Information visual management system and method based on digital twinning

Abstract

The invention discloses an information visualization management system and method based on digital twinning, and the system comprises an emotion calculation module, a three-dimensional printing module, a multi-physics field analysis module, a real-time data processing module and a visualization display module. Intelligent recognition of user emotional states, rapid manufacturing and monitoring of physical entities, simulation analysis of multi-physical field behaviors and real-time visualization and dynamic adjustment of information are achieved, the system generates a personalized user experience optimization strategy by collecting multi-modal data of a user, and the user experience optimization strategy is optimized by combining three-dimensional printing and physical state monitoring. According to the method, the authenticity and interactivity of the digital twinborn model are improved, and meanwhile, the fusion of the multi-physical field coupling analysis result and the emotion data provides comprehensive data support for real-time data processing, so that the information display effect is optimized, the user experience and the data processing efficiency are improved, and an effective tool is provided for intelligent management.

Description

Technical Field

[0001] The present invention relates to the technical field of information visualization management, and more specifically, to an information visualization management system and method based on digital twins. Background Art

[0002] With the rapid development of information technology, digital twin technology has gradually become a key technology in many fields such as industry, medical care, and transportation. Digital twin technology creates virtual models of physical entities to achieve real-time monitoring, analysis, and optimization of physical entities. Digital twin technology has been widely used in many fields. For example, in the manufacturing industry, by simulating the performance of physical objects in various scenarios, it can avoid the repeated development of multiple prototypes and minimize the total development time. In the medical field, digital twin technology can perform three-dimensional modeling of patient body parts and simulate lesions, thereby helping doctors diagnose and treat diseases more accurately. In smart city planning, digital twin technology allows urban planners to simulate traffic flow, identify traffic bottlenecks in advance, optimize traffic signals and road design, and perform intelligent scheduling.

[0003] Although the application prospects of digital twin technology are broad, it still faces some challenges. For example, the business model is not mature enough, the initial investment is high, customized solutions are difficult to replicate and costly, and there is a standardization dilemma in technology. The scale, parameters, format and cycle of data collection have not yet formed a unified standard, which makes data integration and interface docking difficult. In addition, the models and data volumes constructed by digital twins are large, which poses challenges to the computer hardware processing and computing capabilities as well as the display effects of terminal devices. The lack of data capabilities also includes low and incomplete data quality, differences in data format and quality, as well as data security and privacy protection.

[0004] Therefore, the digital twin system in the existing technology has problems such as insufficient information visualization, poor user experience, and low data processing and display efficiency. Summary of the invention

[0005] In order to overcome the problems of insufficient information visualization, poor user experience, low data processing and display efficiency in the digital twin system in the prior art, the present invention designs an information visualization management system and method based on digital twins that can effectively solve the above technical problems.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] An information visualization management system based on digital twins, including: an emotional computing module, a three-dimensional printing module, a multi-physics field analysis module, a real-time data processing module and a visualization display module;

[0008] The emotion calculation module is used to collect user multimodal data, analyze the user's emotional state, generate emotion feature data, and generate a personalized user experience optimization strategy based on the emotion feature data, and send it to the real-time data processing module;

[0009] The three-dimensional printing module is used to manufacture a physical entity according to the digital twin model, collect physical state data of the physical entity in real time, and send it to the multi-physics field analysis module;

[0010] The multi-physics field analysis module is used to receive physical state data, simulate and analyze the multi-physics field behavior of the physical entity, obtain multi-physics field coupling analysis results, and send them to the real-time data processing module;

[0011] The real-time data processing module is used to receive the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis results, perform real-time processing and fusion, generate a comprehensive data stream, and generate raw data required for visualization based on the comprehensive data stream and send it to the visualization display module;

[0012] The visualization display module is used to receive the original data, display it using a variety of visualization methods, and dynamically adjust the display content according to the user's interactive operation.

[0013] Preferably, the emotion calculation module includes:

[0014] A multimodal data acquisition unit, used to collect the user's facial expression images, voice signals and operation behavior data;

[0015] The emotion recognition algorithm unit uses a deep learning model to extract features from the facial expression image to identify the user's emotion category; performs acoustic feature analysis on the voice signal to determine the user's emotion intensity; performs pattern recognition on the operation behavior data to analyze the user's behavior habits and preferences;

[0016] A strategy generation unit generates a personalized user experience optimization strategy according to the emotional feature data, and sends the emotional feature data and the user experience optimization strategy to the real-time data processing module.

[0017] Preferably, the three-dimensional printing module comprises:

[0018] A model information acquisition unit, used to acquire geometric information of the digital twin model, including the size, shape and topological structure of the three-dimensional model, and the material properties, including the density, elastic modulus and thermal conductivity physical parameters of the material;

[0019] A physical entity manufacturing unit, manufacturing a physical entity according to the digital twin model;

[0020] The physical state acquisition unit uses a sensor network to monitor the state changes of the physical entity in different physical fields in real time, and sends the physical state data to the multi-physical field analysis module.

[0021] Preferably, the multi-physics field analysis module comprises:

[0022] A model building unit, used to build a multi-physics field coupling mathematical model according to a specific application scenario of a physical entity;

[0023] A simulation analysis unit is used to discretize and solve the multi-physical field behaviors of physical entities using simulation algorithms to obtain accurate simulation analysis results;

[0024] A result prediction unit is used to predict problems and faults occurring in the multi-physics field coupling mathematical model according to the analysis results.

[0025] Preferably, the visual display module includes:

[0026] A model display unit, used for performing three-dimensional dynamic display of the digital twin model;

[0027] Data chart display unit, used to update and display equipment operating parameters and performance index data in real time in the form of charts;

[0028] The virtual scene display unit is used to construct virtual scenes to allow users to experience various situations in the actual physical environment.

[0029] A digital twin-based information visualization management method is used to implement the above-mentioned digital twin-based information visualization management system, comprising the following steps:

[0030] Collect user multimodal data, analyze the user's emotional state through the emotional calculation module, generate emotional feature data, and generate a personalized user experience optimization strategy based on the emotional feature data;

[0031] The emotional feature data and the user experience optimization strategy are sent to the real-time data processing module, and at the same time, a physical entity is manufactured using a three-dimensional printing module according to the digital twin model, and the physical state data of the physical entity is collected in real time;

[0032] The physical state data is sent to a multi-physics field analysis module to simulate and analyze the multi-physics field behavior of the physical entity to obtain a multi-physics field coupling analysis result;

[0033] The multi-physical field coupling analysis result is sent to a real-time data processing module, which receives the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis result, performs real-time processing and fusion, and generates a comprehensive data stream;

[0034] Generate raw data required for visual display according to the integrated data stream, and send the raw data to a visual display module;

[0035] The visualization display module receives the raw data, displays it using a variety of visualization methods, and dynamically adjusts the display content according to the user's interactive operation.

[0036] An electronic device comprises a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above-mentioned information visualization management method based on digital twins are implemented.

[0037] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned information visualization management method based on digital twins.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: the present solution collects multi-dimensional information of users through the multimodal data acquisition unit of the emotion computing module, and with the help of the emotion recognition algorithm unit and the strategy generation unit, it can not only accurately analyze the user's emotional state, but also generate personalized user experience optimization strategies based on the emotion feature data, thereby improving the user experience; the physical entity manufacturing unit in the three-dimensional printing module manufactures the physical entity based on the digital twin model, while the physical state acquisition unit monitors the physical state data in real time, thereby realizing the close connection between the virtual and physical worlds, and providing a basis for subsequent precise analysis; the multi-physical field analysis module can deeply simulate and predict the complex multi-physical field behaviors of the physical entity by establishing a coupled mathematical model and adopting a simulation algorithm, thereby improving the accuracy of the analysis; the real-time data processing module processes and integrates the emotion feature data, the user experience optimization strategy and the multi-physical field coupling analysis results in real time, generates a comprehensive data stream, and improves the efficiency of data processing; the various units in the visualization display module, such as the model display unit, the data chart display unit and the virtual scene display unit, use a variety of visualization means and dynamic adjustment functions to enhance the richness and flexibility of information visualization, so that users can observe and operate the system more intuitively, thereby improving the overall data processing and display efficiency and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0040] Figure 1 This is a structural diagram of an information visualization management system based on digital twins;

[0041] Figure 2 This is a step-by-step diagram of an information visualization management method based on digital twins. DETAILED DESCRIPTION

[0042] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0043] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0044] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0045] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0046] Example 1

[0047] An information visualization management system based on digital twins, see Figure 1 , including: emotional computing module, 3D printing module, multi-physics field analysis module, real-time data processing module and visualization display module;

[0048] The emotion calculation module is used to collect user multimodal data, analyze the user's emotional state, generate emotion feature data, and generate a personalized user experience optimization strategy based on the emotion feature data, and send it to the real-time data processing module;

[0049] Multimodal data acquisition unit configuration: high-definition cameras are installed in various operation areas, meeting rooms, rest areas and other places in the industrial environment to capture employees' facial expression images; voice acquisition equipment is installed at equipment operating tables, office areas, etc. to collect employees' voice signals; at the same time, employees are equipped with smart wearable devices with sensors, such as smart bracelets, smart work clothes, etc., to collect operation behavior data, including gestures, movement trajectories, operation frequencies, etc.

[0050] The emotion recognition algorithm unit is set up to build a deep learning model, and feature extraction is performed on the collected facial expression images, such as identifying subtle changes in the eyebrows and mouth corners, and matching them with preset emotion categories, such as happiness, sadness, anger, surprise, etc., to accurately identify the emotion categories of employees; acoustic feature analysis is performed on voice signals to extract features such as pitch, speaking speed, volume, etc., and combined with semantic analysis to judge the emotional intensity of employees. For example, faster speaking speed and higher pitch may indicate emotional excitement; pattern recognition is performed on operational behavior data to analyze employees' behavioral habits and preferences. For example, some employees like to check parameters before starting when operating equipment, while others are accustomed to direct operation.

[0051] The strategy generation unit formulates a personalized user experience optimization strategy based on the emotional feature data output by the emotion recognition algorithm unit. For example, when it is detected that an employee is in a state of fatigue, the system will automatically adjust the lighting brightness and temperature of the work area, play soothing music, and remind employees to take a proper rest. If an employee is confused about a certain operation process, the system will push the relevant operation guidance video or graphic tutorial, and send these emotional feature data and optimization strategies to the real-time data processing module.

[0052] The three-dimensional printing module is used to manufacture a physical entity according to the digital twin model, collect physical state data of the physical entity in real time, and send it to the multi-physics field analysis module;

[0053] The model information acquisition unit is configured to obtain the geometric information of digital twin models of various equipment, components, and building structures from the digital twin platform of the industrial environment, including precise three-dimensional dimensions, complex shape contours, and topological structures; at the same time, it obtains material property data, such as the density of different materials (used to calculate weight and center of gravity), elastic modulus (affecting the deformation and strength of the structure), thermal conductivity (related to heat transfer and temperature distribution), and other physical parameters.

[0054] The physical entity manufacturing unit is equipped with multiple industrial-grade 3D printers. Based on the acquired digital twin model, appropriate printing materials and printing processes are selected to manufacture physical entities that are highly consistent with the digital twin model. The physical entity can be used for prototype testing of equipment, rapid replacement of parts, display of architectural models and other scenarios, thereby improving the flexibility and adaptability of the industrial environment.

[0055] Physical state acquisition unit deployment: installing a sensor network on the manufactured physical entity, including temperature sensors, pressure sensors, displacement sensors, strain sensors, etc., to monitor in real time the state changes of the physical entity under different physical fields, such as thermal fields, force fields, electromagnetic fields, etc. For example, monitoring the temperature rise, force deformation, displacement changes, etc. of equipment parts during operation, and sending these physical state data to the multi-physical field analysis module in real time.

[0056] The multi-physics field analysis module is used to receive physical state data, simulate and analyze the multi-physics field behavior of the physical entity, obtain multi-physics field coupling analysis results, and send them to the real-time data processing module;

[0057] The model building unit is set up according to the specific application scenarios and working conditions of the physical entity to establish a multi-physical field coupling mathematical model. This model comprehensively considers the interaction between physical entities in different physical fields, such as the impact of temperature changes in the thermal field on the material strength in the force field, the interference of the electromagnetic field on the thermal field and the force field, etc. It can accurately describe the behavioral characteristics of physical entities in complex environments. For example, for a device component working in a high temperature, high pressure, and strong electromagnetic environment, a coupling model including heat conduction equations, mechanical equilibrium equations, and electromagnetic field equations is established.

[0058] The simulation analysis unit is configured with advanced simulation algorithms, such as finite element analysis algorithm, finite difference algorithm, boundary element algorithm, etc., to discretize and solve the established multi-physical field coupling mathematical model. By dividing the grid, applying loads and boundary conditions, etc., the precise simulation analysis results of the physical entity under different working conditions are calculated, such as temperature field distribution, stress-strain cloud map, electromagnetic field intensity distribution, etc. These simulation results can provide important basis for the design optimization, performance evaluation and fault prediction of the physical entity.

[0059] Based on the simulation analysis results, the result prediction unit uses data mining, machine learning and other technologies to predict possible problems and failures in the multi-physical field coupling mathematical model. For example, by analyzing the stress and strain change trends of equipment components during long-term operation, the possible fatigue fracture location and time can be predicted; based on the temperature field distribution and heat conduction, the overheating failure risk of the equipment is predicted, and these prediction results are sent to the real-time data processing module.

[0060] The real-time data processing module is used to receive the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis results, perform real-time processing and fusion, generate a comprehensive data stream, and generate raw data required for visualization based on the comprehensive data stream and send it to the visualization display module;

[0061] Receive the emotional feature data and user experience optimization strategies from the emotional computing module, as well as the multi-physics coupling analysis results from the multi-physics analysis module, and use efficient data processing algorithms to clean, fuse and process these data in real time, remove noise data and outliers, extract key information, and generate comprehensive data streams. For example, associate employees' emotional state data with equipment operation state data to find out the potential correlation between employee emotional fluctuations and equipment failures; compare and analyze the multi-physics analysis results with the design parameters of the equipment, evaluate the performance indicators and safety performance of the equipment, and generate the original data required for visualization based on the comprehensive data stream and send it to the visualization display module.

[0062] The visualization display module is used to receive the original data, display it using a variety of visualization methods, and dynamically adjust the display content according to the user's interactive operation.

[0063] The model display unit is configured to perform three-dimensional dynamic display of the digital twin model using virtual reality (VR), augmented reality (AR) or three-dimensional visualization software. Users can wear a VR helmet or use AR glasses to view the three-dimensional models of equipment, parts, building structures, etc., including their internal structure, assembly relationships, motion status, etc. It also supports operations such as scaling, rotating, and cutting the model, making it convenient for users to observe and analyze from different angles and levels of detail.

[0064] The data chart display unit is set to update and display equipment operating parameters such as temperature, pressure, speed, flow, etc., performance indicator data such as production efficiency, failure rate, energy consumption, etc., and employee emotional data such as emotion category, emotion intensity, satisfaction, etc. in real time in the form of charts. It uses a variety of chart types such as bar charts, line charts, pie charts, scatter charts, etc. to intuitively present the changing trends and distribution of data. For example, a line chart is used to display the curve of equipment temperature changes over time, and a bar chart is used to compare the emotional intensity distribution of different employees, providing managers and operators with clear and intuitive data references.

[0065] The virtual scene display unit constructs a virtual industrial scene to simulate various situations in actual production, operation, maintenance and other processes. For example, it simulates the on-site scenario when equipment failure occurs, including abnormal sounds, smoke, vibrations and other phenomena of the equipment, so that maintenance personnel can be familiar with the fault characteristics in advance and improve fault diagnosis and handling capabilities; it creates a virtual training scene to provide new employees with training on equipment operation, safety regulations and other aspects, and enhances the training effect through virtual interaction and practical operations. At the same time, it supports users to perform interactive operations in virtual scenes, such as clicking on the equipment to view detailed information, operating virtual equipment to troubleshoot, etc., to achieve immersive experience and learning.

[0066] The emotion calculation module includes:

[0067] A multimodal data acquisition unit, used to collect the user's facial expression images, voice signals and operation behavior data;

[0068] The emotion recognition algorithm unit uses a deep learning model to extract features from the facial expression image to identify the user's emotion category; performs acoustic feature analysis on the voice signal to determine the user's emotion intensity; performs pattern recognition on the operation behavior data to analyze the user's behavior habits and preferences;

[0069] A strategy generation unit generates a personalized user experience optimization strategy according to the emotional feature data, and sends the emotional feature data and the user experience optimization strategy to the real-time data processing module.

[0070] The three-dimensional printing module comprises:

[0071] A model information acquisition unit, used to acquire geometric information of the digital twin model, including the size, shape and topological structure of the three-dimensional model, and the material properties, including the density, elastic modulus and thermal conductivity physical parameters of the material;

[0072] A physical entity manufacturing unit, manufacturing a physical entity according to the digital twin model;

[0073] The physical state acquisition unit uses a sensor network to monitor the state changes of the physical entity in different physical fields in real time, and sends the physical state data to the multi-physical field analysis module.

[0074] The multi-physics field analysis module includes:

[0075] A model building unit, used to build a multi-physics field coupling mathematical model according to a specific application scenario of a physical entity;

[0076] A simulation analysis unit is used to discretize and solve the multi-physical field behaviors of physical entities using simulation algorithms to obtain accurate simulation analysis results;

[0077] A result prediction unit is used to predict problems and faults occurring in the multi-physics field coupling mathematical model according to the analysis results.

[0078] The visual display module includes:

[0079] A model display unit, used for performing three-dimensional dynamic display of the digital twin model;

[0080] Data chart display unit, used to update and display equipment operating parameters and performance index data in real time in the form of charts;

[0081] The virtual scene display unit is used to construct virtual scenes to allow users to experience various situations in the actual physical environment.

[0082] Example 2

[0083] A digital twin-based information visualization management method, see Figure 2 , used for the above-mentioned information visualization management system based on digital twin, comprising the following steps:

[0084] Collect user multimodal data, analyze the user's emotional state through the emotional calculation module, generate emotional feature data, and generate a personalized user experience optimization strategy based on the emotional feature data;

[0085] The emotional feature data and the user experience optimization strategy are sent to the real-time data processing module, and at the same time, a physical entity is manufactured using a three-dimensional printing module according to the digital twin model, and the physical state data of the physical entity is collected in real time;

[0086] The physical state data is sent to a multi-physics field analysis module to simulate and analyze the multi-physics field behavior of the physical entity to obtain a multi-physics field coupling analysis result;

[0087] The multi-physical field coupling analysis result is sent to a real-time data processing module, which receives the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis result, performs real-time processing and fusion, and generates a comprehensive data stream;

[0088] Generate raw data required for visual display according to the integrated data stream, and send the raw data to a visual display module;

[0089] The visualization display module receives the raw data, displays it using a variety of visualization methods, and dynamically adjusts the display content according to the user's interactive operation.

[0090] An electronic device comprises a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above-mentioned information visualization management method based on digital twins are implemented.

[0091] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned information visualization management method based on digital twins.

[0092] Install high-definition cameras in the area covered by the system to capture users' facial expression images in real time. Equip voice acquisition equipment at key locations to collect users' voice signals. Provide users with smart wearable devices, such as smart bracelets, to collect operation behavior data, including gestures, movement trajectories, etc.

[0093] Use deep learning models to extract features from collected facial expression images and identify the user's emotion categories, such as happiness, sadness, anger, etc. Perform acoustic feature analysis on voice signals to determine the user's emotional intensity. For example, nervous emotions can be identified through features such as faster speech speed and higher pitch. Perform pattern recognition on operational behavior data to analyze user behavioral habits and preferences, such as identifying specific gesture patterns when users are concentrating on their work.

[0094] Based on the results of emotion recognition, emotion feature data is generated, including emotion category, emotion intensity, behavioral preference and other information. Based on the emotion feature data, a personalized user experience optimization strategy is formulated. For example, when the user is detected to be in a state of fatigue, the system will automatically adjust the environmental parameters, such as reducing noise, adjusting light brightness, playing soothing music, and reminding the user to take a proper rest; if the user is confused about a certain operation process, the system will push the relevant operation guidance video or graphic tutorial, and send the emotion feature data and personalized user experience optimization strategy to the real-time data processing module for further processing and fusion.

[0095] Based on the digital twin model, the corresponding physical entities, such as equipment parts, building models, etc., are manufactured using 3D printing modules. A sensor network is installed on the physical entities to collect physical state data in real time, including physical field information such as temperature, pressure, displacement, and strain.

[0096] The collected physical state data is sent to the multi-physics field analysis module, which simulates and analyzes the multi-physics field behavior of the physical entity to obtain multi-physics field coupling analysis results, such as temperature field distribution, stress-strain cloud map, electromagnetic field intensity distribution, etc.

[0097] The multi-physics field coupling analysis results are sent to the real-time data processing module for integration with the emotional feature data and user experience optimization strategies.

[0098] The real-time data processing module receives emotional feature data, user experience optimization strategies and multi-physical field coupling analysis results, processes and integrates these data in real time, and generates a comprehensive data stream, including user emotional state, physical entity state, optimization strategy and other information.

[0099] Based on the comprehensive data flow, the raw data required for visualization is generated, such as user sentiment charts, physical entity status charts, optimization strategy prompts, etc., and the raw data is sent to the visualization display module for visualization.

[0100] The visualization display module receives raw data and displays it using a variety of visualization methods, such as three-dimensional model display, data chart display, virtual scene display, etc. It dynamically adjusts the display content based on the user's interactive operations. For example, users can view three-dimensional models from different perspectives, view detailed data charts, enter virtual scenes for interactive experiences, etc. by clicking, dragging, and zooming.

[0101] An electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, an information visualization management method based on digital twins is implemented according to the above steps.

[0102] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an information visualization management method based on digital twins according to the above steps.

[0103] The same or similar reference numerals correspond to the same or similar components;

[0104] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0105] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. An information visualization management system based on digital twins, characterized in that: include: Emotional computing module, 3D printing module, multi-physics field analysis module, real-time data processing module and visualization display module; The emotion calculation module is used to collect user multimodal data, analyze the user's emotional state, generate emotion feature data, and generate a personalized user experience optimization strategy based on the emotion feature data, and send it to the real-time data processing module; The three-dimensional printing module is used to manufacture a physical entity according to the digital twin model, collect physical state data of the physical entity in real time, and send it to the multi-physics field analysis module; The multi-physics field analysis module is used to receive physical state data, simulate and analyze the multi-physics field behavior of the physical entity, obtain multi-physics field coupling analysis results, and send them to the real-time data processing module; The real-time data processing module is used to receive the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis results, perform real-time processing and fusion, generate a comprehensive data stream, and generate raw data required for visualization based on the comprehensive data stream and send it to the visualization display module; The visualization display module is used to receive the original data, display it using a variety of visualization methods, and dynamically adjust the display content according to the user's interactive operation.

2. According to claim 1, an information visualization management system based on digital twins is characterized in that: The emotion calculation module includes: A multimodal data acquisition unit, used to collect the user's facial expression images, voice signals and operation behavior data; The emotion recognition algorithm unit uses a deep learning model to extract features from the facial expression image to identify the user's emotion category; performs acoustic feature analysis on the voice signal to determine the user's emotion intensity; performs pattern recognition on the operation behavior data to analyze the user's behavior habits and preferences; A strategy generation unit generates a personalized user experience optimization strategy according to the emotional feature data, and sends the emotional feature data and the user experience optimization strategy to the real-time data processing module.

3. According to claim 1, an information visualization management system based on digital twins is characterized in that: The three-dimensional printing module comprises: A model information acquisition unit, used to acquire geometric information of the digital twin model, including the size, shape and topological structure of the three-dimensional model, and the material properties, including the density, elastic modulus and thermal conductivity physical parameters of the material; A physical entity manufacturing unit, manufacturing a physical entity according to the digital twin model; The physical state acquisition unit uses a sensor network to monitor the state changes of the physical entity in different physical fields in real time, and sends the physical state data to the multi-physical field analysis module.

4. According to claim 1, the information visualization management system based on digital twin is characterized in that: The multi-physics field analysis module includes: A model building unit, used to build a multi-physics field coupling mathematical model according to a specific application scenario of a physical entity; A simulation analysis unit is used to discretize and solve the multi-physical field behaviors of physical entities using simulation algorithms to obtain accurate simulation analysis results; A result prediction unit is used to predict problems and faults occurring in the multi-physics field coupling mathematical model according to the analysis results.

5. According to the digital twin-based information visualization management system of claim 1, it is characterized in that: The visual display module includes: A model display unit, used for performing three-dimensional dynamic display of the digital twin model; Data chart display unit, used to update and display equipment operating parameters and performance index data in real time in the form of charts; The virtual scene display unit is used to construct virtual scenes to allow users to experience various situations in the actual physical environment.

6. A method for information visualization management based on digital twins, used to implement an information visualization management system based on digital twins as described in any one of claims 1 to 5, characterized in that: The following steps are involved: Collect user multimodal data, analyze the user's emotional state through the emotional calculation module, generate emotional feature data, and generate a personalized user experience optimization strategy based on the emotional feature data; The emotional feature data and the user experience optimization strategy are sent to the real-time data processing module, and at the same time, a physical entity is manufactured using a three-dimensional printing module according to the digital twin model, and the physical state data of the physical entity is collected in real time; The physical state data is sent to a multi-physics field analysis module to simulate and analyze the multi-physics field behavior of the physical entity to obtain a multi-physics field coupling analysis result; The multi-physical field coupling analysis result is sent to a real-time data processing module, which receives the emotional feature data, the user experience optimization strategy and the multi-physical field coupling analysis result, performs real-time processing and fusion, and generates a comprehensive data stream; Generate raw data required for visual display according to the integrated data stream, and send the raw data to a visual display module; The visualization display module receives the raw data, displays it using a variety of visualization methods, and dynamically adjusts the display content according to the user's interactive operation.

7. An electronic device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the information visualization management method based on digital twins described in claim 6 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the information visualization management method based on digital twins described in claim 6 are implemented.

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