3D modeling and visualization system based on digital twin technology

Abstract

The present invention discloses a three-dimensional modeling and visualization system based on digital twin technology, which relates to the field of electrical digital data processing technology. The three-dimensional modeling and visualization system of the digital twin technology includes: a first physical data acquisition module; a second physical data acquisition module; a multi-angle data integration module; and a dynamic interaction module. The present invention acquires the first physical data and the second physical data by real-time monitoring the changes of the physical building data in the first database and the second database within a preset time period, and performs data fusion on the first physical data and the second physical data, and transmits the result of the data fusion to the dynamic interaction module for scene simulation and visualizes it through an interactive interface, thereby improving the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, and solves the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a three-dimensional modeling and visualization system based on digital twin technology. Background Art

[0002] With the continuous advancement and maturity of technology, digital twin 3D modeling and visualization systems will play an important role in more fields. Among them, digital twin (DT) is a cloud-based virtual representation technology that completes the mapping of the entire life cycle of physical equipment or systems in virtual space by integrating multidisciplinary and multi-scale simulation processes. 3D modeling is a technology that uses computer software to present virtual objects in three dimensions. Through 3D modeling, objects, buildings, products, etc. in the real world can be virtualized to achieve highly realistic display and interactive experience. The data visualization system is a powerful data processing tool that can present massive amounts of data in an intuitive and easy-to-understand way. The combination of digital twin 3D modeling and visualization systems combines the real-time, predictive and optimization of digital twins with the high fidelity and interactivity of 3D modeling to form a powerful comprehensive solution.

[0003] The existing 3D modeling and visualization system recommends the corresponding initial model for the building to be constructed through the collaborative filtering recommendation algorithm of architectural features. Then the designer only needs to modify and improve the initial model to complete the construction of the 3D model of the building, thus effectively avoiding the tedious process of designers building the 3D model of the building from scratch.

[0004] For example, the power system operation data visualization system and method based on digital twin technology, which is announced by the invention patent with announcement number: CN112069247B, includes: the data acquisition module collects the operation data of the power system in real time, and then sends it to the control module through wireless communication technology; the control module retrieves the operation data analysis algorithm, the power system operation status identification algorithm and the operation data change prediction algorithm from the machine learning module, and applies them to the analysis, identification and prediction of the operation data, and obtains the power system operation analysis results, the power system operation status identification results, and the power system operation change prediction results, and then sends them to the digital twin model construction module; the digital twin model construction module constructs a three-dimensional digital twin model of the power system based on the power system operation analysis results, the power system operation status identification results, and the power system operation change prediction results, and then displays it through the display module.

[0005] For example, the invention patent announcement with announcement number: CN118133724B discloses a method and system for visualizing space targets and their orbits based on digital twins, including: modeling according to the structural characteristics, external geometry, material properties, component details and internal structure of the space target; using the geocentric inertial coordinate system as the simulation coordinate system, establishing a non-perturbation force geometric motion model and a perturbation force geometric motion model, and using the non-perturbation force geometric motion model and the perturbation force geometric motion model to simulate the state of the space target; visually displaying the state of the space target based on a high-fidelity physical calculation model and graphics rendering technology.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, the initial model of the building to be constructed requires the collection of a large amount of user behavior data and building feature data. However, building feature data is often complex and diverse, which increases the difficulty of data processing, resulting in reduced real-time data processing and the problem of slow matching between the three-dimensional modeling data of the physical building and the actual scene. Summary of the invention

[0008] The embodiment of the present application solves the problem of slow matching between the three-dimensional modeling data of physical buildings and actual scenes in the prior art by providing a three-dimensional modeling and visualization system based on digital twin technology, thereby improving the matching efficiency between the three-dimensional modeling data of physical buildings and actual scenes.

[0009] The embodiment of the present application provides a three-dimensional modeling and visualization system based on digital twin technology, including: a first physical data acquisition module, a second physical data acquisition module, a multi-angle data integration module and a dynamic interaction module; wherein, the first physical data acquisition module is used to monitor in real time the changes of physical building data in the first database within a preset time period to obtain first physical data, and at the same time transmit the acquired first physical data to the multi-angle data integration module, the first database is used to store the physical building data in the first database that needs to be mapped with the first data, and the first data mapping is used to map the physical building data in the first database with the three-dimensional space in the physical building; the second physical data acquisition module is used to monitor in real time the changes of physical building data in the second database within a preset time period to obtain second physical data, and at the same time transmit the acquired second physical data to the multi-angle data integration module To the multi-angle data integration module, the second database is used to store the physical building data in the second database that needs to be mapped with the second data, the second data mapping includes a first mapping and a second mapping, the first mapping is used to map the physical building data in the second database with the acquired first physical data, and the second mapping is used to map the physical building data in the second database with the three-dimensional space in the physical building; the multi-angle data integration module is used to receive the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module and perform data fusion, and at the same time transmit the result of the data fusion to the dynamic interaction module for visual display; the dynamic interaction module is used to perform scene simulation according to the result of the data fusion and perform visual display through an interactive interface, and the scene simulation is used to reflect the real-time operating status of the physical building under a preset simulation scene.

[0010] Furthermore, the specific process of real-time monitoring the changes of physical building data in the first database within a preset time period to obtain first physical data is as follows: S11, obtaining first physical building data from the first database according to a preset first acquisition frequency, the first physical building data being used to reflect the changes of data in the first database of the physical building within a preset time period; S12, determining whether the obtained first physical building data meets the set first abnormality threshold, if so, recording it as the first abnormality data and performing a first abnormality feedback, otherwise executing S13, the first abnormality feedback being used to feed back the corresponding abnormal position and abnormality type in the first abnormal data to a preset person; S13, storing the obtained first physical building data in the first database and performing a first preprocessing to obtain the first physical data.

[0011] Furthermore, the obtaining of the first physical data further includes obtaining a first data update complexity score according to the real-time update of the first physical data in the first database; the first data update complexity score is used to measure the complexity of the real-time update of the first physical data within a preset time period, and the first data update complexity score is calculated by the following formula:

[0012] ;

[0013] Where t is the number of the preset time period, , T is the total number of preset time periods, represents the first data update complexity fraction of the first physical data in the t-th preset time period, e is a natural constant, represents the first physical data transmission rate of the first physical data in the tth preset time period, represents the first physical data reference transmission rate, represents the first physical data amount of the first physical data in the t-th preset time period, represents the reference first physical data volume, represents the number of times the first physical data is updated within the t-th preset time period, Indicates the number of reference updates of the first physical data; the specific steps for obtaining the first physical data transmission rate are: recording the first transmission timestamp of the first physical data in real time, and obtaining the first physical data transmission rate according to the change of the first transmission timestamp within a preset time period, wherein the first transmission timestamp indicates the time difference between the time when the multi-angle data integration module receives the first physical data and the time when the first physical data is sent.

[0014] Furthermore, the specific process of real-time monitoring the changes of the physical building data in the second database within a preset time period to obtain the second physical data is as follows: S21, obtaining the second physical building data from the second database according to the preset second acquisition frequency, the second physical building data being used to reflect the changes of the data in the second database of the physical building within the preset time period; S22, judging whether the obtained second physical building data meets the set second abnormality threshold, if so, recording it as the second abnormality data and performing the second abnormality feedback, otherwise executing S23, the second abnormality feedback is used to feed back the corresponding abnormal position and abnormality type in the second abnormal data to the preset personnel; S23, storing the obtained second physical building data in the second database and performing a second preprocessing to obtain the second physical data.

[0015] Furthermore, the obtaining of the second physical data further includes obtaining a second data update complexity score according to the real-time update of the second physical data in the second database. The second data update complexity score is used to measure the complexity of the real-time update of the second physical data within a preset time period. The second data update complexity score is calculated by the following formula:

[0016] ;

[0017] Where t is the number of the preset time period, , T is the total number of preset time periods, represents the second data update complexity fraction of the second physical data in the tth preset time period, e is a natural constant, represents the second physical data transmission rate of the second physical data in the tth preset time period, represents the second physical data reference transmission rate, represents the second physical data amount of the second physical data in the tth preset time period, represents the reference second physical data volume, represents the number of times the second physical data is updated within the tth preset time period, Indicates the second physical data reference update times.

[0018] Furthermore, the data fusion result is transmitted to the dynamic interaction module for visual display, which also includes inputting the data fusion result into the digital twin model, and obtaining data mapping indicators through the digital twin model. The digital twin model is used to obtain the data mapping indicators, and the data mapping indicators are obtained through the first data mapping indicator and the second data mapping indicator.

[0019] Furthermore, the expression of the data mapping index obtained by the digital twin model is:

[0020] ;

[0021] Where y is the number of the first physical data, , Y is the total number of first physical data, n is the number of second physical data, , N is the total number of the second physical data, e is a natural constant, represents the data matching correction factor, Indicates the data matching degree of the first physical data and the second physical data in the data fusion process within a preset time period, Indicates the matching degree of reference data. represents the first data mapping index correction factor, represents the first data mapping index of the yth first physical data within a preset time period, represents the first mapping index correction factor, represents the first mapping index of the nth second physical data within a preset time period, represents the second mapping index correction factor, The second mapping index represents the nth second physical data within a preset time period.

[0022] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0023] 1. The first physical data and the second physical data are acquired by real-time monitoring of the changes of the physical building data in the first database and the second database within a preset time period, and then data fusion is performed on the first physical data and the second physical data. Finally, the result of the data fusion is transmitted to the dynamic interaction module for scene simulation and visualized through the interactive interface, thereby improving the accuracy and reliability of data fusion, and further improving the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, and effectively solving the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art;

[0024] 2. Acquire first physical building data from the first database at a preset first acquisition frequency, and determine whether the acquired first physical building data meets a set first abnormal threshold. Finally, store the acquired first physical building data in the first database and perform a first preprocessing to acquire the first physical data, thereby improving the accuracy of acquiring the first physical building data, and further achieving more accurate acquisition of the first physical data.

[0025] 3. Acquire the second physical building data from the second database through a preset second acquisition frequency, and determine whether the acquired second physical building data meets the set second abnormal threshold. Finally, store the acquired second physical building data in the second database and perform a second preprocessing to acquire the second physical data, thereby improving the accuracy of acquiring the second physical building data, and further achieving more accurate acquisition of the second physical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the structure of a three-dimensional modeling and visualization system based on digital twin technology provided in an embodiment of the present application;

[0027] Figure 2 A flowchart for obtaining the first physical data provided in an embodiment of the present application;

[0028] Figure 3 A flowchart for obtaining the second physical data provided in an embodiment of the present application;

[0029] Figure 4 A three-dimensional coordinate analysis diagram of data matching provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiment of the present application solves the problem of slow matching between the three-dimensional modeling data of physical buildings and the actual scenes in the prior art by providing a three-dimensional modeling and visualization system based on digital twin technology. The first physical data acquisition module monitors the changes of the physical building data in the first database within a preset time period in real time to obtain the first physical data, and transmits the acquired first physical data to the multi-angle data integration module. Then, the second physical data acquisition module monitors the changes of the physical building data in the second database within a preset time period in real time to obtain the second physical data, and transmits the acquired second physical data to the multi-angle data integration module. Then, the multi-angle data integration module receives the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module and performs data fusion. At the same time, the result of the data fusion is transmitted to the dynamic interaction module for visualization. Finally, the dynamic interaction module performs scene simulation according to the result of the data fusion and performs visualization through the interactive interface, thereby improving the matching efficiency between the three-dimensional modeling data of the physical building and the actual scene.

[0031] The technical solution in the embodiment of the present application is to solve the problem of slow matching between the three-dimensional modeling data of the above-mentioned physical building and the actual scene. The overall idea is as follows:

[0032] The first physical data and the second physical data are acquired by real-time monitoring of changes in the physical building data in the first database and the second database within a preset time period, and data fusion is performed on the first physical data and the second physical data. Meanwhile, the result of the data fusion is transmitted to the dynamic interaction module for scene simulation and visualized through the interactive interface, thereby achieving the effect of improving the matching efficiency between the three-dimensional modeling data of the physical building and the actual scene.

[0033] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0034] like Figure 1As shown, it is a structural schematic diagram of a three-dimensional modeling and visualization system based on digital twin technology provided in an embodiment of the present application. The three-dimensional modeling and visualization system based on digital twin technology provided in an embodiment of the present application includes: a first physical data acquisition module, a second physical data acquisition module, a multi-angle data integration module and a dynamic interaction module; wherein the first physical data acquisition module is used to monitor in real time the changes of physical building data in the first database within a preset time period to obtain first physical data, and at the same time transmit the acquired first physical data to the multi-angle data integration module, the physical building data is used to reflect the operating status of the physical building within a preset time period, the first database is used to store the physical building data in the first database that needs to be mapped with the first data, the first data mapping is used to map the physical building data in the first database with the three-dimensional space in the physical building, and the first physical data represents the physical building data updated in real time in the first database within a preset time period; the second physical data acquisition module is used to monitor in real time the changes of physical building data in the second database within a preset time period The second physical data is acquired by the first physical data acquisition module and the second physical data acquisition module is transmitted to the multi-angle data integration module. The second database is used to store the physical building data in the second database that needs to be mapped with the second data. The second data mapping includes a first mapping and a second mapping. The first mapping is used to map the physical building data in the second database with the acquired first physical data. The second mapping is used to map the physical building data in the second database with the three-dimensional space in the physical building. The second physical data represents the physical building data updated in real time in the second database within a preset time period. The multi-angle data integration module is used to receive the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module and perform data fusion. At the same time, the result of the data fusion is transmitted to the dynamic interaction module for visual display. The data fusion is used to remove redundant data and noise data. The dynamic interaction module is used to perform scene simulation according to the result of the data fusion and perform visual display through an interactive interface. The scene simulation is used to reflect the real-time operation status of the physical building in a preset simulation scene.

[0035] In this embodiment, data to be mapped are extracted from the first database and the second database, usually including timestamps, user behavior data and geographic location information. These data are usually sampled and recorded at specific time intervals (such as every hour or every minute). The extracted data are cleaned to remove invalid values, duplicates or outliers. At the same time, the data is converted into a format suitable for mapping, including a unified data type, unit and timestamp. Then, the three-dimensional space of the physical building is constructed through building information modeling software, and the data to be mapped into the three-dimensional space (such as temperature, humidity, energy consumption) is clearly defined. The position of each data point in the database in the three-dimensional space is determined through a position sensor, and it is ensured that the timestamp in the database matches the time dimension in the three-dimensional space. At the same time, visualization attributes such as color, size and transparency are assigned to the mapped data so as to clearly display the changes and distribution of the data in the three-dimensional view. The preset personnel can view the mapping results through the three-dimensional visualization tool to check whether the data is correctly displayed in the expected position, thereby improving the matching efficiency between the three-dimensional modeling data of the physical building and the actual scene.

[0036] Further, such as Figure 2 As shown, it is a flowchart for obtaining the first physical data provided by an embodiment of the present application. The specific process of real-time monitoring the changes of the physical building data in the first database within a preset time period to obtain the first physical data is: S11, obtaining the first physical building data from the first database according to the preset first acquisition frequency, the first acquisition frequency is set by summing and averaging the acquisition frequencies in the preset database, and the first physical building data is used to reflect the changes of the data in the first database of the physical building within the preset time period; S12, judging whether the obtained first physical building data meets the set first abnormal threshold, if so, it is recorded as the first abnormal data and the first abnormal feedback is performed, otherwise S13 is executed, the first abnormal feedback is used to feed back the corresponding abnormal position and abnormal type in the first abnormal data to the preset personnel; S13, storing the obtained first physical building data in the first database and performing a first preprocessing to obtain the first physical data, the first preprocessing is used to convert the text data in the first physical building data into numerical data.

[0037] In this embodiment, the first acquisition frequency is usually represented by the sum and average of the acquisition frequency values ​​in the preset first database. The first physical building data usually includes temperature data, humidity data and light intensity data. In actual application scenarios, temperature data plays a major role. Usually, a corresponding temperature threshold is set for the temperature of the physical building according to actual needs and application scenarios. This temperature threshold can be static (such as the indoor temperature should not exceed 26°C) or dynamic (such as automatically adjusting the set value of the indoor temperature according to outdoor weather changes). The first abnormal threshold is usually represented by the sum and average of the abnormal temperature data in the preset first database, wherein the abnormal temperature data indicates that when it exceeds 26°C, the indoor temperature is above 26°C. The temperature exceeds the set value of the indoor temperature. In the process of obtaining the first physical building data, it is necessary to record the time interval for data acquisition in real time to ensure that the data changes of the physical building can be fully and accurately reflected within the preset time period, usually including temperature fluctuations, energy loss and personnel flow patterns; for data determined to be abnormal, the system needs to generate a first abnormal feedback, which usually includes the location of the abnormality (such as abnormal sensor location, abnormal area location), the type of abnormality (such as high temperature, low pressure) and the specific value of the abnormality. This feedback will be sent to the preset personnel so that they can take timely measures, thereby improving the accuracy and efficiency of obtaining the first physical data of the physical building in actual scenarios.

[0038] Further, the first physical data is obtained, and then the first data update complexity score is obtained according to the real-time update of the first physical data in the first database; the first data update complexity score is used to measure the complexity of the real-time update of the first physical data within a preset time period, and the first data update complexity score is calculated by the following formula:

[0039] ;

[0040] Where t is the number of the preset time period, , T is the total number of preset time periods, represents the first data update complexity fraction of the first physical data in the t-th preset time period, e is a natural constant, represents the first physical data transmission rate of the first physical data in the tth preset time period, represents the first physical data reference transmission rate, represents the first physical data amount of the first physical data in the t-th preset time period, represents the reference first physical data volume, represents the number of times the first physical data is updated within the t-th preset time period, Indicates the first physical data reference update number.

[0041] Specifically, the first physical data transmission rate is used to measure the speed at which the first physical data is received and sent by the multi-angle data integration module within a preset time period. The specific steps for obtaining the first physical data transmission rate are: recording the first transmission timestamp of the first physical data in real time, and obtaining the first physical data transmission rate based on the change of the first transmission timestamp within the preset time period. The first transmission timestamp represents the time difference between the time when the multi-angle data integration module receives the first physical data and the time when the first physical data is sent.

[0042] In this embodiment, the reference transmission rate of the first physical data is usually represented by summing and averaging the data transmission speeds preset in the first database, the reference first physical data volume is usually represented by summing and averaging the physical data volume within a specified time period (such as one minute, ten minutes) in the preset first database, and the reference update number of the first physical data is usually represented by summing and averaging the update number of the physical data in the preset first database within a specified time period (such as one minute, ten minutes), wherein the preset complexity is usually represented by summing and averaging the data complexity in the preset first database.

[0043] It should be understood that the algorithm of this embodiment combines the first physical data transmission rate, the first physical data volume and the number of first physical data updates, and comprehensively analyzes to obtain the first data update complexity score. The first physical data volume and the first physical data transmission rate in this formula not only unilaterally affect the value of the first data update complexity score, but also affect each other. When the first physical data volume is large, if the first physical data transmission rate is low, then the update and transmission of the first physical data will become slow, thereby increasing the complexity of the first physical data update. This is because a large amount of first physical data requires a longer time to transmit, which may cause delays or interruptions in the update of the first physical data. On the contrary, if the first physical data transmission rate is high, even if the first physical data volume is large, it can be transmitted in a shorter time, thereby reducing the complexity of the first physical data update, achieving an improvement in the accuracy and reliability of obtaining the first data update complexity score, and then achieving an improvement in the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, effectively solving the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art.

[0044] Further, such as Figure 3As shown, it is a flowchart for obtaining the second physical data provided by an embodiment of the present application. The specific process of real-time monitoring the changes of the physical building data in the second database within a preset time period to obtain the second physical data is: S21, obtaining the second physical building data from the second database according to the preset second acquisition frequency, the second acquisition frequency is set by summing and averaging the acquisition frequency data in the preset database, and the second physical building data is used to reflect the changes of the data in the second database of the physical building within the preset time period; S22, judging whether the obtained second physical building data meets the set second abnormal threshold, if so, it is recorded as the second abnormal data and the second abnormal feedback is performed, otherwise S23 is executed, the second abnormal feedback is used to feed back the corresponding abnormal position and abnormal type in the second abnormal data to the preset personnel; S23, storing the obtained second physical building data in the second database and performing a second preprocessing to obtain the second physical data, the second preprocessing is used to convert the text data in the second physical building data into numerical data.

[0045] In this embodiment, the second collection frequency is usually represented by the result of summing and averaging the collection frequency values ​​in the preset second database. The second physical building data usually includes equipment operation data and energy consumption data, wherein the equipment operation data usually includes the number of elevator operations and the on / off status of the lighting system. These data are usually obtained through equipment sensors. The energy consumption data usually includes real-time consumption or historical data of electricity, water, gas, etc. In practical applications, energy consumption data is usually used to quantify the abnormality of the second physical building data. The second abnormal threshold is usually represented by the result of summing and averaging the abnormal energy consumption data in the preset second database. The abnormal energy consumption data represents the data when the energy consumption of the physical building in a preset time period exceeds the preset energy-saving target value. The preset energy-saving target value is set by the preset personnel according to the preset The rated power of the equipment is set. When the second physical building exceeds the second abnormal threshold, the second physical building data exceeding the second abnormal threshold is recorded as the second abnormal data. At this time, a second abnormal feedback needs to be generated. This feedback should contain sufficient information so that the preset personnel can quickly understand and respond to the abnormal situation. Usually, the second abnormal feedback will include the specific value of the abnormal data, the time when the abnormality occurred, the location of the abnormality (such as the abnormal location of the room, the abnormal location of the equipment), and the type of abnormality (such as high temperature, low humidity). This information can be sent to the preset personnel by e-mail, SMS, message push or direct display on the monitoring interface. After receiving the second abnormal feedback, the preset personnel needs to take corresponding actions based on the feedback information, thereby improving the accuracy and efficiency of obtaining the second physical data.

[0046] Further, the second physical data is obtained, and then the second data update complexity score is obtained according to the real-time update of the second physical data in the second database. The second data update complexity score is used to measure the complexity of the real-time update of the second physical data within a preset time period. The second data update complexity score is calculated by the following formula:

[0047] ;

[0048] Where t is the number of the preset time period, , T is the total number of preset time periods, represents the second data update complexity fraction of the second physical data in the tth preset time period, e is a natural constant, represents the second physical data transmission rate of the second physical data in the tth preset time period, represents the second physical data reference transmission rate, represents the second physical data amount of the second physical data in the tth preset time period, represents the reference second physical data volume, represents the number of times the second physical data is updated within the tth preset time period, Indicates the number of times the second physical data reference is updated; the second physical data transmission rate is used to measure the speed at which the second physical data is received and sent by the multi-angle data integration module within a preset time period. The specific steps for obtaining the second physical data transmission rate are: recording the second transmission timestamp of the second physical data in real time, and obtaining the second physical data transmission rate according to the change of the second transmission timestamp within the preset time period. The second transmission timestamp indicates the time difference between the time when the multi-angle data integration module receives the second physical data and the time when the second physical data is sent.

[0049] In this embodiment, the reference transmission rate of the second physical data is usually represented by summing and averaging the data transmission speeds in the preset second database, the reference second physical data volume is usually represented by summing and averaging the physical data volume in the preset second database within a specified time period (such as one minute, ten minutes), and the reference update number of the second physical data is usually represented by summing and averaging the update number of the physical data in the preset second database within a specified time period (such as one minute, ten minutes), wherein the preset complexity is usually represented by summing and averaging the data complexity in the preset second database.

[0050] It should be understood that the algorithm of this embodiment combines the second physical data transmission rate, the second physical data volume and the number of times the second physical data is updated, and a comprehensive analysis is performed to obtain the second data update complexity score. The second physical data volume and the second physical data transmission rate in this formula not only unilaterally affect the value of the second data update complexity score, but also affect each other. When the second physical data volume is large, if the second physical data transmission rate is low, then the update and transmission of the second physical data will become slow, thereby increasing the complexity of the second physical data update. This is because a large amount of second physical data requires a longer time to transmit, which may cause delays or interruptions in the update of the second physical data. On the contrary, if the second physical data transmission rate is high, even if the second physical data volume is large, it can be transmitted in a shorter time, thereby reducing the complexity of the second physical data update, achieving an improvement in the accuracy and reliability of obtaining the second data update complexity score, and thereby achieving an improvement in the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, effectively solving the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art.

[0051] Furthermore, the specific steps of mapping the physical building data in the second database with the acquired first physical data include: matching the physical building data in the second database with the mapping information in the first physical data for data items to obtain a first mapping indicator, the mapping information including a timestamp, a data identifier and location information, the first mapping indicator being used to measure the degree of mapping between the physical building data in the second database and the acquired first physical data; determining whether the acquired first mapping indicator is equal to the reference first mapping indicator, and if so, storing the acquired first mapping indicator in the second database, otherwise re-matching the data items until the acquired first mapping indicator is equal to the reference first mapping indicator.

[0052] In this embodiment, the mapping information generally includes a timestamp (used to determine the time point of the data), a data identifier (used to uniquely identify a data item) and location information (used to indicate the specific location of the data in the physical building). In practical applications, the mapping information is a clear and searchable data structure, such as a database table or an index file. The corresponding reference time index is generally obtained by summing and averaging the time data in a preset database, the corresponding reference data item index is obtained by summing and averaging the time data per unit time in the preset database, the corresponding reference location index is obtained by summing and averaging the physical building location points in the preset database, and the corresponding reference first mapping index is obtained by summing and averaging the reference time index, the reference data item index and the reference location index. The reference time index is used to measure the amount of data mapped by the physical building data per unit time in the first mapping process, the reference data item index is used to measure the number of data items of the physical building data per unit time in the first mapping process, and the reference location index is used to measure the number of location points of the physical building data in a preset area.

[0053] Specifically, the physical building data to be mapped are extracted from the second database. These data usually include temperature, humidity, pressure, and energy consumption, depending on the needs of monitoring and management. When extracting data, it is necessary to keep the timestamp and possible identifier of each data item (if the second database itself has it). Then, the timestamp, data identifier, and location information in the mapping information are used as keywords to find the corresponding item in the data of the second database. If the timestamp and data identifier match, then it can be generally considered that the two data items are corresponding. If the data in the second database does not have a direct data identifier, it may be necessary to approximately match them through a combination of timestamp and location information. This usually involves creating a new data structure (such as a dictionary, list, or database table) in memory to store the correspondence between the mapping information in the first physical data and the data items in the second database. According to the correspondence between the mapping information in the first physical data and the data items in the second database, the amount of successfully matched data items is counted to obtain a mapping success rate (i.e., a first mapping index). The mapping success rate represents the ratio of the number of successfully matched data items to the total number of data items, thereby improving the accuracy of mapping the physical building data in the second database with the acquired first physical data.

[0054] Furthermore, the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module are received and data fusion is performed, and then the data matching degree is obtained according to the result of the data fusion; the data matching degree is used to measure the matching degree of the first physical data and the second physical data in the data fusion process, and the data matching degree is obtained by the following method: the timestamps and data items corresponding to the first physical data and the second physical data are aligned to obtain the timestamp consistency rate and the data item consistency rate, and the data matching degree is obtained by combining the obtained first data update complexity score and the second data update complexity score, the timestamp consistency rate is used to measure the consistency degree between the timestamp corresponding to the first physical data completing the first data mapping and the timestamp corresponding to the second physical data completing the second mapping, and the data item consistency rate is used to measure the consistency degree between the number of data items corresponding to the first physical data and the number of data items corresponding to the second physical data.

[0055] In this embodiment, the data matching degree is calculated by the following formula:

[0056] ;

[0057] In the formula, m is the number of data fusion, , M is the total number of data fusion times, Indicates the data matching degree of the first physical data and the second physical data in the data fusion process within a preset time period, Indicates the first data update complexity score of the first physical data in the preset time period during the mth data fusion process, Indicates the second data update complexity score of the first physical data in the preset time period during the mth data fusion process, represents the data update complex score reference deviation between the first data update complex score and the second data update complex score, e is a natural constant, represents the timestamp consistency rate of the first physical data and the second physical data in the mth data fusion process within the preset time period, represents the reference timestamp consistency rate, represents the data item consistency rate of the first physical data and the second physical data in the mth data fusion process within a preset time period, Indicates the consistency rate of the reference data item.

[0058] Specifically, to simplify the analysis, define , , where represents the data item matching coefficient of the first physical data in the preset time period during the data fusion process, It represents the data update complexity coefficient of the first physical data in the preset time period during the data fusion process, wherein the data update complexity score reference deviation is usually represented by the result of summing and averaging the data complexity in the preset database, the reference timestamp consistency rate is usually represented by the result of summing and averaging the time difference in the preset database, and the reference data item consistency rate is usually represented by the result of summing and averaging the data items in the preset database. The simplified calculation formula for data matching is:

[0059] ,like Figure 4 As shown, it is a three-dimensional coordinate analysis diagram of the data matching degree provided in an embodiment of the present application. It can be seen from the figure that the data matching degree increases with the increase of the data item matching coefficient (the increase is small), and the data matching degree decreases with the increase of the data update complexity coefficient (the increase is large).

[0060] It should be understood that the algorithm of this embodiment combines the data item matching coefficient and the data update complexity coefficient, and comprehensively analyzes to obtain the data matching degree. The timestamp consistency rate and the data item consistency rate in this formula not only unilaterally affect the value of the data matching degree, but also influence each other. When the timestamp consistency rate is high, the system may tend to believe that there is a certain correlation between the data items, and thus pay more attention to the calculation results of the data item consistency rate. If the data item consistency rate is also high at this time, then the data matching degree will be significantly improved. On the contrary, if the timestamp consistency rate is low, but the data item consistency rate is abnormally high, the system will usually believe that there is an abnormality in this match (such as data tampering or false alarm), thereby improving the accuracy and reliability of data matching, and then improving the efficiency of matching the three-dimensional modeling data of physical buildings with the actual scene, effectively solving the problem of slow matching of the three-dimensional modeling data of physical buildings with the actual scene in the prior art.

[0061] Furthermore, the result of data fusion is transmitted to the dynamic interaction module for visual display, which also includes inputting the result of data fusion into the digital twin model, and obtaining data mapping indicators through the digital twin model. The digital twin model is used to obtain data mapping indicators. The data mapping indicators are obtained through the first data mapping indicator and the second data mapping indicator. The second data mapping indicator includes the first mapping indicator and the second mapping indicator. The first data mapping indicator is used to measure the degree of mapping between the physical building data in the first database and the three-dimensional space in the physical building. The second mapping indicator is used to measure the degree of mapping between the physical building data in the second database and the three-dimensional space in the physical building.

[0062] In this embodiment, in the digital twin model, by processing and analyzing the input data, a series of data mapping indicators can be obtained. These data mapping indicators are the manifestation of physical entities in digital space, which can reflect various attributes and states of physical entities. For example, in manufacturing, data mapping indicators usually include equipment operating efficiency, failure rate, and energy consumption. In urban management, they usually include traffic flow, environmental quality, and population density. In the dynamic interaction module, users can browse and analyze data mapping indicators through various interactive means (such as clicking, dragging, zooming, etc.), so as to have a deeper understanding of the state and behavior of physical entities. In actual applications, the dimensional data of physical buildings are usually measured in real time by laser scanning equipment, and compared with the dimensional data in the preset physical building database to obtain the dimensional deviation. When the dimensional deviation is 0, the first data mapping indicator is the highest at this time, wherein the dimensional deviation represents the difference between the dimensional data actually measured of the physical building and the dimensional data in the preset physical building database, and the first data mapping indicator represents the ratio of the dimensional deviation to the dimensional data in the preset physical building database. A high degree of mapping means that the information in the database can very accurately reflect the actual condition of the physical building.

[0063] Specifically, the first data mapping indicator is usually used to measure the degree of mapping between the physical building data of a specific part (which may be a subsystem or a specific type of data) in the second database and the three-dimensional space of the physical building. For example, it may focus on the data mapping accuracy of the building's electrical system, plumbing system or security monitoring system; the second data mapping indicator is aimed at the mapping degree of another type of data in the second database. This subdivision helps to more accurately evaluate the mapping quality of different data sets in the database and identify possible differences or problem areas; in practical applications, these data mapping indicators together constitute an evaluation system for the integrity and accuracy of the digital representation of physical buildings. By regularly monitoring and evaluating these indicators, problems in data mapping can be discovered and resolved in a timely manner, and the accuracy and reliability of the digital model can be improved. In addition, these data mapping indicators can also be used as input to optimize the data fusion algorithm, and the fusion process can be continuously improved through a feedback mechanism to improve the accuracy and comprehensiveness of the final data mapping results, thereby achieving an improvement in the accuracy and comprehensiveness of the data mapping indicators.

[0064] Furthermore, the expression of data mapping index obtained through the digital twin model is:

[0065] ;

[0066] Where y is the number of the first physical data, , Y is the total number of first physical data, n is the number of second physical data, , N is the total number of the second physical data, e is a natural constant, represents the data mapping index of the first physical data and the second physical data in the data fusion process within a preset time period, represents the data matching correction factor, Indicates the data matching degree of the first physical data and the second physical data in the data fusion process within a preset time period, Indicates the matching degree of reference data. represents the first data mapping index correction factor, represents the first data mapping index of the yth first physical data within a preset time period, represents the first mapping index correction factor, represents the first mapping index of the nth second physical data within a preset time period, represents the second mapping index correction factor, A second mapping index representing the nth second physical data within a preset time period;

[0067] Specifically, the data matching correction factor, the first data mapping index correction factor, the first mapping index correction factor and the second mapping index correction factor are obtained from a preset database. The data matching correction factor is used to correct the timestamp deviation and data item deviation of the first physical data and the second physical data during the data fusion process. The first data mapping index correction factor is used to correct the mapping deviation between the physical building data in the first database and the three-dimensional space in the physical building. The first mapping index correction factor is used to correct the mapping deviation between the physical building data in the second database and the acquired first physical data. The second mapping index correction factor is used to correct the mapping deviation between the physical building data in the second database and the three-dimensional space in the physical building.

[0068] In this embodiment, the three-dimensional space in the physical building generally includes rooms, corridors and stairs. The rooms, corridors and stairs in the three-dimensional space are marked to obtain room position points, corridor position points and stair position points, and are transmitted to the second database. In practical applications, the second mapping index is generally obtained based on the distance between the room position point in the three-dimensional space and the room position point in the second database, wherein the distance between the room position point in the three-dimensional space and the room position point in the second database is generally measured by a position sensor, and the second mapping index is used to measure the degree of deviation of the distance between the room position point in the second database and the room position point in the three-dimensional space. In order to simplify the analysis, the definition , , , where represents the data matching coefficient of the first physical data and the second physical data in the data fusion process within a preset time period, represents the first data mapping index coefficient of the first physical data in the data fusion process within the preset time period, It represents the second data mapping index coefficient of the second physical data in the preset time period during the data fusion process, wherein the reference data matching degree is usually represented by the result of summing and averaging the data matching degrees in the preset database. The simplified calculation formula of the data mapping index is:

[0069] ,The statistical table of changes in data mapping indicators is shown in Table 1:

[0070] Table 1 Statistics of changes in data mapping indicators:

[0071] ;

[0072] From Table 1, we can see that when =0, =1 and =2, the more accurate the corresponding data mapping index is, that is, the mapping degree between the physical building data in the first database and the second database and the three-dimensional space in the physical building is the greatest; it should be understood that the data matching degree correction factor is obtained from the preset database. In a specific embodiment, the relationship between the data matching degree and the data mapping index is fitted by the historical data matching degree and the data mapping index value in the preset database to obtain a fitting curve, and the relationship between the data matching degree coefficient and the data mapping index is determined according to the fitting curve. The real-time data matching degree in the data fusion process is substituted into the fitting curve to obtain the corresponding data matching degree correction factor, wherein the historical data matching degree is used to reflect the actual degree of matching in different time periods or different scenarios in the past, and is usually in the form of a percentage value or fraction in the preset database.

[0073] The first data mapping indicator correction factor is obtained from a preset database. In a specific embodiment, the relationship between the first data mapping indicator and the data mapping indicator is fitted through the historical mapping data and the first data mapping indicator data in the preset database to obtain a fitting curve, the relationship between the first data mapping indicator and the data mapping indicator is determined according to the fitting curve, and the real-time first data mapping indicator in the first data mapping process is substituted into the fitting curve to obtain the corresponding first data mapping indicator correction factor.

[0074] The first mapping index correction factor is obtained from a preset database. In a specific embodiment, the relationship between the first mapping index and the data mapping index is fitted by presetting the historical first mapping data and the first mapping index data in the second database to obtain a fitting curve, the relationship between the first mapping index and the data mapping index is determined according to the fitting curve, and the real-time first mapping index in the first mapping process is substituted into the fitting curve to obtain the corresponding first mapping index correction factor.

[0075] The second mapping index correction factor is obtained from a preset database. In a specific embodiment, the relationship between the second mapping index and the data mapping index is fitted by the historical second mapping data and the second mapping index data in the preset second database to obtain a fitting curve, the relationship between the second mapping index and the data mapping index is determined according to the fitting curve, and the real-time second mapping index in the second mapping process is substituted into the fitting curve to obtain the corresponding second mapping index correction factor, thereby improving the accuracy and efficiency of obtaining the data mapping index, thereby improving the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, and effectively solving the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art.

[0076] Furthermore, the dynamic interaction module includes a simulation unit and a visualization interaction unit; the simulation unit is used to perform scene simulation according to the access requirements of authorized users to obtain simulation data, and the simulation data includes energy consumption data, structural stress data and environmental response data; the visualization interaction unit is used to visualize the simulation data on the interactive interface in the form of images and animations.

[0077] In this embodiment, the authorized user is usually an access user who has passed identity authentication. According to the specific needs of the authorized user, including data type (energy consumption, structural stress, environmental response) and time range, the specific conditions of the simulation scene, such as building type, equipment configuration, and environmental conditions, are determined. Then, the building information modeling technology is used to establish an interactive interface of the physical building of the simulation object. According to actual needs, simulation parameters are set, such as climate data, equipment operating status, and building material properties. Then, professional simulation software (such as EnergyPlus) is used to perform simulation operations, and the simulation process is monitored in real time; line graphs, bar graphs, or pie charts are used. It displays the energy consumption in different time periods and different areas, and uses color depth to indicate energy consumption intensity, helping users to quickly identify energy consumption hot spots; uses color or line thickness to indicate stress magnitude, and provides a slice view of the physical building structure so that users can observe the distribution and changes of stress from different angles; marks the distribution of environmental parameters (such as temperature, humidity, and air quality) on the map, uses color coding to indicate the values ​​of different parameters, and simulates the occurrence and evolution of weather phenomena (such as rainfall, wind fields, etc.) through animation, which enhances users' intuitive perception of the environment and improves the efficiency of real-time interaction between authorized users and simulation data.

[0078] To summarize, the embodiment of the present application obtains the first physical data and the second physical data by real-time monitoring the changes of the physical building data in the first database and the second database within a preset time period, and then fuses the first physical data and the second physical data. Finally, the result of the data fusion is transmitted to the dynamic interaction module for scene simulation and visualized through the interactive interface, thereby improving the accuracy and reliability of data fusion, and further improving the efficiency of matching the three-dimensional modeling data of the physical building with the actual scene, effectively solving the problem of slow matching of the three-dimensional modeling data of the physical building with the actual scene in the prior art.

[0079] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0080] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0083] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0084] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A three-dimensional modeling and visualization system based on digital twin technology, characterized by: include: A first physical data acquisition module, a second physical data acquisition module, a multi-angle data integration module and a dynamic interaction module; The first physical data acquisition module is used to monitor the changes of the physical building data in the first database in real time within a preset time period to acquire the first physical data, and transmit the acquired first physical data to the multi-angle data integration module. The first database is used to store the physical building data in the first database that needs to be mapped with the first data, and the first data mapping is used to map the physical building data in the first database with the three-dimensional space in the physical building. The second physical data acquisition module is used to monitor in real time the changes of the physical building data in the second database within a preset time period to acquire second physical data, and transmit the acquired second physical data to the multi-angle data integration module. The second database is used to store the physical building data in the second database that needs to be mapped with the second data. The second data mapping includes a first mapping and a second mapping. The first mapping is used to map the physical building data in the second database with the acquired first physical data, and the second mapping is used to map the physical building data in the second database with the three-dimensional space in the physical building. The multi-angle data integration module is used to receive the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module and perform data fusion, and transmit the result of the data fusion to the dynamic interaction module for visual display; The dynamic interaction module is used to perform scene simulation according to the result of data fusion and to perform visual display through an interactive interface. The scene simulation is used to reflect the real-time operating status of the physical building in a preset simulation scene.

2. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 1, characterized in that: The specific process of real-time monitoring the changes of the physical building data in the first database within a preset time period to obtain the first physical data is: S11, acquiring first physical building data from a first database according to a preset first acquisition frequency, where the first physical building data is used to reflect changes in data of the physical building in the first database within a preset time period; S12, determining whether the acquired first physical building data meets the set first abnormality threshold, if so, recording it as the first abnormality data and performing the first abnormality feedback, otherwise executing S13, the first abnormality feedback is used to feed back the corresponding abnormal position and abnormality type in the first abnormality data to the preset personnel; S13, storing the acquired first physical building data in a first database and performing first preprocessing to acquire first physical data.

3. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 2, characterized in that: The obtaining of the first physical data further includes obtaining a first data update complexity score according to a real-time update of the first physical data in the first database; The first data update complexity score is used to measure the complexity of real-time updating of the first physical data within a preset time period. The first data update complexity score is calculated by the following formula: ； Where t is the number of the preset time period, , T is the total number of preset time periods, represents the first data update complexity fraction of the first physical data in the t-th preset time period, e is a natural constant, represents the first physical data transmission rate of the first physical data in the tth preset time period, represents the first physical data reference transmission rate, represents the first physical data amount of the first physical data in the t-th preset time period, represents the reference first physical data volume, represents the number of times the first physical data is updated within the t-th preset time period, Indicates the first physical data reference update number.

4. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 1, characterized in that: The specific process of real-time monitoring the changes of the physical building data in the second database within a preset time period to obtain the second physical data is: S21, acquiring second physical building data from a second database according to a preset second acquisition frequency, where the second physical building data is used to reflect changes in data of the physical building in the second database within a preset time period; S22, determining whether the acquired second physical building data meets the set second abnormality threshold, if so, recording it as the second abnormality data and performing second abnormality feedback, otherwise executing S23, the second abnormality feedback is used to feed back the corresponding abnormal position and abnormality type in the second abnormality data to the preset personnel; S23, storing the acquired second physical building data in a second database and performing a second preprocessing to acquire second physical data.

5. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 4, characterized in that: The obtaining of the second physical data further includes obtaining a second data update complexity score according to a real-time update of the second physical data in the second database; The second data update complexity score is used to measure the complexity of real-time updating of the second physical data within a preset time period. The second data update complexity score is calculated by the following formula: ； Where t is the number of the preset time period, , T is the total number of preset time periods, represents the second data update complexity fraction of the second physical data in the tth preset time period, e is a natural constant, represents the second physical data transmission rate of the second physical data in the tth preset time period, represents the second physical data reference transmission rate, represents the second physical data amount of the second physical data in the tth preset time period, represents the reference second physical data volume, represents the number of times the second physical data is updated within the tth preset time period, Indicates the second physical data reference update times.

6. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 1, characterized in that: The specific steps of mapping the physical building data in the second database with the acquired first physical data include: Matching data items of the physical building data in the second database with mapping information in the first physical data to obtain a first mapping index, wherein the mapping information includes a timestamp, a data identifier, and location information, and the first mapping index is used to measure the degree of mapping between the physical building data in the second database and the obtained first physical data; Determine whether the acquired first mapping index is equal to the reference first mapping index. If so, store the acquired first mapping index in the second database. Otherwise, re-match the data items until the acquired first mapping index is equal to the reference first mapping index.

7. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 4, characterized in that: The receiving of the first physical data and the second physical data transmitted by the first physical data acquisition module and the second physical data acquisition module and performing data fusion, and then obtaining a data matching degree according to a result of the data fusion; The data matching degree is used to measure the matching degree between the first physical data and the second physical data in the data fusion process, and the data matching degree is obtained by the following method: The timestamps and data items corresponding to the first physical data and the second physical data are aligned to obtain the timestamp consistency rate and the data item consistency rate, and the data matching degree is obtained by combining the obtained first data update complexity score and the second data update complexity score.

8. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 1, characterized in that: The result of data fusion is transmitted to the dynamic interaction module for visual display, which also includes inputting the result of data fusion into the digital twin model and obtaining data mapping indicators through the digital twin model. The digital twin model is used to obtain data mapping indicators, and the data mapping indicators are obtained through the first data mapping indicator and the second data mapping indicator.

9. The three-dimensional modeling and visualization system based on digital twin technology as claimed in claim 8, characterized in that: The expression of the data mapping index obtained by the digital twin model is: ； Where y is the number of the first physical data, , Y is the total number of first physical data, n is the number of second physical data, , N is the total number of the second physical data, e is a natural constant, Indicates the data mapping index of the first physical data and the second physical data in the data fusion process within a preset time period, represents the data matching correction factor, Indicates the data matching degree of the first physical data and the second physical data in the data fusion process within a preset time period, Indicates the matching degree of reference data. represents the first data mapping index correction factor, represents the first data mapping index of the yth first physical data within a preset time period, represents the first mapping index correction factor, represents the first mapping index of the nth second physical data within a preset time period, represents the second mapping index correction factor, The second mapping index represents the nth second physical data within a preset time period.

10. The three-dimensional modeling and visualization system based on digital twin technology according to claim 1, characterized in that: The dynamic interaction module includes a simulation unit and a visualization interaction unit; The simulation unit is used to perform scenario simulation according to the access requirements of the authorized user to obtain simulation data, wherein the simulation data includes energy consumption data, structural stress data and environmental response data; The visualization interaction unit is used to visualize the simulation data on the interaction interface in the form of images and animations.

Images