Thermal power plant ash conveying process digital twinning

Abstract

The invention relates to the field of digital twinning and industrial automation, and aims to construct a'three-dimensional modeling-real-time data acquisition-analogue simulation-visual display-intelligent analysis' full-process system aiming at the problems that the traditional ash conveying system equipment is difficult to monitor, data is split, no visual graph exists in monitoring, and exception handling and maintenance are passive. The modular design of the system comprises three-dimensional modeling (high-precision 3D + PBR rendering), data acquisition (sensor real-time transmission), a digital twin engine (Unity to realize virtual-real synchronization), simulation visualization (physical simulation + particle effect), intelligent analysis (big data + machine learning, fault prediction and parameter optimization) and user interaction (multi-terminal access). Three-dimensional visualization and data linkage of the equipment are realized, and the equipment has the characteristics of fault early warning, improvement of ash conveying efficiency, multi-terminal convenient operation and the like. The traditional bottleneck is broken through, a path is provided for intelligent ash conveying, and the economic and environment-friendly benefits of improving efficiency, reducing energy consumption and guaranteeing equipment safety are achieved.

Description

I. TECHNICAL FIELD

[0001] The present application relates to the field of digital twin technology and industrial automation control, specifically a visualization and intelligent management system for the ash conveying process in a thermal power plant based on digital twin technology. The system aims to achieve comprehensive monitoring and optimization of the ash conveying process in a thermal power plant through three-dimensional modeling, real-time data acquisition, simulation, and visual display, thereby improving production efficiency, reducing energy consumption, and ensuring safe operation of equipment. In the context of the development of the thermal power industry towards intelligence, greenness, and low carbonization, digital twin technology, as an important component of new-generation information technology, is gradually applied to various aspects of industrial production to achieve real-time mapping and dynamic simulation of complex systems, thereby providing scientific basis for production management, equipment maintenance, and process optimization. Digital twin technology not only enables real-time mapping of physical systems, but also predicts and optimizes system operation through data-driven methods, providing strong support for the intelligent transformation of thermal power plants. II. BACKGROUND

[0002] The thermal power industry, as an important part of China's energy structure, involves a large number of complex equipment and systems in its production process, among which the ash conveying system is a key link in the operation of the boiler. The ash conveying system mainly includes equipment such as ash hoppers, pump rooms, pipelines, and air compressors, and its operation status directly affects the combustion efficiency and environmental emission level of the boiler. However, with the continuous expansion of the scale of thermal power plants and the continuous increase in the number of equipment, the traditional management method of the ash conveying system has been difficult to meet the needs of modern production. Currently, there are still many problems in the monitoring and management of the ash conveying process in thermal power plants, mainly in the following aspects:

[0003] In actual operation, the equipment status of the ash conveying system is often difficult to be discovered in a timely manner. The traditional ash conveying system in thermal power plants is mostly monitored by manual inspection, which is not only inefficient, but also prone to missed detection or misjudgment due to human factors, affecting the stability of equipment operation. In a high-load operation state, the ash conveying system is under great pressure, and once a fault occurs, it often takes a long time to locate and handle, resulting in production interruption and economic loss.

[0004] The ash conveying system involves multiple subsystems, such as boilers, dust removal, ash conveying, and air compression, and the data between systems is fragmented, making it difficult to form a unified data platform. This data island phenomenon limits the improvement of overall operation efficiency and makes it difficult for management personnel to comprehensively analyze and decide on the system operation status from a global perspective. In addition, the non-standardization of data acquisition and transmission also increases the risk of system operation and affects the stability and reliability of the system. In actual operation, management personnel often need to switch between multiple system interfaces to obtain complete equipment operation information, which not only increases the operation difficulty, but also reduces the work efficiency.

[0005] The monitoring method of the traditional ash conveying system is mostly in the form of text or table, which lacks intuitive graphical display and is not conducive to the quick grasp of the running state of the equipment by the management personnel. In actual operation, the management personnel often need to switch through multiple system interfaces to obtain complete equipment running information, which not only increases the operation difficulty, but also reduces the work efficiency. At the same time, the lack of three-dimensional visual display of the ash conveying process makes it difficult to intuitively present the dynamic changes of the equipment running state, affecting the real-time judgment and decision-making of the system running state.

[0006] The ash conveying system involves multiple key equipment such as ash hoppers, bin pumps, and pipelines. Once the equipment is abnormal, it often takes a long time to discover and handle. The traditional maintenance method is mostly post-maintenance, which lacks dynamic analysis of the running state of the equipment and cannot provide early warning of potential faults. This passive maintenance method not only increases the failure rate of the equipment, but also leads to high maintenance cost and production loss. Especially under high load running state, the running pressure of the ash conveying system is large, and once a fault occurs, it will often lead to the shutdown of the entire boiler system, affecting the power generation efficiency and environmental protection indicators.

[0007] Due to the lack of comprehensive understanding of the running state of the equipment, the maintenance work is passive, which increases the maintenance cost. The traditional maintenance method is mostly post-maintenance, which lacks predictive maintenance of the running state of the equipment, leading to aggravated equipment wear and tear and high maintenance cost. At the same time, the maintenance personnel often need to make judgments based on experience, which lacks scientific basis, making the maintenance work lack systematicness and standardization, affecting the overall maintenance efficiency and quality.

[0008] To solve the above problems, a digital twin system capable of realizing comprehensive monitoring, real-time visualization, intelligent analysis and optimization of the ash conveying process of a thermal power plant is urgently needed. In the prior art, although some thermal power plants have introduced three-dimensional modeling, Internet of Things, big data and other technologies, most of them are limited to the monitoring of single equipment or local scene, and have not formed a digital twin system covering the entire ash conveying process. Therefore, it is of great practical significance and application value to develop a digital twin system for the ash conveying process of a thermal power plant based on digital twin technology. III. SUMMARY

[0009] The present application provides a digital twin system for the ash conveying process of a thermal power plant, which realizes comprehensive monitoring and optimization of the ash conveying process by constructing a three-dimensional digital model of the ash conveying system and integrating real-time data acquisition, simulation, visualization and intelligent analysis functions. The system mainly includes the following core components, which together constitute a highly integrated and intelligent industrial management system.

[0010] In system design, three-dimensional modeling is the foundation of realizing digital twinning. Based on high-precision 3D modeling technology, this module constructs a three-dimensional model of the ash conveying system in thermal power plants, covering the structure and layout of key equipment such as ash hoppers, warehouse pumps, pipelines, and air compressors. During modeling, the scale, material, and lighting effects of the model must be consistent with the actual equipment to ensure that the digital twin is highly consistent with the real equipment in terms of vision. In addition, the model supports the import of multiple data formats, such as FBX, OBJ, GLT, and other common Mesh data formats, to improve the system's compatibility and scalability. Through PBR (Physical-Based Rendering) technology, the model can accurately simulate the light flow in the real world, achieving high-fidelity rendering effects, making the digital twin highly consistent with the actual equipment in terms of lighting, reflection, and material. This modeling approach not only enhances the system's visualization, but also provides high-quality three-dimensional foundations for subsequent simulation and analysis.

[0011] In data acquisition and transmission, the system installs sensors on key equipment in the ash conveying system to collect real-time data such as temperature, pressure, flow, and equipment status, and transmits them to the digital twinning platform through industrial Ethernet or wireless communication. The data acquisition module must have high precision and stability to ensure real-time and accuracy of data. To address the problem of large data volume and frequent transmission, the system uses network protocols such as Socket communication or UnityWebRequest, combined with Retrofit library and UniRx framework, to realize asynchronous data request and processing, ensuring the efficiency and stability of data transmission. In addition, the system also designs a dynamic Retrofit configuration method to support different platform data interfaces, realizing API serialization and deserialization, and improving the flexibility and maintainability of the system. Through this module, the system can obtain the running state of the ash conveying system in real time, providing reliable data support for subsequent simulation and analysis.

[0012] The digital twinning engine is the core of the system to realize real-time synchronization between the physical system and the virtual model. This module uses three-dimensional rendering technologies such as Unity Engine or WebGL to build a three-dimensional digital model of the ash conveying system and synchronize it with the physical system in real time. The digital twinning engine must have good rendering performance to ensure smooth operation on different devices. The system achieves high-fidelity rendering effects through light source and global lighting settings, realistically simulating the device working environment and balancing performance overhead. In addition, the system also supports model animation control systems, which read working state data to control the animation playback state of pre-defined action information, realizing dynamic display of equipment running state. This module not only improves the system's visualization, but also provides dynamic three-dimensional model support for subsequent simulation and analysis.

[0013] In terms of simulation and visualization, the system is based on a physical simulation engine, simulating the running state of the ash conveying system, including the changes in ash quantity, flue gas flow, compressed air ash blowing, etc., and displaying the device running state through a visual interface. The visualization module supports the import and display of multiple data formats, ensuring that users can intuitively understand the device running situation. In addition, the system also supports particle special effects, simulating the movement of gas and ash, including the changes in flue gas concentration, ash falling and compressed air ash blowing effects in the boiler, electric ash removal and bag ash removal, improving the visualization effect and interactive experience of the system. Through this module, users not only can see the running state of the device, but also can intuitively feel the complexity and dynamic changes of the ash conveying process through dynamic particle effects, thus improving the intuitiveness and operability of the system.

[0014] The intelligent analysis and decision-making module is the key part of the system to realize the running state prediction and optimization of the ash conveying system. This module uses big data analysis, machine learning and other technologies to analyze the collected data, predict equipment failures, optimize running parameters, and provide decision support. The intelligent analysis module needs to have good algorithm models to ensure the accuracy and reliability of the prediction. In addition, the system also supports multi-threaded data processing, combined with Linq extension operators to simplify the development process and improve the maintainability and scalability of the system. Through intelligent analysis, the system can early warning potential failures, optimize equipment running parameters, and improve the running efficiency and stability of the ash conveying system. This module not only improves the intelligent level of the system, but also provides scientific decision-making basis for management personnel.

[0015] The user interaction and control module is an important part of the system to realize user operation and system control. This module provides Web, mobile and other multi-terminal access methods, supporting real-time monitoring, operation control and fault alarm of the ash conveying system by users. The user interaction module needs to have good user experience to ensure that users can easily operate and query. In addition, the system also supports modular design, prefabricating data lists, column charts, line charts, pie charts, scatter charts and other charts, and linking data with models and virtual buttons in the scene to realize dynamic display and interaction of data. Through this module, users not only can view the running state of the device, but also can intuitively understand the running situation of the ash conveying system through the linkage of charts and models, improving the operation efficiency and user satisfaction of the system.

[0016] The beneficial effects of the present application are reflected in multiple aspects. First, the system can improve the operation efficiency of the ash conveying system. Through real-time monitoring and intelligent analysis, the system optimizes the equipment operation parameters and improves the ash conveying efficiency. The system can reflect the equipment operation state in real time, ensure the stability of the ash conveying system under high load operation state, and reduce the production interruption caused by equipment failure. Second, the system can reduce maintenance cost. Through predictive maintenance, the system reduces unplanned downtime and reduces maintenance cost. The system can early warning potential failure, avoid equipment downtime due to sudden failure, and reduce maintenance cost and downtime loss. In addition, the system can enhance safety. Through real-time monitoring and early warning mechanism, the system improves the safety of equipment operation. The system can monitor the equipment operation state in real time, find abnormal conditions in time, prevent equipment damage due to overload or failure, and ensure production safety.

[0017] The system can also realize data visualization. Through a three-dimensional visualization interface, the system can intuitively display the equipment operation state, and facilitate the management personnel to master the equipment operation condition. The system can present complex data in an intuitive way, improve the decision-making efficiency and operation efficiency of the management personnel. At the same time, the system can support decision optimization. Through data analysis and simulation, the system provides scientific basis for production scheduling, equipment maintenance, etc., and improves the overall management level. Based on historical data and real-time data, the system provides optimization suggestions to help the management personnel to make scientific production plan and maintenance strategy.

[0018] Finally, the system has good compatibility and expandability. The system adopts modular design, supports import and processing of multiple data formats, and ensures the compatibility and expandability of the system on different platforms. In addition, the system also supports dynamic Retrofit configuration method, realizes automatic serialization and deserialization of API, and improves the flexibility and maintainability of the system. At the same time, the system provides multiple terminal access modes such as Web terminal and mobile terminal, supports real-time monitoring, operation control and fault alarm of the ash conveying system by the user, and improves the usability and user satisfaction of the system.

[0019] In summary, the present application provides a digital twin system for ash conveying process in thermal power plant based on digital twin technology. Through three-dimensional modeling, real-time data acquisition, simulation, visualization and intelligent analysis, the system realizes comprehensive monitoring and optimization of the ash conveying system. The system not only improves the production efficiency and equipment management level of the thermal power plant, but also provides strong support for the intelligent transformation of the thermal power plant. IV. BRIEF DESCRIPTION OF DRAWINGS

[0020] The present application relates to a digital twin system for ash conveying process in thermal power plant. The technical implementation involves the cooperative work of multiple modules, including three-dimensional modeling, data acquisition, digital twin engine, simulation and visualization, intelligent analysis and user interaction. To more clearly show the structure and function of the present application, the drawings are as follows:

[0021] Figure 1 : System architecture diagram

[0022] This diagram shows the overall architecture of the coal-fired power plant ash conveying process digital twin system, including three-dimensional modeling module, data acquisition and transmission module, digital twin engine module, simulation and visualization module, intelligent analysis and decision module, and user interaction and control module. Through this diagram, the logical relationship and collaborative working method between the modules of the system can be intuitively understood, providing technical reference for subsequent implementation.

[0023] Figure 2 : Data acquisition and transmission flowchart

[0024] This diagram shows the implementation process of data acquisition and transmission in the coal-fired power plant ash conveying system, including sensor deployment, data acquisition, data transmission, data processing, and data interface configuration. This diagram shows the complete process of data acquisition and transmission, providing data support for system operation.

[0025] Figure 3 : Digital twin engine implementation flowchart

[0026] This diagram shows the implementation process of the digital twin engine, including model loading, light source and lighting setting, animation control, real-time synchronization, and rendering and display. This diagram shows the implementation process of the digital twin engine, providing core support for system operation.

[0027] Figure 4 : User interaction and control flowchart

[0028] This diagram shows the implementation process of the user interaction and control module in the coal-fired power plant ash conveying system, including user access, data display, operation control, fault alarm, and data export. This diagram shows the implementation process of the user interaction and control module, providing user operation support for system operation. Five, specific implementation

[0029] The specific implementation of the coal-fired power plant ash conveying process digital twin system of the present application includes the following aspects:

[0030] In the system design phase, first of all, the physical environment of the coal-fired power plant ash conveying system needs to be investigated in detail, and the layout and operation characteristics of key equipment such as ash hoppers, warehouse pumps, pipelines, and air compressors are determined. Based on the research results, high-precision 3D modeling technology is used, and professional software such as 3ds Max and Maya is used to model each device in the ash conveying system, ensuring that the scale, material, and lighting effects of the model are highly consistent with the actual equipment. During modeling, special attention should be paid to the details of the model, such as the internal structure of the ash hopper, the movement trajectory of the warehouse pump, and the direction of the pipeline, to ensure the realism and accuracy of the model. In addition, the model needs to support the import of multiple data formats, such as FBX, OBJ, and GLT, which are common Mesh data formats, to improve the compatibility and scalability of the system. Through PBR (Physical-Based Rendering) technology, the model can accurately simulate the light flow in the real world, achieving high-fidelity rendering effects, making the digital twin highly consistent with the actual equipment in terms of lighting, reflection, and material. This modeling method not only improves the visualization of the system, but also provides a high-quality three-dimensional basis for subsequent simulation and analysis.

[0031] In the data collection phase, the system collects real-time data such as temperature, pressure, flow, and equipment status by installing sensors on key devices in the ash conveying system. The deployment of sensors needs to cover key equipment such as ash hoppers, warehouse pumps, pipelines, and air compressors to ensure the comprehensiveness and representativeness of the data. The data collection module needs to have high precision and stability to ensure real-time and accuracy of the data. At the same time, to deal with the problem of large data volume and frequent transmission, the system uses network protocols such as Socket communication and UnityWebRequest, combined with Retrofit library and UniRx framework, to realize asynchronous data request and processing, ensuring the efficiency and stability of data transmission. In addition, the system also designs a dynamic Retrofit configuration method to support different platform data interfaces, realizes API automatic serialization and deserialization, and improves the flexibility and maintainability of the system. Through this module, the system can obtain the running state of the ash conveying system in real time, providing reliable data support for subsequent simulation and analysis.

[0032] In the implementation phase of the digital twin engine, the system uses three-dimensional rendering technologies such as Unity Engine or WebGL to build a three-dimensional digital model of the ash conveying system and synchronizes it with the physical system in real time. The digital twin engine needs to have good rendering performance to ensure smooth operation on different devices. The system achieves high-fidelity rendering effects through light source and global lighting settings, simulates the device working environment realistically, and balances performance overhead. In addition, the system also supports model animation control system, which controls the animation playback state of pre-defined action information by reading the working state data, and realizes the dynamic display of the device running state. This module not only improves the visualization effect of the system, but also provides dynamic three-dimensional model support for subsequent simulation and analysis. During the rendering process, the system needs to optimize the model to ensure its compatibility and stability on different devices, avoiding performance problems caused by large or complex models.

[0033] In the implementation phase of the simulation and visualization module, the system simulates the running state of the ash conveying system based on the physical simulation engine, including the processes of ash amount change, flue gas flow, compressed air blowing, etc. The simulation module needs to have a high-precision physical engine that can accurately simulate the motion trajectory and state change of devices such as ash hoppers, warehouse pumps, and pipelines. By importing the collected device running state data, the system can dynamically simulate the running process of the ash conveying system and provide users with intuitive visual effects. The visualization module supports the import and display of multiple data formats to ensure that users can intuitively understand the device running situation. In addition, the system also supports particle effects to simulate the motion effect of gas and ash, including the flue gas concentration change, ash falling, and compressed air blowing effect of the boiler, electric ash removal, and bag ash removal, improving the visualization effect and interactive experience of the system. Through this module, users not only can see the running state of the device, but also can intuitively feel the complexity and dynamic changes of the ash conveying process through dynamic particle effects, thereby improving the intuitiveness and operability of the system.

[0034] In the implementation phase of the intelligent analysis and decision-making module, the system uses big data analysis, machine learning, and other technologies to analyze the collected equipment operation status data, predict equipment failures, optimize operation parameters, and provide decision support. The intelligent analysis module needs to have good algorithm models to ensure the accuracy and reliability of the predictions. In addition, the system also supports multi-threaded data processing, combined with Linq extension operators to simplify the development process and improve the maintainability and scalability of the system. Through intelligent analysis, the system can provide early warning of potential failures, optimize equipment operation parameters, and improve the efficiency and stability of the ash conveying system. This module not only improves the intelligence level of the system but also provides scientific decision-making basis for management personnel. During the analysis process, the system needs to clean, normalize, and extract features from the data to provide a foundation for subsequent prediction and optimization. Through machine learning algorithms, the system can train on historical data, build prediction models, and dynamically adjust based on real-time data to ensure the accuracy and reliability of the prediction results.

[0035] In the implementation phase of the user interaction and control module, the system provides multi-terminal access methods such as Web and mobile terminals, supporting real-time monitoring, operation control, and fault alarm of the ash conveying system by users. The user interaction module needs to have good user experience to ensure that users can easily operate and query. In addition, the system also supports modular design, pre-fabricates data lists, column charts, line charts, pie charts, scatter charts, and other charts, and links data with models and virtual buttons in the scene to realize dynamic display and interaction of data. Through this module, users can not only view the running status of the equipment but also intuitively understand the running status of the ash conveying system through the linkage of charts and models, improving the operation efficiency and user satisfaction of the system. During the interaction process, the system needs to provide real-time feedback on user operations to ensure that users can timely obtain information on the running status of the equipment and realize real-time control of the running status of the equipment through the linkage of virtual buttons and models.

[0036] In the system deployment and running phase, the system needs to be deployed in the production environment of the thermal power plant to ensure real-time synchronization with the physical system. During deployment, the server, network, storage, and other infrastructure need to be configured to ensure the stability and security of the system. At the same time, the system needs to manage user permissions to ensure that users with different roles can access corresponding data and functions. During operation, the system needs to monitor the running status of the equipment in real time to ensure the stable operation of the ash conveying system. At the same time, the system needs to record user operations to ensure the traceability of the operation process. In addition, the system also needs to back up data regularly to ensure the security and integrity of the data. During operation, the system needs to dynamically analyze the running status of the equipment to ensure the efficient operation of the ash conveying system and provide optimization suggestions through the intelligent analysis module to help management personnel develop scientific production plans and maintenance strategies.

[0037] In the system maintenance and optimization phase, the system needs to maintain the digital twin platform regularly to ensure its stable operation. During the maintenance process, the server, network, storage and other infrastructure need to be checked to ensure their normal operation. At the same time, the system needs to collect and analyze user feedback to ensure that the user experience and functions of the system meet the actual needs. In addition, the system also needs to clean up and optimize the data regularly to ensure the accuracy and integrity of the data. In the optimization process, the system needs to update the model to ensure its consistency with the actual equipment. At the same time, the system also needs to optimize the algorithm model to ensure the accuracy and reliability of the prediction results. Through continuous maintenance and optimization, the system can continuously improve its performance and stability, providing more intelligent support for the production management of the power plant.

[0038] In the system expansion and upgrade phase, the system needs to expand and upgrade the digital twin platform according to the development needs of the power plant. During the expansion process, new equipment and new technologies need to be modeled and integrated to ensure the compatibility and scalability of the system. At the same time, the system needs to investigate user needs to ensure the practicality and operability of new functions. In the upgrade process, the system architecture needs to be optimized to ensure its stability and security. In addition, the system also needs to optimize the algorithm model to ensure the accuracy and reliability of the prediction results. Through continuous expansion and upgrade, the system can continuously improve its functions and performance, enabling the intelligent transformation of the power plant.

Claims

1. A digital twin system for ash conveying processes in thermal power plants, characterized in that... A full-process visual management system is constructed, encompassing "3D modeling - real-time data acquisition - dynamic simulation - intelligent decision-making - interactive control." This system utilizes a digital twin engine to achieve real-time mapping between the physical system and the virtual model, and includes the following core modules: (1) 3D modeling module: Based on high-precision 3D modeling technology, a 3D digital model of the ash conveying system is constructed, covering key equipment such as ash hoppers, silo pumps, and pipelines. It supports the import of common formats such as FBX, OBJ, and GLT, and achieves high-fidelity restoration of materials and lighting through PBR physical rendering technology. (2) Data acquisition and transmission module: Deploy multiple types of sensors to collect operating data such as temperature, pressure, and flow in real time, and use industrial Ethernet or wireless communication protocols to transmit data. Asynchronous data processing is achieved through Socket communication, UnityWebRequest and Retrofit library. (3) Digital Twin Engine Module: A 3D rendering platform is built using the Unity engine or WebGL technology. Scene simulation is achieved through light source and global illumination settings. Model animation control is driven based on working status data, and real-time synchronization between physical system and virtual model is supported. (4) Simulation and visualization module: Based on the physical simulation engine, it simulates the process of ash volume change, flue gas flow, etc., integrates particle special effects technology to present dynamic effects such as compressed air blowing, and displays the equipment operation status through a three-dimensional visualization interface. (5) Intelligent Analysis and Decision Module: Utilizes big data analysis and machine learning algorithms to perform fault prediction and operational parameter optimization on collected data, supports multi-threaded data processing and LINQ extended operators, and provides decision support. (6) User interaction and control module: Provides multi-terminal access interfaces for Web and mobile terminals, integrates visualization components such as data lists and bar charts, realizes equipment status monitoring, operation control and fault alarm functions, and supports the linkage and interaction between models and data.

2. The digital twin system according to claim (i), characterized in that... The 3D modeling module also has the following characteristics: (1) The model's scale and materials are ≥95% consistent with the actual equipment; (2) Supports dynamic loading and unloading of model components to improve system operating efficiency; (3) Use LOD (Level of Detail) technology to optimize the rendering performance of complex scenes.

3. The digital twin system according to claim (i), characterized in that... The data acquisition and transmission module meets the following technical requirements: (1) Sensors are deployed to cover key equipment such as ash hoppers, silo pumps, and pipelines, with a data acquisition frequency of ≥10Hz; (2) Data transmission latency ≤50ms, and cross-platform API interface adaptation is achieved by using dynamic Retrofit configuration; (3) It has data cleaning and outlier filtering functions to ensure data accuracy ≥ 99.5%.

4. The digital twin system according to claim (i), characterized in that... The digital twin engine module achieves the following technical effects: (1) The model real-time synchronization latency is ≤100ms, supporting smooth operation across multiple devices and platforms; (2) By using light source baking technology to balance rendering quality and performance overhead, the frame rate is stabilized at over 60fps. (3) Accurate simulation of device motion trajectory based on physics engine with an error rate of ≤2%.

5. The digital twin system according to claim (i), characterized in that... The simulation and visualization module includes the following technical features: (1) Supports dynamic simulation of flue gas concentration in scenarios such as boilers, electrostatic precipitators, and bag filters; (2) Particle effects rendering efficiency ≥ 100,000 particles / second, achieving realistic reproduction of the dust falling and blowing process; (3) The visual interface supports 2D / 3D view switching and provides real-time alarm indicators for device status.

6. The digital twin system according to claim (i), characterized in that... The intelligent analysis and decision-making module has the following functions: (1) A machine learning algorithm is used to establish a device fault prediction model with an early warning accuracy of ≥90%; (2) Supports multi-objective optimization algorithms, and the ash conveying efficiency is improved by ≥15% after the running parameters are optimized; (3) Provide historical data backtracking and trend analysis to generate visual decision-making reports.

7. The digital twin system according to claim (i), characterized in that... The user interaction and control module meets the following interaction requirements: (1) Consistent design of multi-terminal interface, with operation response latency ≤300ms; (2) Supports linkage control between virtual buttons and physical devices, with a control command feedback time of ≤1s; (3) Integrates data export and report generation functions, and supports output in Excel, PDF and other formats.

8. The digital twin system according to claim 1, characterized in that... The system has modular expansion capabilities and supports: (1) Rapid import and integration of new equipment models, with an extension cycle of ≤2 working days; (2) Dynamic configuration of sensor type and data interface, compatible with ≥90% of industry standard protocols; (3) The algorithm model can be upgraded and optimized online without interrupting the system operation.

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