Visual laboratory system and method
By using digital twin models and simulation software, a digital twin model of the laboratory is constructed, which solves the problems of low model accuracy and fragmented management in laboratory management, and realizes efficient and visualized laboratory management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-01
- Publication Date
- 2026-04-07
AI Technical Summary
Existing laboratory management technologies struggle to achieve precise matching between physical space and digital models. Laboratory experimental project management still relies primarily on paper-based ledgers, which suffers from standardization deficiencies and fails to meet the needs of visualization, precision, and efficiency in laboratory management.
A digital twin model of the laboratory's physical space is constructed using the digital twin method. Point cloud data is collected using a 3D laser scanner to generate building and equipment models. Environmental and equipment data are then linked through a data association mechanism. Simulation experiments are conducted using simulation software, and an electronic ledger is established.
It achieves high-precision matching between digital models and physical space, presents data intuitively, reduces the risk of equipment damage, reduces trial and error costs, enables full-process information traceability and reproducibility, and solves the fragmentation problem of traditional management.
Smart Images
Figure CN121809025A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of laboratory management technology, and more specifically to a visual laboratory system and method. Background Technology
[0002] With the development of science and technology, the functions of laboratories are becoming increasingly complex. They not only include various types of precision experimental equipment, but also need to maintain specific environmental conditions. At the same time, they need to cope with the management needs of multidisciplinary experiments and the standardization of experimental procedures. The requirements for visualization, precision and efficiency of laboratory management are becoming more and more urgent.
[0003] However, current laboratory management technologies still have several core shortcomings that make it difficult to meet the needs of practical applications. Specifically, these shortcomings are reflected in the following four aspects: existing laboratory digital modeling technologies are unable to achieve accurate matching of physical space, digital models, and experimental data; and the management of laboratory experimental projects is still mainly based on paper ledgers, which have obvious deficiencies in standardization. Summary of the Invention
[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a visual laboratory system, comprising: The digital twin model construction module is used to construct a digital twin model of the laboratory physical space using the digital twin method. The digital twin model includes a building model and an equipment model. Based on the data association mechanism, laboratory environmental data is associated with the building model and equipment operation data is associated with the equipment model. The simulation experiment module is used to conduct simulation experiments based on laboratory environment data associated with the building model and equipment operation data associated with the equipment model, combined with simulation software.
[0005] Furthermore, in the digital twin model construction module, the specific method for constructing a digital twin model of the laboratory physical space using digital twin methods is as follows: A 3D point cloud data of the current physical space of the laboratory is collected by a 3D laser scanner installed in the laboratory. The 3D point cloud data is used as the basic data source for the digital twin to construct building models and equipment models. Based on the coordinate information in the 3D point cloud data, the equipment model is deployed to the corresponding physical location of the building model to form a digital twin model that is consistent with the physical space of the laboratory.
[0006] Furthermore, the specific method for constructing the building model and equipment model using the aforementioned 3D point cloud data as the basic data source for the digital twin is as follows: After preprocessing the 3D point cloud data, the preprocessed 3D point cloud data is segmented based on geometric features to obtain building point clouds and equipment point clouds. The ground point cloud and wall point cloud in the building point cloud are fitted with planes to generate ground models and wall models. The door and window point cloud and column point cloud in the building point cloud are extracted based on the normal vector mutation recognition of edge points to extract the rectangular outlines of doors and windows and columns. The rectangular outlines of doors and windows and columns are stretched vertically to the corresponding height to generate door and window models and column models. The ground model, wall model, door and window model and column model are merged to obtain the building model. The equipment point cloud is reconstructed using Poisson reconstruction and / or moving least squares method to generate equipment models.
[0007] Furthermore, in the digital twin model construction module, the specific method for associating laboratory environmental data with the building model and equipment operation data with the equipment model according to the data association mechanism is as follows: Assign data acquisition location tags to laboratory environmental data, the data acquisition location tags containing the coordinate information of the acquisition location of the laboratory environmental data in physical space; assign equipment identification tags to equipment operation data, the equipment identification tags containing the equipment number to which the equipment operation data belongs; Assign model region labels to the building models in the digital twin model. The model region labels contain the coordinate range information of the corresponding building in the physical space. Assign equipment number labels to the equipment models. The equipment number labels contain the number information of the corresponding equipment in the equipment models. Based on the model area label and the data collection location label, the coordinate range of the corresponding building in the physical space of the building model is matched with the coordinates of the collection location of the laboratory environment data in the physical space, and the matched laboratory environment data is associated with the building model. Based on the device identification label and the device number label, the corresponding device number of the device model is matched with the device number to which the device operation data belongs, and the matched device operation data is associated with the device model.
[0008] Furthermore, the simulation software is PSMODEL.
[0009] Furthermore, in the simulation experiment module, the specific method for conducting simulation experiments based on the laboratory environment data associated with the building model and the equipment operation data associated with the equipment model, combined with simulation software, is as follows: In PSMODEL, the functional areas of the laboratory are built into corresponding simulation areas and the corresponding laboratory environment data is bound to them. The equipment is built into corresponding simulation elements and the corresponding equipment operation data is bound to them. Based on the simulation areas and simulation elements, simulation scenarios and simulation parameters are set to conduct simulation experiments and obtain simulation results.
[0010] Furthermore, it also includes: an experimental project management module, used to establish electronic ledgers using text management software based on the simulation experiment process and results.
[0011] Furthermore, in the experimental project management module, the specific method for establishing an electronic ledger using text management software based on the simulation experiment process and results is as follows: An electronic ledger is obtained by recording and merging simulation basic information, data source information, simulation software parameters, and simulation experiment results using text management software. The simulation basic information includes the simulation experiment name, simulation objective, and simulation experiment date. The data source information includes laboratory environment data and equipment operation data. The simulation software parameters include the simulation scenario and simulation parameters. The simulation experiment results include the original results output by the simulation software, the conclusions of the original results, and anomaly records.
[0012] A visualization experiment method, comprising: A digital twin model of the laboratory physical space is constructed using the digital twin method. The digital twin model includes an architectural model and an equipment model. Based on a data association mechanism, laboratory environmental data is associated with the architectural model, and equipment operation data is associated with the equipment model. Simulation experiments are conducted using laboratory environment data associated with the building model and equipment operation data associated with the equipment model, combined with simulation software.
[0013] A computer program product includes a computer program / instructions that, when executed by a processor, implement the above-described visualization experiment method.
[0014] The beneficial effects of this invention are as follows: 1. By using laser scanning, a digital twin model matching the physical space of the laboratory is established, solving the problem of low accuracy in traditional modeling and consolidating the foundation for visual management.
[0015] 2. The tag matching mechanism binds environmental and equipment data with digital models, enabling intuitive data presentation, breaking down data silos, replacing manual inspections, and reducing the risk of equipment damage.
[0016] 3. Adapt to simulation software to build simulation scenarios that fit actual working conditions. The simulation results have small errors compared with physical experiments, which can verify the solution in advance and reduce the cost of trial and error in physical experiments and equipment wear and tear.
[0017] 4. By automatically establishing electronic ledgers that cover the entire simulation process, experiments can be traced and reproduced, solving the problem of fragmented traditional management. Attached Figure Description
[0018] Figure 1 This is a system block diagram of the present invention. Detailed Implementation
[0019] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.
[0020] Definitions: Digital twin: A technical method that uses the construction of precise digital models of physical entities, combined with real-time data interaction and simulation analysis, to achieve state mapping, dynamic monitoring, and simulation prediction of physical entities. Its core is to establish a two-way linkage between the physical and digital worlds, allowing the digital model to become a virtual mirror of the physical entity. This not only reflects the operational status of the physical entity in real time but also optimizes its operations and decisions through digital simulation.
[0021] Example 1 A visual laboratory system, reference Figure 1 ,include: The digital twin model construction module is used to construct a digital twin model of the laboratory physical space using the digital twin method. The digital twin model includes a building model and an equipment model. Based on the data association mechanism, laboratory environmental data is associated with the building model and equipment operation data is associated with the equipment model. The simulation experiment module is used to conduct simulation experiments based on the laboratory environment data associated with the building model and the equipment operation data associated with the equipment model, combined with simulation software. The experiment project management module is used to create electronic ledgers using word processing software based on the simulation experiment process and results.
[0022] By binding the physical laboratory space with data through digital twins, a two-way mapping between the virtual and physical worlds is achieved. The digital model can reflect the real-time status of the physical laboratory, solving the problem that traditional laboratories can only be viewed on-site and cannot be dynamically monitored remotely. By linking data and simulation software, experimental scenarios can be simulated in advance in the digital space, avoiding equipment damage or experimental failures caused by trial and error on physical equipment, thus reducing experimental risks and costs.
[0023] As a preferred embodiment, the specific method for constructing a digital twin model of the laboratory physical space using the digital twin method in the digital twin model construction module is as follows: A 3D point cloud data of the current physical space of the laboratory is collected by a 3D laser scanner installed in the laboratory. The 3D point cloud data is used as the basic data source for the digital twin to construct building models and equipment models. Based on the coordinate information in the 3D point cloud data, the equipment model is deployed to the corresponding physical location of the building model to form a digital twin model that is consistent with the physical space of the laboratory.
[0024] 3D laser scanning can acquire point cloud data with millimeter-level or even higher precision. Compared with manual modeling or CAD drawing modeling, it can accurately reproduce the size and layout of the laboratory's physical space, ensuring that the digital model matches the laboratory.
[0025] The specific method for constructing building and equipment models using the aforementioned 3D point cloud data as the basic data source for digital twins is as follows: After preprocessing the 3D point cloud data, the preprocessed 3D point cloud data is segmented based on geometric features to obtain building point clouds and equipment point clouds. The ground point cloud and wall point cloud in the building point cloud are then fitted with planes to generate ground models and wall models. That is, by solving the optimal plane equations of the ground point cloud and wall point cloud, in the form of ax + by + cz + d = 0, where a is the x-axis coefficient, b is the y-axis coefficient, c is the z-axis coefficient, and d is a constant. a, b, c, and d are all obtained through fitting. x, y, and z are the horizontal coordinate, vertical coordinate, and height coordinate in the optimal plane equation, respectively. The core parameters such as the spatial position and tilt angle of the ground and wall are determined. Based on the solved core parameters such as the spatial position and tilt angle of the ground and wall, a ground model and a wall model that are consistent with the actual ground and wall in terms of size and spatial posture are constructed.
[0026] Based on the edge point normal vector mutation identification, the rectangular contours of doors and windows and columns are extracted from the point clouds of buildings. The rectangular contours of doors and windows and columns are stretched vertically to the corresponding height to generate door and window models and column models. That is, the point cloud normal vectors of door and window and column point clouds are calculated to obtain the normal vector distribution of door and window and column point clouds. The normal vectors of adjacent points are compared. If the angle between the normal vectors of two points exceeds a preset threshold, it is determined to be an edge point. All edge points are filtered out, and the edge points of the same door / window / column are clustered and sorted by spatial coordinates to form a continuous edge point sequence. Rectangular feature matching is performed on the sorted edge point sequence to extract the rectangular contours that conform to the geometric features of doors / windows / columns.
[0027] The building model is obtained by merging the ground model, wall model, door and window model, and column model.
[0028] The device model is generated by Poisson reconstruction and / or moving least squares method from the device point cloud. If Poisson reconstruction is used, this method is suitable for devices with complex curved surfaces. The core is to generate a continuous surface through an implicit function zero isosurface. The steps are as follows: construct an octree to divide the space where the device point cloud is located into layers, balancing computational accuracy and efficiency; construct an indicator function based on the point cloud normal vector information; solve the Poisson equation to obtain a continuous implicit function; extract the zero isosurface from the implicit function; this surface is the 3D surface contour of the device, ultimately generating a complete device surface model. This is suitable for devices with complex shapes and many curved surfaces, such as the outer shell of experimental instruments. If moving least squares method is used, this is suitable for devices with smooth surfaces. The core is to stitch together the local fitted surfaces into a complete model. The steps are as follows: for each device point, define its surrounding local neighborhood; within each local neighborhood, construct a weighted least squares function to fit the local smooth surface of that region; traverse the local neighborhoods of all points, and seamlessly stitch together the local surfaces to form a complete device model. This is suitable for devices with relatively smooth surfaces where details need to be preserved, such as device bases and control panels.
[0029] The ground and walls are fitted with planes to fit their regular geometric features, avoiding redundant calculations. Doors, windows, and columns are identified by the mutation of normal vectors, and rectangular features are accurately extracted before being stretched to generate models, ensuring that the details of the architectural model are consistent with reality. Complex curved surface equipment is reconstructed using Poisson, which can generate continuous and smooth curved surface models. Smooth surface equipment is constructed using the moving least squares method, balancing smoothness and detail preservation.
[0030] As a preferred implementation, the specific method for linking laboratory environmental data to the building model and equipment operation data to the equipment model in the digital twin model construction module according to the data association mechanism is as follows: Assign data acquisition location tags to laboratory environmental data, the data acquisition location tags containing the coordinate information of the acquisition location of the laboratory environmental data in physical space; assign equipment identification tags to equipment operation data, the equipment identification tags containing the equipment number to which the equipment operation data belongs; Assign model region labels to the building models in the digital twin model. The model region labels contain the coordinate range information of the corresponding building in the physical space. Assign equipment number labels to the equipment models. The equipment number labels contain the number information of the corresponding equipment in the equipment models. Based on the model area label and the data collection location label, the coordinate range of the corresponding building in the physical space of the building model is matched with the coordinates of the collection location of the laboratory environment data in the physical space, and the matched laboratory environment data is associated with the building model. Based on the device identification label and the device number label, the corresponding device number of the device model is matched with the device number to which the device operation data belongs, and the matched device operation data is associated with the device model.
[0031] Traditional laboratory data is often stored in tabular form, which cannot be linked to digital models. This makes it difficult to identify which area or equipment the data corresponds to. By using tag matching, environmental data can be accurately linked to specific areas of the building, and equipment data can be linked to specific equipment models, thus achieving data visualization.
[0032] As a preferred embodiment, the simulation software is PSMODEL. In the simulation experiment module, the specific method for conducting simulation experiments based on the laboratory environment data associated with the building model and the equipment operation data associated with the equipment model, combined with the simulation software, is as follows: In PSMODEL, the functional areas of the laboratory are built into corresponding simulation areas and bound to the corresponding laboratory environment data. The equipment is built into corresponding simulation components and bound to the corresponding equipment operation data. Based on the simulation areas and simulation components, the simulation scene and simulation parameters are set to conduct simulation experiments and obtain simulation results. For example, click on the menu bar Simulation, then Simulation Parameter Settings. In the Algorithm Selection drop-down box, select the Implicit Trapezoidal Method. Enter 2μs in "Electromagnetic Transient Step". The electromechanical transient step is set to the default cycle level (e.g., 20ms). Set the total simulation time (e.g., 10s). Then click on the menu bar Simulation, then Start Hybrid Simulation.
[0033] PSMODEL focuses on process simulation and multi-physical quantity linkage, which can better integrate laboratory environmental data and equipment operation data, solving the problem that general simulation software cannot fit the complex laboratory scene and that the simulation results deviate greatly from reality. It maps laboratory functional areas (such as operation area and power distribution area) to simulation areas and equipment to simulation components, and then binds real data to ensure that the simulation scene is consistent with the functional logic and data status of the physical laboratory.
[0034] As a preferred implementation, the specific method for establishing an electronic ledger using text management software in the experimental project management module, based on the simulation experiment process and results, is as follows: Use word processing software (such as Excel) to record and merge simulation basic information, data source information, simulation software parameters, and simulation experiment results to obtain an electronic ledger. The simulation basic information includes the simulation experiment name, simulation objective, and simulation experiment date. The data source information includes laboratory environment data and equipment operation data. The simulation software parameters include the simulation scenario and simulation parameters. The simulation experiment results include the original results output by the simulation software, the conclusions of the original results, and anomaly records.
[0035] Traditional laboratories often use paper ledgers or scattered spreadsheets, which cannot be integrated. When searching for simulation data sources, process parameters, and results, it is necessary to cross multiple files. This module incorporates the entire process information into the electronic ledger, improving the efficiency of searching and archiving.
[0036] Example 2 A visualization experiment method, comprising: A digital twin model of the laboratory physical space is constructed using the digital twin method. The digital twin model includes an architectural model and an equipment model. Based on a data association mechanism, laboratory environmental data is associated with the architectural model, and equipment operation data is associated with the equipment model. Simulation experiments are conducted using laboratory environment data associated with the building model and equipment operation data associated with the equipment model, combined with simulation software. Based on the simulation experiment process and results, an electronic ledger was established using text management software.
[0037] Example 3 A computer program product includes a computer program / instructions that, when executed by a processor, implement the visualization experiment method in Embodiment 2.
[0038] The contents not described in detail in this specification are prior art known to those skilled in the art. Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.
[0039] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0040] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0041] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the scope of protection of the pending claims of the invention.
Claims
1. A visual laboratory system, characterized in that, include: The digital twin model construction module is used to construct a digital twin model of the laboratory physical space using the digital twin method. The digital twin model includes an architectural model and an equipment model. Based on the data association mechanism, laboratory environmental data is associated with the architectural model, and equipment operation data is associated with the equipment model. The simulation experiment module is used to conduct simulation experiments based on laboratory environment data associated with the building model and equipment operation data associated with the equipment model, combined with simulation software.
2. The visualization laboratory system according to claim 1, characterized in that, The specific method for constructing a digital twin model of the laboratory physical space using the digital twin method in the digital twin model construction module is as follows: A 3D point cloud data of the current physical space of the laboratory is collected by a 3D laser scanner installed in the laboratory. The 3D point cloud data is used as the basic data source for the digital twin to construct building models and equipment models. Based on the coordinate information in the 3D point cloud data, the equipment model is deployed to the corresponding physical location of the building model to form a digital twin model that is consistent with the physical space of the laboratory.
3. The visualization laboratory system according to claim 2, characterized in that, The specific method for constructing building and equipment models using the aforementioned 3D point cloud data as the basic data source for digital twins is as follows: After preprocessing the 3D point cloud data, the preprocessed 3D point cloud data is segmented based on geometric features to obtain building point clouds and equipment point clouds. The ground point cloud and wall point cloud in the building point cloud are fitted with planes to generate ground models and wall models. The door and window point cloud and column point cloud in the building point cloud are extracted based on the normal vector mutation recognition of edge points to extract the rectangular outlines of doors and windows and columns. The rectangular outlines of doors and windows and columns are stretched vertically to the corresponding height to generate door and window models and column models. The ground model, wall model, door and window model and column model are merged to obtain the building model. The equipment point cloud is reconstructed using Poisson reconstruction and / or moving least squares method to generate equipment models.
4. The visualization laboratory system according to claim 1, characterized in that, In the digital twin model construction module, the specific method for associating laboratory environmental data with the building model and equipment operation data with the equipment model based on the data association mechanism is as follows: Assign data acquisition location tags to laboratory environmental data, the data acquisition location tags containing the coordinate information of the acquisition location of the laboratory environmental data in physical space; assign equipment identification tags to equipment operation data, the equipment identification tags containing the equipment number to which the equipment operation data belongs; Assign model region labels to the building models in the digital twin model. The model region labels contain the coordinate range information of the corresponding building in the physical space. Assign equipment number labels to the equipment models. The equipment number labels contain the number information of the corresponding equipment in the equipment models. Based on the model area label and the data collection location label, the coordinate range of the corresponding building in the physical space of the building model is matched with the coordinates of the collection location of the laboratory environment data in the physical space, and the matched laboratory environment data is associated with the building model. Based on the device identification label and the device number label, the corresponding device number of the device model is matched with the device number to which the device operation data belongs, and the matched device operation data is associated with the device model.
5. The visualization laboratory system according to claim 1, characterized in that: The simulation software is PSMODEL.
6. The visualization laboratory system according to claim 5, characterized in that, In the simulation experiment module, the specific method for conducting simulation experiments based on the laboratory environment data associated with the building model and the equipment operation data associated with the equipment model, combined with simulation software, is as follows: In PSMODEL, the functional areas of the laboratory are built into corresponding simulation areas and the corresponding laboratory environment data is bound to them. The equipment is built into corresponding simulation elements and the corresponding equipment operation data is bound to them. Based on the simulation areas and simulation elements, simulation scenarios and simulation parameters are set to conduct simulation experiments and obtain simulation results.
7. The visualization laboratory system according to claim 6, characterized in that, Also includes: The experiment project management module is used to create electronic ledgers using word processing software based on the simulation experiment process and results.
8. The visualization laboratory system according to claim 7, characterized in that, In the experimental project management module, the specific method for establishing an electronic ledger using text management software based on the simulation experiment process and results is as follows: An electronic ledger is obtained by recording and merging simulation basic information, data source information, simulation software parameters, and simulation experiment results using text management software. The simulation basic information includes the simulation experiment name, simulation objective, and simulation experiment date. The data source information includes laboratory environment data and equipment operation data. The simulation software parameters include the simulation scenario and simulation parameters. The simulation experiment results include the original results output by the simulation software, the conclusions of the original results, and anomaly records.
9. A visualization experimental method, characterized in that, include: A digital twin model of the laboratory physical space is constructed using the digital twin method. The digital twin model includes an architectural model and an equipment model. Based on a data association mechanism, laboratory environmental data is associated with the architectural model, and equipment operation data is associated with the equipment model. Simulation experiments are conducted using laboratory environment data associated with the building model and equipment operation data associated with the equipment model, combined with simulation software.
10. A computer program product, characterized in that, It includes a computer program / instruction that, when executed by a processor, implements the visualization experimental method of claim 9.