion risk assessment in real time, and realize alarm tracking of combustible gas concentration, special hidden danger treatment, equipment failure and other events; The power consumption monitoring and early warning module is used to monitor key safety parameters such as enterprise power consumption, electrical room temperature and humidity in real time online, and to track and warn of events such as sensor and equipment failures and electrical hazards; The violation monitoring and early warning module is used to implement real-time online monitoring of the company's existing video surveillance. By adding an AI analysis engine, it can analyze the violation behaviors of personnel in key parts of the company in real time.

[0013] The adoption of the above technical solution facilitates all-round monitoring of key production scenarios. Once an abnormal situation occurs, the system immediately triggers the early warning mechanism. At the same time, through the linkage of multiple modules, it can achieve rapid positioning, analysis and disposal of safety hazards, and nip safety risks in the bud.

[0014] As a preferred technical solution of the present invention, the dual prevention monitoring and early warning module includes a safety risk classification control module and a hidden danger investigation and treatment module; The safety risk classification control module is used to build a full-process risk prevention and control system through digital modeling, standardized assessment, responsibility-based management and dynamic monitoring, and achieve accurate risk identification, hierarchical management and dynamic monitoring; The hidden danger investigation and control module is used to achieve full life cycle management of hidden dangers from discovery to elimination through multi-dimensional task generation, hierarchical warning tracking, full-process closed-loop management and intelligent analysis and evaluation, thereby improving the efficiency and management level of enterprise hidden danger control.

[0015] The adoption of the above technical solutions facilitates the establishment of a scientific and standardized risk and hidden danger management process, identifies potential risks in advance through risk classification and control, and uses hidden danger investigation and management to achieve closed-loop problem handling, forming a virtuous cycle of risk prevention and control and hidden danger management, and improving the safety management efficiency of the enterprise.

[0016] As a preferred technical solution of the present invention, the security risk hierarchical management and control module includes an analysis object management module, an analysis object hierarchical assessment module, a risk control measure management module and a dynamic risk change warning module; The analysis object management module is used to distinguish equipment and facility risk points and operational activity risks, conduct digital modeling, form a risk analysis object library, associate geographic coordinates, process parameters and other information, structure and itemize, and decompose layer by layer to facilitate user analysis and review of risk composition; The analysis object classification assessment module is used to automatically generate risk levels using built-in mainstream analysis methods such as job hazards (JHA), operating condition criticality (LEC), and safety checklist (SCL), and visually annotate them with different colors in the digital twin model; The risk control measures management module is used to formulate control measures for different risk levels, associate responsible departments and responsible persons, and automatically push task reminders through the system; The dynamic risk change warning module is used to collect equipment operation data, personnel behavior data, etc. in real time, and compare them with risk management standards. When a higher risk event occurs in the risk object, the system automatically sends a change warning.

[0017] The adoption of the above technical solutions facilitates the refined management of enterprise risks, enables clear presentation of risks through digital modeling, ensures that risks are always within a controllable range with the help of graded assessment and dynamic early warning, and implements management and control responsibilities through task push, thereby improving the execution of risk management.

[0018] As the preferred technical solution of the present invention, the hidden danger investigation and treatment module includes a multi-dimensional investigation module, a hierarchical early warning module, a closed-loop process management module, and an intelligent analysis and evaluation module; The multi-dimensional investigation module is used to support the formulation of hidden danger investigation plans, associate and analyze control measures, associate maintenance work orders, associate special operations, associate various changes, and automatically generate investigation tasks; The hierarchical warning module is used to timely track abnormal time such as overdue and timeout, and provide graded reminders according to the severity; The closed-loop process management module is used for hidden danger rectification, which requires uploading comparison photos before and after rectification and acceptance reports. After review, the closed-loop process is closed. Hidden dangers can be associated with special operation approvals and equipment maintenance work orders to avoid data silos. The intelligent analysis and evaluation module is used for the system to automatically generate multi-dimensional and multi-format analysis reports, analyzing from the dimensions of hidden danger types, frequent occurrence areas, and governance efficiency, to assist enterprises in optimizing safety management strategies.

[0019] The adoption of the above technical solutions facilitates the intelligent and process-based management of hidden danger investigation and control, and enables online operation of the entire process from task generation to rectification and acceptance, thereby reducing human intervention and improving the efficiency of hidden danger control. At the same time, through data analysis, management shortcomings can be discovered and safety management strategies can be optimized.

[0020] As a preferred technical solution of the present invention, the emergency management module includes an emergency sandbox module and a comprehensive early warning and disposal module; The emergency sandbox module uses 3D GIS geographic maps and big data technology to gather basic emergency management information such as enterprise risks, emergency resources, and emergency plans. It integrates enterprise geography, video surveillance, broadcasting, access control, large screens, hazardous chemical monitoring and early warning data, and achieves precise prevention and control of risks within the enterprise and the rapid formation of unified command, intelligent decision-making, and coordinated emergency rescue capabilities in the event of an accident. The comprehensive early warning and disposal module is used for unified management of all-factor early warnings, real-time tracking of early warning disposal efficiency, evaluation and analysis of early warning disposal conditions and effects, and ensures that early warning events are handled in a timely and effective manner through alarm location tracking and disposal process tracking.

[0021] The adoption of the above-mentioned technical solution facilitates the integration of corporate emergency resources and the construction of an efficient emergency response mechanism. When an accident occurs, resources can be quickly mobilized, rescue plans can be formulated, and multi-party collaborative operations can be achieved to minimize accident losses. At the same time, through the full tracking and evaluation of early warning and disposal, the emergency management process is continuously optimized.

[0022] Compared with the existing technology, the beneficial effects of the present invention are as follows: the digital twin visualization monitoring and early warning system based on production management builds an intelligent monitoring and early warning system covering all production factors through the deep integration of digital twin, big data, artificial intelligence and 3D GIS technology, realizes the efficient integration and intelligent analysis of production data, 3D visualization management and control of the entire process, dynamic risk classification and early warning and coordinated emergency response, significantly improves the intelligence and precision level of enterprise safety production, can be widely used in high-risk industries, effectively reduces the accident rate, and has significant economic and social benefits; 1. Through sensors, cameras, positioning equipment, etc., all-factor data such as production environment, equipment operation, and personnel behavior are collected, covering key safety parameters such as temperature, dust concentration, combustible gas concentration, as well as video images and personnel location information. This solves the data fragmentation problem in the traditional model and lays the foundation for precise management; 2. Use big data analysis and artificial intelligence algorithms to conduct multi-dimensional evaluation and prediction of the integrated data, generate visual security situation analysis reports, and help managers identify potential risks in advance, shifting from passive response to active prevention; 3. Build a digital twin model of the factory through 3D modeling technology, linking all aspects of the entire production process with processed data in real time, presenting it in the form of visualization and virtual reality, and achieving three-dimensional centralized control of the production process. Through large monitoring screens and announcement screens that dynamically display information such as safety status, production processes, and equipment status, managers can intuitively grasp the overall production status, shortening risk identification and decision-making time. The digital twin model integrates geographic coordinates and process parameters, supports spatial positioning of risk points and data drill-down analysis, and can quickly locate abnormal equipment and view associated parameters through the model to assist in accurate decision-making. 4. Through digital modeling, standardized assessment, responsible management and dynamic monitoring, accurate risk identification, hierarchical management and dynamic monitoring can be achieved, supporting multi-dimensional task generation, hierarchical and graded early warning, closed-loop process management and intelligent analysis and evaluation, thereby improving the efficiency and management level of hidden danger control. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0024] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0025] See also Figure 1, the technical solution of the present invention: a digital twin visualization monitoring and early warning system based on production management, including a data acquisition module, a data processing module, a digital twin visualization module, a safety monitoring and early warning module, an emergency management module and an application module. The data acquisition module collects all-factor data in the enterprise's production process. The data processing module is used to clean, convert and fuse the collected data, integrate multi-source heterogeneous data into a unified format, establish a logical database, a business database, a real-time database and a cache database to classify and store management data to ensure data integrity, consistency and availability. The logical database performs logical processing and analysis on the data to extract valuable information. The business database stores business data related to enterprise safety production management, such as basic safety information, personnel information, equipment files, etc. The real-time database is used to store real-time collected data so that the system can obtain the latest production information in real time. The cache database is used to cache commonly used data to improve the system. The system's response speed is improved. At the same time, the data layer also has data encryption and interface access authentication functions to ensure the security and legality of the data. The digital twin visualization module uses 3D modeling technology to build a digital twin model of the factory area, associates the processed data, and presents all elements of the entire process of the entire factory area in the form of visualization and virtual reality, realizing centralized and unified 3D visualization of the entire production operation process. Through the monitoring screen and the announcement screen, the safety situation, production process, equipment status and other information are displayed in real time. The safety monitoring and early warning module comprehensively uses big data and artificial intelligence technology to build a comprehensive safety protection system for safety monitoring and early warning throughout the production process. The emergency management module is used to deeply integrate 3D GIS geographic maps and big data technology, integrate enterprise emergency management multi-source information and business data, and realize the integration of risk prevention and control, emergency rescue and early warning disposal. The application module is used for users to conduct information management of all elements of production safety through PC and mobile terminals.

[0026] The data acquisition module includes collecting key safety parameters such as temperature, dust concentration, combustible gas concentration, power consumption, temperature and humidity of the electrical room through sensors; obtaining video images of the enterprise site through cameras; and tracking the location of personnel through positioning equipment.

[0027] When cleaning data in the data processing module, filtering algorithms are used to remove outliers and noise interference in the data.

[0028] The safety monitoring and early warning module includes a comprehensive safety situation analysis module, a safety perception monitoring and early warning module, a dual prevention monitoring and early warning module, and a fire simulation module. The comprehensive safety situation analysis module is used to conduct a comprehensive analysis of the integrated data, use big data analysis and artificial intelligence algorithms to evaluate and predict the company's safety situation, and generate a safety situation analysis report, so that managers can intuitively understand the company's safety status and provide a basis for decision-making for managers. The safety perception monitoring and early warning module is used for real-time monitoring and early warning of various scenarios. The dual prevention monitoring and early warning module is used for dynamic risk monitoring of real-time risk changes. Through comprehensive risk monitoring, regional hidden danger investigation and governance monitoring, control measures monitoring, and risk event monitoring, with risk as the core, the whole process management from risk identification to hidden danger investigation and governance is realized, and possible deficiencies and loopholes in risk control are promptly identified, risks are controlled before hidden dangers form, and hidden dangers are eliminated before accidents occur. The fire simulation module is used for storage tanks and warehouse areas. According to the hazardous chemical media on site of the enterprise, parameters such as flame type, temperature, direction, medium type, etc. are set to simulate and calculate data such as fire burning speed, range, loss, and casualties.

[0029] The safety perception monitoring and early warning module includes a high-risk operation monitoring and early warning module, a fire monitoring and early warning module, a boiler pipeline monitoring and early warning module, an emergency facility monitoring and early warning module, a dust explosion monitoring and early warning module, a combustible gas monitoring and early warning module, an electricity monitoring and early warning module, and a violation monitoring and early warning module. The high-risk operation monitoring and early warning module is used to summarize information such as high-risk operation plans, areas, operation trends, operation classifications, and operation units, to achieve intelligent monitoring and early warning of high-risk operation processes, including capturing violations (smoking, open flames, not wearing safety helmets, etc.), expired certificates, fires, combustible gases, etc., to achieve real-time video monitoring of high-risk operations and real-time gas analysis. The fire monitoring and early warning module is used to monitor the fire data of the enterprise such as smoke detection, fire water pool, fire hydrant water pressure, fire detection in real time, and realize the alarm tracking of the enterprise fire situation, fire equipment failure, fire special hidden danger treatment expiration and other events. The boiler pipeline monitoring and early warning module is used to realize the real-time online monitoring and early warning of the enterprise boiler and pipeline safety risks by accessing the enterprise pipeline and boiler pressure, temperature and other sensing equipment, and realize the linkage disposal of early warning and safety risk management measures, video monitoring, and AI intelligent analysis. The emergency facility monitoring and early warning module is used to summarize and analyze the key information such as emergency facility inspection and maintenance, expiration, etc., and realize the early warning and early warning of maintenance, expiration and other events. The dust explosion monitoring and early warning module is used to monitor the real-time concentration of dust explosion areas. Through the risk management and evaluation model, combined with the real-time concentration monitoring sensor, the regional dust explosion risk assessment calculation is dynamically sorted and reminded in real time, and the alarm tracking of dust concentration, dust hidden danger control, equipment failure and other events is realized. The combustible gas monitoring and early warning module is used to realize the real-time gas concentration monitoring of the key monitoring area of combustible gas by accessing the enterprise GDS system (gas detection alarm system). Through the risk management and evaluation model, combined with the real-time concentration monitoring sensor, the regional combustible gas explosion risk assessment calculation is dynamically sorted and reminded in real time, and the combustible gas is realized. Concentration, special hidden danger treatment, equipment failure and other event alarm tracking, electricity monitoring and early warning module is used for real-time online monitoring of key safety parameters such as enterprise electricity consumption, electrical room temperature, humidity, and realizes event tracking and early warning of sensors, equipment failure, electrical hidden dangers, etc., and violation monitoring and early warning module is used to realize real-time online monitoring of enterprise video for the existing video surveillance of the enterprise. By adding AI analysis engine, real-time analysis of personnel violation behaviors in key parts of the enterprise can be realized, including regional intrusion, smoking, making phone calls, smoke, flame, safety clothing, personnel leaving the post, work clothes, not wearing masks, static electricity release, cellar netting, not wearing helmets and other behaviors.

[0030] The dual prevention monitoring and early warning module includes a safety risk classification control module and a hidden danger investigation and governance module. The safety risk classification control module is used to build a full-process risk prevention and control system through digital modeling, standardized assessment, responsibility management and dynamic monitoring, and realize accurate risk identification, hierarchical management and dynamic monitoring. The hidden danger investigation and governance module is used to realize the full life cycle control of hidden dangers from discovery to elimination through multi-dimensional task generation, hierarchical early warning tracking, full-process closed-loop management and intelligent analysis and evaluation, thereby improving the efficiency and management level of enterprise hidden danger governance.

[0031] The safety risk classification and control module includes an analysis object management module, an analysis object classification assessment module, a risk control measures management module, and a dynamic risk change warning module. The analysis object management module is used to distinguish between equipment and facility risk points and operational activity risks, perform digital modeling, form a risk analysis object library, associate geographic coordinates, process parameters and other information, and structure and itemize them. The layered decomposition facilitates user analysis and review of risk composition. The analysis object classification assessment module is used to automatically generate risk levels through built-in mainstream analysis methods such as job hazards (JHA), operating condition hazards (LEC), and safety checklists (SCL), and visually mark them with different colors in the digital twin model. The risk control measures management module is used to formulate control measures for different risk levels, associate responsible departments and persons, and automatically push task reminders through the system. The dynamic risk change warning module is used to collect equipment operation data, personnel behavior data, etc. in real time, and compare them with risk control standards. When a higher risk event occurs in a risk object, the system automatically sends a change warning.

[0032] The hidden danger investigation and control module includes a multi-dimensional investigation module, a hierarchical early warning module, a closed-loop process management module, and an intelligent analysis and evaluation module. The multi-dimensional investigation module is used to support the formulation of hidden danger investigation plans, associate analysis control measures, associate maintenance work orders, associate special operations, associate various changes, and automatically generate investigation tasks. The hierarchical early warning module is used to timely warn and track abnormal time such as overdue and timeout management, and provide graded reminders based on severity. The closed-loop process management module is used in the hidden danger rectification process to upload comparison photos and acceptance reports before and after rectification, and the closed-loop is cancelled after review. Hidden dangers can be associated with special operation approvals and equipment maintenance work orders to avoid data silos. The intelligent analysis and evaluation module is used for the system to automatically generate multi-dimensional and multi-form analysis reports, analyze from dimensions such as hidden danger types, frequent occurrence areas, and governance efficiency, and assist enterprises in optimizing safety management strategies.

[0033] The emergency management module includes an emergency sandbox module and a comprehensive early warning and disposal module. The emergency sandbox module uses three-dimensional GIS geographic maps and big data technology to gather basic emergency management information such as enterprise risks, emergency resources, and emergency plans, and integrate enterprise geography, video surveillance, broadcasting, access control, large screens, hazardous chemical monitoring and early warning data to achieve accurate prevention and control of risks within the enterprise and quickly form unified command, intelligent decision-making, and coordinated emergency rescue capabilities under accident conditions. The comprehensive early warning and disposal module is used for unified management of all-factor early warnings, real-time tracking of early warning disposal efficiency, evaluation and analysis of early warning disposal situations and effects, and ensures that early warning events are handled in a timely and effective manner through alarm location tracking and disposal process tracking.

[0034] The contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0035] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A digital twin visualization monitoring and early warning system based on production management, including a data acquisition module, a data processing module, a digital twin visualization module, a safety monitoring and early warning module, an emergency management module, and an application module, characterized by: The data acquisition module collects all-factor data in the enterprise's production process; The data processing module is used to clean, convert and fuse the collected data, integrate multi-source heterogeneous data into a unified format, establish a logical database, a business database, a real-time database and a cache database to classify and store management data, and ensure data integrity, consistency and availability; The digital twin visualization module uses 3D modeling technology to construct a digital twin model of the factory area, associates the processed data, and presents all elements of the entire process of the entire factory area in the form of visualization and virtual reality, realizing the centralized and unified management and control of the entire production operation process through 3D visualization. The safety situation, production process, equipment status and other information are displayed in real time on the monitoring screen and announcement screen. The safety monitoring and early warning module uses big data and artificial intelligence technology to build a comprehensive safety protection system for safety monitoring and early warning throughout the production process; The emergency management module is used to deeply integrate 3D GIS geographic maps and big data technology, integrate enterprise emergency management multi-source information and business data, and realize the integration of risk prevention and control, emergency rescue and early warning disposal; The application module is used by users to conduct information management of all factors of safe production through PC and mobile terminals.

2. A digital twin visualization monitoring and early warning system based on production management according to claim 1, characterized in that: The data acquisition module includes collecting key safety parameters such as temperature, dust concentration, combustible gas concentration, power consumption, temperature and humidity of the electrical room through sensors; obtaining video images of the enterprise site through cameras; and tracking the location of personnel through positioning equipment.

3. A digital twin visualization monitoring and early warning system based on production management according to claim 1, characterized in that: When cleaning the data in the data processing module, a filtering algorithm is used to remove abnormal values and noise interference in the data.

4. A digital twin visualization monitoring and early warning system based on production management according to claim 1, characterized in that: The safety monitoring and early warning module includes a safety situation comprehensive analysis module, a safety perception monitoring and early warning module, a dual prevention monitoring and early warning module and a fire simulation module; The security situation comprehensive analysis module is used to conduct a comprehensive analysis of the integrated data, using big data analysis and artificial intelligence algorithms to evaluate and predict the enterprise's security situation, and generate a security situation analysis report, allowing managers to intuitively understand the enterprise's security status and provide a basis for decision-making; The safety perception monitoring and early warning module is used for real-time monitoring and early warning of various scenarios; The dual prevention monitoring and early warning module is used to dynamically monitor risk changes in real time. Through comprehensive risk monitoring, regional hidden danger investigation and treatment monitoring, control measures monitoring and risk event monitoring, with risk as the core, it realizes the whole process management from risk identification to hidden danger investigation and treatment, and promptly finds out the possible deficiencies and loopholes in risk control, controls risks before hidden dangers form, and eliminates hidden dangers before accidents occur. The fire simulation module is used to set parameters such as flame type, temperature, direction, medium type, etc. for storage tanks and warehouse areas according to the hazardous chemicals media on site of the enterprise, and realize simulation calculation of fire burning speed, scope, loss, casualties and other data.

5. A digital twin visualization monitoring and early warning system based on production management according to claim 4, characterized in that: The safety perception monitoring and early warning module includes a high-risk operation monitoring and early warning module, a fire monitoring and early warning module, a boiler pipeline monitoring and early warning module, an emergency facility monitoring and early warning module, a dust explosion monitoring and early warning module, a combustible gas monitoring and early warning module, an electricity consumption monitoring and early warning module, and a violation monitoring and early warning module; The high-risk operation monitoring and early warning module is used to collect statistics on high-risk operation plans, areas, operation trends, operation classifications, operation units, etc., to achieve intelligent monitoring and early warning of high-risk operation processes; The fire monitoring and early warning module is used to monitor the enterprise's smoke sensors, fire water tanks, fire hydrant water pressure, fire detection and other fire data in real time, and to realize alarm tracking of events such as enterprise fire conditions, fire equipment failures, and expired fire special hidden danger treatment; The boiler pipeline monitoring and early warning module is used to achieve real-time online monitoring and early warning of enterprise boiler and pipeline safety risks by accessing enterprise pipeline and boiler pressure, temperature and other sensing equipment, and realize early warning and safety risk control measures, video monitoring, and AI intelligent analysis linkage disposal; The emergency facility monitoring and early warning module is used to collect and analyze key information such as emergency facility inspection, maintenance, and expiration, and to implement early warning tracking of maintenance, expiration, and other events; The dust explosion monitoring and early warning module is used to monitor the real-time concentration of dust explosion areas. Through the risk management and assessment model, combined with the real-time concentration monitoring sensor, it can dynamically sort and remind the regional dust explosion risk assessment in real time, and realize the alarm tracking of dust concentration, dust hazard control, equipment failure and other events; The combustible gas monitoring and early warning module is used to achieve real-time gas concentration monitoring in key combustible gas monitoring areas by connecting to the enterprise's GDS system (gas detection and alarm system). Through the risk management and assessment model, combined with the real-time concentration monitoring sensor, it can dynamically sort and remind the regional combustible gas explosion risk assessment in real time, and realize alarm tracking of combustible gas concentration, special hidden danger treatment, equipment failure and other events; The power consumption monitoring and early warning module is used to monitor key safety parameters such as enterprise power consumption, electrical room temperature and humidity in real time online, and to track and warn of events such as sensor and equipment failures and electrical hazards; The violation monitoring and early warning module is used to implement real-time online monitoring of the company's existing video surveillance. By adding an AI analysis engine, it can analyze the violation behaviors of personnel in key parts of the company in real time.

6. A digital twin visualization monitoring and early warning system based on production management according to claim 4, characterized in that: The dual prevention monitoring and early warning module includes a safety risk classification control module and a hidden danger investigation and treatment module; The safety risk classification control module is used to build a full-process risk prevention and control system through digital modeling, standardized assessment, responsibility-based management and dynamic monitoring, and achieve accurate risk identification, hierarchical management and dynamic monitoring; The hidden danger investigation and control module is used to achieve full life cycle management of hidden dangers from discovery to elimination through multi-dimensional task generation, hierarchical warning tracking, full-process closed-loop management and intelligent analysis and evaluation, thereby improving the efficiency and management level of enterprise hidden danger control.

7. A digital twin visualization monitoring and early warning system based on production management according to claim 6, characterized in that: The security risk classification management and control module includes an analysis object management module, an analysis object classification assessment module, a risk control measure management module and a dynamic risk change warning module; The analysis object management module is used to distinguish equipment and facility risk points and operational activity risks, conduct digital modeling, form a risk analysis object library, associate geographic coordinates, process parameters and other information, structure and itemize, and decompose layer by layer to facilitate user analysis and review of risk composition; The analysis object classification assessment module is used to automatically generate risk levels using built-in mainstream analysis methods such as job hazards (JHA), operating condition criticality (LEC), and safety checklist (SCL), and visually annotate them with different colors in the digital twin model; The risk control measures management module is used to formulate control measures for different risk levels, associate responsible departments and responsible persons, and automatically push task reminders through the system; The dynamic risk change warning module is used to collect equipment operation data, personnel behavior data, etc. in real time, and compare them with risk management standards. When a higher risk event occurs in the risk object, the system automatically sends a change warning.

8. The digital twin visualization monitoring and early warning system based on production management according to claim 6 is characterized in that: The hidden danger investigation and treatment module includes a multi-dimensional investigation module, a hierarchical early warning module, a closed-loop process management module, and an intelligent analysis and evaluation module; The multi-dimensional investigation module is used to support the formulation of hidden danger investigation plans, associate and analyze control measures, associate maintenance work orders, associate special operations, associate various changes, and automatically generate investigation tasks; The hierarchical warning module is used to timely track abnormal time such as overdue and timeout, and provide graded reminders according to the severity; The closed-loop process management module is used for hidden danger rectification, which requires uploading comparison photos before and after rectification and acceptance reports. After review, the closed-loop process is closed. Hidden dangers can be associated with special operation approvals and equipment maintenance work orders to avoid data silos. The intelligent analysis and evaluation module is used for the system to automatically generate multi-dimensional and multi-format analysis reports, analyzing from the dimensions of hidden danger types, frequent occurrence areas, and governance efficiency, to assist enterprises in optimizing safety management strategies.

9. The digital twin visualization monitoring and early warning system based on production management according to claim 1 is characterized in that: The emergency management module includes an emergency sandbox module and a comprehensive early warning and disposal module; The emergency sandbox module uses 3D GIS geographic maps and big data technology to gather basic emergency management information such as enterprise risks, emergency resources, and emergency plans. It integrates enterprise geography, video surveillance, broadcasting, access control, large screens, hazardous chemical monitoring and early warning data, and achieves precise prevention and control of risks within the enterprise and the rapid formation of unified command, intelligent decision-making, and coordinated emergency rescue capabilities in the event of an accident. The comprehensive early warning and disposal module is used for unified management of all-factor early warnings, real-time tracking of early warning disposal efficiency, evaluation and analysis of early warning disposal conditions and effects, and ensures that early warning events are handled in a timely and effective manner through alarm location tracking and disposal process tracking.

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