Multi-information perception and fusion imaging system in large-scale complex test model

Abstract

The invention relates to a multi-information perception and fusion imaging system in a large-scale complex test model, and relates to the field of model test information monitoring. The multi-information sensing system is used for acquiring multi-physical-quantity information of a temperature field, a humidity field, a seepage field, a stress field and a fracture field in a model by using various monitoring technologies such as optical fibers, electromagnetism, ultrasound and acoustic emission; and the information fusion imaging system is used for uploading the monitoring data to a cloud platform database in a unified manner, fusing the monitoring data generated in a model test process to a three-dimensional model for accurate expression of a spatial position, and realizing visualization and transparency of the monitoring data and comparative analysis and mutual verification of various physical parameters. Through the technology, the coupling influence rule of multi-information and the occurrence mechanism of various disasters can be better explored by better utilizing a model test.

Description

Technical Field

[0001] This invention relates to the field of model experiment information monitoring, specifically a multi-dimensional information perception and fusion imaging system for large-scale complex experimental models. Background Technology

[0002] Physical simulation is a method of simulating real physical processes through laboratory physical experiments. It places a scaled-down model of the actual terrain physics within the experimental body and, based on satisfying basic similarity conditions (including geometric, kinematic, thermal, dynamic, and boundary condition similarity), simulates the main characteristics of the real process. Compared to field experiments, physical simulation experiments are easier to control and repeat, save manpower and resources, and allow for more comprehensive and systematic experiments.

[0003] The experimental data of multiple physical quantities obtained in physical simulation experiments are crucial to the success or failure of the experiment and are also essential for subsequent analysis of experimental phenomena and the proposal of new mechanisms. However, physical model experiments often involve complex geological environments with high ground stress, high osmotic pressure, high ground temperature, and water and gas content. They also often need to simulate complex dynamic disturbance loads with multiple strain rates, such as excavation unloading, fault rupture, and blasting vibration, which poses great difficulties for the acquisition of multi-dimensional information within the experimental model.

[0004] Currently, extensive research has been conducted on acquiring experimental data within experimental models under complex conditions, resulting in the innovation of various monitoring devices, technologies, and methods, such as: Chinese patent CN112762975A proposes a sealed acquisition system and method for multi-physical quantity information of model tests under high pressure environment. The system mainly includes a multi-physical quantity sensing unit, which is embedded in the test material under high pressure environment; an amplification unit, which is connected to the multi-physical quantity sensing unit through a first signal line extending out of the test material; and a processing unit, which is located outside the model test device and is connected to the amplification unit through a second signal line.

[0005] Chinese patent CN110725273A proposes a device and method for monitoring the foundation scour process and rapidly acquiring terrain in model tests. This involves embedding two or more elastic membranes around the building foundation on an opaque base plate of a test tank. Two symmetrical small laser emitters are installed on the bottom surface of each elastic membrane. An equal number of reflective spheres are installed on a measurement platform, each corresponding to an elastic membrane, with its center directly below the center of its corresponding elastic membrane. A scaled screen is installed on both sides of each reflective sphere, and each scaled screen is connected to a computer via a data acquisition device.

[0006] Chinese patent CN110954053A proposes a test platform for monitoring displacement inside the surrounding rock of a tunnel model. The crown displacement monitoring device and the sidewall radial displacement monitoring device are both rod devices vertically embedded in the soil, with their upper parts exposed on the soil surface. The bottom of the crown displacement monitoring device is close to the top of the dynamic tunnel excavation model, while the side measuring points of the sidewall radial displacement monitoring device are close to the sidewall of the dynamic tunnel excavation model.

[0007] In summary, existing multi-source information sensing technologies in model experiments each have their own characteristics, but their main limitations are as follows: (1) The types of physical quantities obtained are limited, which is not conducive to the coupled analysis of experimental phenomena and results; (2) Only key experimental data can be obtained, resulting in limited and one-sided information; (3) The experimental data are highly independent, making it impossible to effectively fuse, jointly express, and dynamically present the data; (4) The sensors and monitoring technologies used cannot test complex gas-solid coupling environments. Summary of the Invention

[0008] To address at least one of the technical problems in the background art, the present invention provides a multi-dimensional information perception and fusion imaging system for large-scale complex experimental models. This technology enables better utilization of model experiments to explore the coupling influence of multi-dimensional information and the occurrence mechanism of various disasters.

[0009] To achieve the above objectives, the present invention provides a multi-dimensional information perception and fusion imaging system for large-scale complex experimental models, comprising: Multi-dimensional information sensing system: It uses a variety of monitoring technologies such as fiber optics, electromagnetics, ultrasound, and acoustic emission to obtain information on multiple physical quantities inside the model, including temperature field, humidity field, seepage field, stress field, and fracture field. Information fusion imaging system: It uploads monitoring data to the cloud platform database in a unified manner, and integrates the monitoring data generated during the model test into the three-dimensional model to accurately express the spatial position, so as to realize the intuitiveness and transparency of monitoring data, as well as the comparative analysis and mutual verification of various physical parameters.

[0010] Furthermore, the multi-source information sensing system includes an optical fiber monitoring unit, an electromagnetic monitoring unit, an ultrasonic monitoring unit, and an acoustic emission monitoring unit. The optical fiber monitoring unit is embedded in the test model, and the optical fiber monitoring unit is arranged in a mesh on the top of the simulated tunnel. The electromagnetic monitoring unit is arranged around the simulated tunnel. The ultrasonic monitoring unit and the acoustic emission monitoring unit are arranged outside the test model. The fiber optic monitoring unit monitors the temperature field and seepage field through fiber optic sensors; The electromagnetic monitoring unit monitors the internal stress field of the test model through electromagnetic radiation equipment; The ultrasonic monitoring unit monitors the fracture field inside the test model using an ultrasonic probe. The acoustic emission monitoring unit monitors the fracture field and seepage field inside the test model through an acoustic emission probe.

[0011] Furthermore, the ultrasonic monitoring unit is arranged on the top of the test model, with multiple probes arranged in an array; the acoustic emission monitoring unit is arranged on multiple surfaces of the test model, thereby achieving three-dimensional detection.

[0012] Furthermore, the information fusion imaging system includes a data analysis unit and a three-dimensional imaging unit; wherein, the data analysis unit uploads the test data monitored by the multi-source information sensing system to the cloud platform database in a unified manner, and realizes the comparative analysis and mutual verification of multiple physical parameters of the same monitoring object by setting the monitoring object and control indicators; the three-dimensional imaging unit fuses the test data of multiple physical quantities obtained by the multi-source information sensing system into a three-dimensional model to accurately express the spatial position, thereby performing three-dimensional visualization imaging of the test data.

[0013] Furthermore, the 3D imaging unit includes a web-based web page system, a database storage and management system, and a mobile app. The web-based web page system includes a model experiment visualization module and a multi-functional operation module, used for managing model structure and attributes, analyzing, querying, and displaying model experiment data, and representing the 3D scene of groundwater migration in coal seam mining. The database storage and management system includes data receiving, classification, filtering, and retrieval functions, used for unified management of model monitoring data. The mobile app includes modules for model overview, data query, work status, and mobile meeting, used for real-time querying of remote model information, recording of daily work, and remote conferencing.

[0014] The beneficial effects of this invention are as follows: (1) Multiple monitoring technologies such as optical fiber, electromagnetic, ultrasonic, and acoustic emission are used to obtain information on multiple physical quantities such as temperature field, humidity field, seepage field, stress field, and crack field inside the model.

[0015] (2) The monitoring data generated during the model test can be integrated into the three-dimensional model to accurately express the spatial location, thus realizing the intuitiveness and transparency of the monitoring data.

[0016] (3) Monitoring data can be uploaded to the cloud platform database in a unified manner. By setting monitoring objects and control indicators, comparative analysis and mutual verification of multiple physical parameters of the same monitoring object can be realized. Attached Figure Description

[0017] Figure 1 This is a three-dimensional diagram of the multi-element information sensing system of Embodiment 1 of the present invention; Figure 2 This is a structural block diagram of the overall information perception and fusion imaging system of Embodiment 1 of the present invention; Figure 3 This is a structural block diagram of the information fusion imaging system of Embodiment 1 of the present invention.

[0018] Among them, 1-test model, 2-simulated roadway, 3-simulated coal seam, 4-fiber optic monitoring unit, 5-electromagnetic monitoring unit, 6-ultrasonic monitoring unit, 7-acoustic emission monitoring unit. Detailed Implementation

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0022] Furthermore, some of the aforementioned terms, besides indicating location or positional relationships, may also have other meanings. For example, the term "above" may, in certain circumstances, indicate a dependency or connection. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0023] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linking," and "socketing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral structure; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0024] To achieve the above objectives, this invention provides a multi-dimensional information sensing and fusion imaging system for large-scale complex experimental models, comprising: Multi-dimensional information sensing system: It uses a variety of monitoring technologies such as fiber optics, electromagnetics, ultrasound, and acoustic emission to obtain information on multiple physical quantities inside the model, including temperature field, humidity field, seepage field, stress field, and fracture field. Information fusion imaging system: It uploads monitoring data to the cloud platform database in a unified manner, and integrates the monitoring data generated during the model test into the three-dimensional model to accurately express the spatial position, so as to realize the intuitiveness and transparency of monitoring data, as well as the comparative analysis and mutual verification of various physical parameters.

[0025] This invention provides a multi-dimensional information perception and fusion imaging technology for large-scale complex experimental models, which can perform line and surface monitoring of multi-dimensional information inside large-scale experimental models under gas-solid coupling conditions, and perform fusion and visualization imaging of experimental data.

[0026] The multi-dimensional information sensing system includes fiber optic monitoring units, electromagnetic monitoring units, ultrasonic monitoring units, and acoustic emission monitoring units. The fiber optic monitoring units are embedded in the test model and arranged in a mesh pattern on the top of the simulated tunnel. The electromagnetic monitoring units are arranged around the perimeter of the simulated tunnel. The ultrasonic and acoustic emission monitoring units are arranged on the outside of the test model. The ultrasonic monitoring units, with multiple probes arranged in an array on the top of the test model, are arranged on multiple surfaces of the test model, thus achieving three-dimensional detection. Each of the four monitoring units has its own characteristics, and their monitoring devices are coupled and arranged inside or on the surface of the test model to monitor different physical quantities, thereby achieving three-dimensional monitoring of the internal information of the test model.

[0027] The fiber optic monitoring unit monitors the temperature, humidity, and seepage fields using fiber optic sensors. Fiber optics are extremely sensitive sensors, providing excellent monitoring of temperature and strain data. Since the temperature change process in the model is related to the water content, the seepage field can be characterized by changes in temperature and water content, allowing for real-time monitoring of fluid transport. Several DTS temperature-measuring fiber optic sensors are deployed at the water seepage locations in the model, with one end connected to a photoelectric demodulator to monitor the temperature field in the model in real time. For real-time monitoring of water content, this invention coats a layer of polyimide tens of micrometers thick onto a fiber Bragg grating. When the polyimide absorbs water from the model, it expands, causing a change in the axial stress of the fiber Bragg grating. This causes a wavelength shift in the grating's reflection peak; by determining the wavelength position, the humidity information at the current location can be obtained.

[0028] The electromagnetic monitoring unit monitors the internal stress field of the model using electromagnetic radiation equipment. Stress field monitoring is achieved by acquiring the electromagnetic radiation characteristics of similar materials used in the fabrication of the experimental model under different stresses. The ultrasonic monitoring unit monitors the fracture field inside the test model using ultrasonic probes. Both the ultrasonic transmitting and receiving probes are arranged in an array. This array enhances the transmitted energy to increase the penetration depth of the sound waves and uses phased-array focusing to adjust the direction and focus of the sound beam. During testing, the probes are positioned on either side of the model, transmitting from one side and receiving from the other. The probes are then moved to different locations to transmit and receive signals until the entire testing surface is covered, obtaining ultrasonic monitoring data. This data allows for the acquisition of fracture field information such as crack orientation, the shape of water- and gas-bearing pores, and the interfaces between various media.

[0029] The acoustic emission monitoring unit monitors the fracture field and seepage field inside the test model using acoustic emission probes. During the test, an array of acoustic emission sensors is deployed inside and on the surface of the model. Based on a precise imaging method of the model's acoustic wave velocity, the acoustic emission source is accurately located, thereby achieving global monitoring of the fracture field and seepage field.

[0030] The information fusion imaging system includes a data analysis unit and a three-dimensional imaging unit. The data analysis unit uploads the experimental data monitored by the multi-source information sensing system to the cloud platform database. By setting the monitoring object and control indicators, it realizes the comparative analysis and mutual verification of multiple physical parameters of the same monitoring object. The three-dimensional imaging unit integrates the experimental data of multiple physical quantities obtained by the multi-source information sensing system into a three-dimensional model to accurately express the spatial position, thereby performing three-dimensional visualization imaging of the experimental data.

[0031] The data analysis unit achieves real-time reception and storage of various physical parameter data through a unified database design. Data preprocessing is achieved by setting up filtering algorithms for monitoring data. Then, the 3D model of the model experiment is imported into the cloud platform system to determine the spatial location of each sensor within the model. By fusing the monitoring data with the actual sensor locations, the real-time dynamics of the sensor data for a specific physical parameter in the model experiment are visually displayed. Data acquired from various physical parameters is connected to a switch, forming a local area network (LAN). Within the LAN, the mainstream MQTT protocol is used for data forwarding and communication. MQTT control messages and embedded application data integrity checks ensure correct data transmission and prevent tampering. Different information is obtained based on subscriptions to different topics. The backend service uses a Java program to analyze and process data from different topics, and can handle the synchronous operation of large amounts of data. To achieve effective fusion of multiple types of monitoring data, secondary filtering is implemented by setting different floating percentages to improve data value and comparability. Classification management of various physical parameters is achieved by adding sensor coordinate tables and monitoring type tables. Furthermore, by connecting multiple types of physical parameter monitoring data to the cloud platform, and by setting the analysis object and control parameters, comparative analysis and mutual verification of multiple physical parameters of the same monitoring object can be achieved.

[0032] The 3D imaging unit comprises a web-based web page system, a database storage and management system, and a mobile app. The web page system includes a model experiment visualization module and a multi-functional operation module for managing model structure and attributes, analyzing, querying, and displaying model experiment data, and representing the 3D scene of groundwater migration in coal seam mining. The database storage and management system includes functions such as data reception, classification, filtering, and retrieval for unified management of model monitoring data. The mobile app includes modules for model overview, data query, work status, and mobile meetings, for real-time querying of remote model information, recording of daily work, and remote conferencing. The web page is primarily implemented using a React framework, employing local Revit modeling software to create a complex model of the experimental device. A particle system in Three.js renders the model blue to simulate groundwater; particle velocity simulates water flow rate, and particle density simulates water volume. Data from distributed fiber optic measurements is used to control the particles for dynamic display.

[0033] This invention utilizes various monitoring technologies such as optical fiber, electromagnetic, ultrasonic, and acoustic emission to obtain information on multiple physical quantities within the model, including temperature field, humidity field, seepage field, stress field, and fracture field. It can integrate monitoring data generated during model testing into a three-dimensional model for accurate spatial representation, making the monitoring data more intuitive and transparent. Furthermore, it can upload the monitoring data to a cloud platform database, and by setting monitoring objects and control indicators, it can achieve comparative analysis and mutual verification of multiple physical parameters of the same monitoring object.

[0034] Example 1

[0035] This embodiment discloses a multi-dimensional information perception and fusion imaging technology for a large-scale complex test model in a simulated coal and gas outburst test during roadway excavation and coal exposure.

[0036] like Figure 1-2 As shown, the test model in this embodiment mainly consists of roof and floor rock strata and simulated coal seam 3 similar materials. The roof and floor rock strata are made using the method proposed in Chinese invention patent CN201911340783.7 "A similar material for ultra-low permeability and gas tightness rock strata and its preparation method and application". The simulated coal seam 3 is made using the method proposed in the paper "Wang Hanpeng, Zhang Qinghe, Yuan Liang, et al. Development of similar materials for gas-bearing coal and its outstanding experimental application [J]. Rock and Soil Mechanics, 2015(06):1676-1682". Thus, a gas-solid coupling test model 1 that can achieve coalbed gas sealing is formed.

[0037] The specific experimental objective is to simulate a high-gas coal seam in a coal mine by filling a simulated coal seam 3 with high-pressure gas. Due to the low permeability of the similar roof and floor strata, the gas can be sealed within the simulated coal seam 3, thus realistically simulating the gas occurrence conditions in a real-world coal mine. Then, a simulated roadway 2 is excavated using a tunneling device to gradually expose the simulated coal seam 3. During the excavation of the simulated roadway 2, a coal and gas outburst disaster is induced, thus simulating a coal and gas outburst accident in a real-world coal mine. By real-time monitoring of the diverse information generated during the coal and gas outburst induced by the excavation of the simulated roadway 2, a better understanding of the coal and gas outburst mechanism can be achieved, guiding coal and gas outburst prevention and control efforts.

[0038] During the fabrication of test model 1, fiber optic monitoring units 4 and electromagnetic monitoring units 5 are pre-embedded. The fiber optic monitoring units 4 are arranged in a mesh on the top of the simulated tunnel 2, and the electromagnetic monitoring units 5 are arranged around the tunnel. After the test model 1 is fabricated, ultrasonic monitoring units 6 and acoustic emission monitoring units 7 are arranged on the outside of test model 1. The ultrasonic monitoring units 6 are arranged on the top of test model 1 with multiple probes arranged in an array, and the acoustic emission monitoring units 7 are arranged on multiple surfaces of test model 1, thereby achieving three-dimensional detection.

[0039] The fiber optic monitoring unit 4 monitors the temperature and seepage fields using fiber optic sensors. Fiber optics are extremely sensitive sensors, providing excellent monitoring of temperature and strain data. Several DTS temperature-measuring fiber optic sensors are deployed at key locations on the experimental model 1, with one end connected to a photoelectric demodulator to monitor the temperature and gas seepage fields in the model in real time.

[0040] Electromagnetic monitoring unit 5 monitors the internal stress field of test model 1 using electromagnetic radiation equipment. Stress field monitoring is achieved by acquiring the electromagnetic radiation characteristics of similar materials used in the fabrication of test model 1 under different stress conditions. The ultrasonic monitoring unit 6 monitors the fracture field inside the test model 1 using ultrasonic probes. Both the ultrasonic transmitting and receiving probes are arranged in an array to enhance the transmitted energy and increase the sound wave penetration depth, while phased-array focusing adjusts the direction and focus of the sound beam. By transmitting and receiving signals at different locations until the entire detection surface is covered, ultrasonic monitoring data is obtained, thereby acquiring information about the fracture field, such as the crack orientation and the interfaces between various media.

[0041] The acoustic emission monitoring unit 7 monitors the fracture field and seepage field inside the test model 1 through an acoustic emission probe. Based on the precise imaging method of the model's acoustic wave velocity, the acoustic emission source is accurately located, thereby achieving global monitoring of the fracture field and seepage field.

[0042] Through the above sensor arrangement, the temperature field, humidity field, seepage field and other information inside the test model 1 are obtained through the fiber optic monitoring unit 4, the stress field inside the test model 1 is obtained through the electromagnetic monitoring unit 5, the fracture field inside the test model 1 is obtained through the ultrasonic monitoring unit 6, and the seepage field and fracture field inside the test model 1 are obtained through the acoustic emission monitoring unit 7. Thus, the acquisition of multi-dimensional information inside the large-scale test model under the gas-solid coupling condition is realized.

[0043] like Figure 2-3As shown, after acquiring multi-source information, the information is first uploaded to the cloud platform database of the data analysis unit. The data analysis unit, through a unified database storage design, achieves real-time reception and storage of data for each physical parameter. Data preprocessing is achieved by setting a filtering algorithm for the monitoring data. Then, the 3D model of the model experiment is imported into the cloud platform system to determine the spatial location of each sensor within the model. By fusing the monitoring data with the actual sensor locations, the real-time dynamic data of a specific physical parameter in the model experiment is displayed intuitively. The data acquired from each physical parameter is connected to a switch, forming a local area network (LAN). Within the LAN, the mainstream MQTT protocol is used for data forwarding. MQTT control messages and embedded application data integrity verification ensure correct data transmission and prevent tampering. Different information is acquired based on subscribed topics. The backend service uses a Java program to analyze and process data from different topics, and can simultaneously handle large volumes of data. To achieve effective fusion of multiple types of monitoring data, secondary filtering is implemented by setting different floating percentages to improve data value and comparability. Classification management of each physical parameter is achieved by adding sensor coordinate tables and monitoring type tables. Furthermore, by connecting multiple types of physical parameter monitoring data to the cloud platform, and by setting the analysis object and control parameters, comparative analysis and mutual verification of multiple physical parameters of the same monitoring object can be achieved.

[0044] The 3D imaging unit comprises a web-based web page system, a database storage and management system, and a mobile app. The web page system includes a model experiment visualization module and a multi-functional operation module for managing model structure and attributes, analyzing, querying, and displaying model experiment data, and representing the 3D scene of groundwater migration in coal seam mining. The database storage and management system includes functions such as data reception, classification, filtering, and retrieval for unified management of model monitoring data. The mobile app includes modules for model overview, data query, work status, and mobile meetings, for real-time querying of remote model information, recording of daily work, and remote conferencing. The web page is primarily implemented using a React framework, employing local Revit modeling software to create a complex model of the experimental device. A particle system in Three.js renders the model blue to simulate groundwater; particle velocity simulates water flow rate, and particle density simulates water volume. Data from distributed fiber optic measurements is used to control the particles for dynamic display.

[0045] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the technical scope of the present invention. Therefore, any minor modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A multi-dimensional information sensing and fusion imaging system for a large-scale complex experimental model, characterized in that, include: Multi-dimensional information sensing system: It uses a variety of monitoring technologies such as fiber optics, electromagnetics, ultrasound, and acoustic emission to obtain information on multiple physical quantities inside the model, including temperature field, humidity field, seepage field, stress field, and fracture field. Information fusion imaging system: It uploads monitoring data to the cloud platform database in a unified manner, and integrates the monitoring data generated during the model test into the three-dimensional model to accurately express the spatial position. This is used to realize the visualization and transparency of monitoring data, as well as the comparative analysis and mutual verification of various physical parameters.

2. The multi-dimensional information perception and fusion imaging system for a large-scale complex experimental model as described in claim 1, characterized in that, The multi-source information sensing system includes fiber optic monitoring units, electromagnetic monitoring units, ultrasonic monitoring units, and acoustic emission monitoring units. The fiber optic monitoring units are embedded in the test model and arranged in a mesh on the top of the simulated tunnel. The electromagnetic monitoring units are arranged around the simulated tunnel. The ultrasonic monitoring unit and the acoustic emission monitoring unit are arranged outside the test model; The fiber optic monitoring unit monitors the temperature field and seepage field through fiber optic sensors; The electromagnetic monitoring unit monitors the internal stress field of the test model through electromagnetic radiation equipment; The ultrasonic monitoring unit monitors the fracture field inside the test model using an ultrasonic probe. The acoustic emission monitoring unit monitors the fracture field and seepage field inside the test model through an acoustic emission probe.

3. The multi-dimensional information perception and fusion imaging system for a large-scale complex experimental model as described in claim 2, characterized in that, The ultrasonic monitoring unit is arranged on the top of the test model, with multiple probes arranged in an array; the acoustic emission monitoring unit is arranged on multiple surfaces of the test model, thereby achieving three-dimensional detection.

4. The multi-dimensional information perception and fusion imaging system for a large-scale complex experimental model as described in claim 3, characterized in that, The information fusion imaging system includes a data analysis unit and a three-dimensional imaging unit. The data analysis unit uploads the experimental data monitored by the multi-source information sensing system to the cloud platform database. By setting the monitoring object and control indicators, it realizes the comparative analysis and mutual verification of multiple physical parameters of the same monitoring object. The three-dimensional imaging unit integrates the experimental data of multiple physical quantities obtained by the multi-source information sensing system into a three-dimensional model to accurately express the spatial position, thereby performing three-dimensional visualization imaging of the experimental data.

5. The multi-dimensional information perception and fusion imaging system for a large-scale complex experimental model as described in claim 4, characterized in that, The 3D imaging unit includes a web-based web page system, a database storage and management system, and a mobile app. The web-based web page system includes a model experiment visualization module and a multi-functional operation module, used for managing model structure and attributes, analyzing, querying, and displaying model experiment data, and representing the 3D scene of groundwater migration in coal seam mining. The database storage and management system includes data receiving, classification, filtering, and retrieval functions, used for unified management of model monitoring data. The mobile app includes modules for model overview, data query, work status, and mobile meeting, used for real-time querying of remote model information, recording of daily work, and remote conferencing.

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