Monitoring Method for Identifying the Rising Path of Water Inrush Catastrophe Water Sources Based on Similarity Simulation Tests

Abstract

The present invention relates to the technical field of mine water hazard prevention and control, and discloses a method for identifying and monitoring the source and rise path of water in sudden water disasters based on similar simulation tests. The method comprises: collecting mining area data, determining the lithology and paving thickness of each rock layer in the mining area, and proportioning similar materials for each determined rock layer; and using exothermic materials as layering materials in the similar simulation tests. The method, based on similar simulation tests, enhances the responsiveness of each rock layer to temperature changes in the experimental environment by using exothermic materials in the similar simulation tests, and can more accurately reflect subtle changes in rock layer temperature during the water inrush process, thereby improving monitoring accuracy. During the water inrush monitoring process, an infrared thermal imager is used to capture real-time thermal images, which can display the real-time temperature distribution during mining, thereby reflecting the dynamic situation of the water inrush, including the temperature anomaly areas and the preliminary outline of the water inrush path.

Description

Technical Field

[0001] The present invention relates to the technical field of mine water hazard prevention and control, and in particular to a method for identifying and monitoring water source rising paths of sudden water disasters based on similar simulation tests. Background Art

[0002] As coal mining depth increases, underground pressurized water activity becomes more frequent, leading to a growing risk of water inrush from the floor during mining operations. Water inrush can not only cause direct losses such as mine flooding and equipment damage, but can also endanger the lives of underground workers. Therefore, quickly and accurately identifying and monitoring the path of water inrush during mining operations has become a key technology for coal mine safety.

[0003] Existing water inrush path monitoring technologies primarily rely on methods such as water pressure observation and borehole detection. These methods have numerous limitations, including the inability to achieve real-time monitoring, long monitoring cycles, and difficulty capturing dynamically changing water inrush paths. Furthermore, traditional monitoring methods have limited accuracy in predicting water inrush paths, making it difficult to promptly reflect subtle changes during the water inrush process.

[0004] Infrared thermal imaging technology, with its non-contact, long-distance, and real-time monitoring capabilities, is becoming an emerging tool for monitoring water inrush in mines. Infrared imaging can capture the temperature distribution of mining areas in real time and identify water inrush paths by analyzing temperature anomalies.

[0005] However, existing infrared thermal imaging monitoring methods still have some limitations, such as limited image resolution, noise interference, and the impact of uneven lighting on image clarity, making it difficult to identify water inrush paths in thermal images. Therefore, improving the quality and resolution of infrared thermal imaging images, reducing noise interference, and further enhancing the visualization of water inrush paths are of great research significance in the field of mine water hazard prevention. Summary of the Invention

[0006] To address the problems of the existing water burst path monitoring technology, such as the inability to achieve real-time monitoring, long monitoring cycles, difficulty in capturing dynamically changing water burst paths, and difficulty in timely reflecting subtle changes in the water burst process, as well as the limited image resolution, noise interference, and uneven illumination of existing infrared thermal imaging monitoring methods, which make it difficult to identify water burst paths in thermal images, the present invention is achieved through the following technical solutions: a water source riser path identification and monitoring method based on similar simulation tests, comprising:

[0007] S1. Collect mining area data, determine the lithology and paving thickness of each rock layer in the mining area, and make similar material proportions for each rock layer with determined lithology;

[0008] S2. Use exothermic materials as layering materials in similar simulation tests;

[0009] S3. Use the mining coal seam floor water inrush similarity simulation test system to lay the test materials and build a similar simulation test environment;

[0010] S4. Deploy an infrared thermal imager to measure the infrared heat of the target;

[0011] S5. During the mining process, infrared thermal imagers are used to obtain real-time thermal images and temperature values, thereby enabling preliminary identification and monitoring of the water inrush path;

[0012] S6. After the mining is completed, the measurement results are exported, the measurement data are obtained and analyzed, and the water inrush path is obtained;

[0013] S7. Compare and analyze the thermal image obtained by real-time monitoring with the path map obtained through algorithm processing to obtain detailed and accurate test results.

[0014] Furthermore, in S4, an infrared thermal imager is deployed to measure the infrared heat of the target, specifically:

[0015] S4.1. Deploy infrared thermal imagers in locations that can cover the mining impact area, fault areas, and possible water inrush paths;

[0016] S4.2. Set the measurement range and resolution of the infrared thermal imager to ensure that it can monitor local temperature changes during mining.

[0017] Furthermore, the S5 specifically includes:

[0018] S5.1. During the mining process, use an infrared thermal imager to monitor the test in real time, and obtain real-time thermal images and temperature values through its built-in conversion function;

[0019] S5.2. Real-time analysis of thermal images can be used to visualize the bottom plate water inrush path formed during the high-pressure water rise process.

[0020] Furthermore, the S5.1 specifically includes:

[0021] S5.11. The infrared thermal imager continuously scans the mining area to collect temperature data in real time.

[0022] S5.12. Infrared thermal imagers detect infrared energy non-contactly and convert it into electrical signals, which then generate visual thermal images and temperature values on the display.

[0023] Furthermore, the S5.2 specifically includes:

[0024] S5.21. In thermal images, high-pressure water flow reacts chemically with components in exothermic materials, releasing heat energy and causing localized temperature anomalies. By identifying areas of rapid temperature increase or decrease and analyzing the trajectory of the water flow, the path of the water inrush is gradually revealed in the thermal image.

[0025] S5.22. Generate a continuous sequence of thermal images at a set frequency for real-time monitoring. By comparing thermal images at different times, analyze the dynamic process of temperature changes. The expansion and direction of the water inrush path are manifested in the image as the displacement and diffusion of the temperature anomaly area.

[0026] Furthermore, the S6 specifically includes:

[0027] S6.1. After the mining is completed, the measurement results in the infrared thermal imager storage system are exported to obtain the measurement data;

[0028] S6.2. Use the TV-Retinex algorithm to process the exported image data to obtain the specific water inrush path.

[0029] Furthermore, the S6.2 processes the exported image data using the TV-Retinex algorithm, specifically:

[0030] S6.21. Preprocessing of raw image data:

[0031] Noise removal: Use Gaussian filtering or median filtering techniques to remove image noise and eliminate random temperature changes that may affect path recognition;

[0032] Contrast enhancement: adjust the image contrast through histogram equalization to enhance the overall visibility of the image and make the water inrush path more obvious in the image;

[0033] S6.22. Use the TV-Retinex algorithm combined with Retinex theory and total variation regularization technology to enhance the preprocessed image:

[0034] Use the Retinex theoretical model to perform illumination correction and color constancy processing on thermal images;

[0035] The images are further processed using a total variation regularization method to remove noise and artifacts introduced during the processing.

[0036] Furthermore, the S7 is specifically:

[0037] By comparing thermal images and processed images at different times, the dynamic changes in the speed, direction and range of the water inrush path expansion during the pressurized water diversion process are analyzed.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. This method for identifying and monitoring water source and riser paths in water inrush disasters, based on similar simulation experiments, uses exothermic materials to enhance the responsiveness of various rock formations to temperature changes within the experimental environment. This allows for more accurate reflection of subtle temperature changes during water inrush events, improving monitoring accuracy. During water inrush monitoring, infrared thermal imaging captures real-time thermal images, demonstrating the real-time temperature distribution during mining operations, particularly temperature changes in highly pressurized water flow areas. This reveals the dynamics of the water inrush, including areas of temperature anomalies and the preliminary outlines of the water inrush paths.

[0040] 2. This method for identifying and monitoring water source rise paths in flood disasters, based on similar simulation experiments, processes the derived thermal image data using the TV-Retinex algorithm after acquiring it, generating clear images of the water burst path. These processed images undergo contrast enhancement, denoising, and edge enhancement, accurately displaying the direction and temperature trends of the water burst path. The processed images not only remove noise and uneven lighting, but also highlight key details of the water burst path. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of the method for identifying and monitoring the water source rise path of a sudden flood disaster according to the present invention;

[0042] Figure 2 A histogram showing the distribution of coal seams and surrounding rocks in a similar simulation test in an embodiment of the present invention;

[0043] Figure 3 Schematic diagram showing the comparison between the infrared thermal imager and normal shooting after the excavation work of a similar simulated test working face is completed in an embodiment of the present invention;

[0044] Figure 4 This is a flow chart of the present invention using the TV-Retinex algorithm to process image data. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0046] The embodiment of the method for identifying and monitoring the water source rise path of a sudden flood disaster based on similar simulation experiments is as follows:

[0047] See also Figure 1-Figure 4 , a method for identifying and monitoring water source rise paths of sudden flood disasters based on similar simulation tests, including:

[0048] S1. Collect mining area data, determine the lithology and paving thickness of each rock layer in the mining area, and make similar material proportions for each rock layer with determined lithology;

[0049] S2. Use exothermic materials as layering materials in similar simulation tests;

[0050] S3. Use the mining coal seam floor water inrush similarity simulation test system to lay the test materials and build a similar simulation test environment;

[0051] S4. Deploy an infrared thermal imager to measure the infrared heat of the target;

[0052] S4.1. Deploy infrared thermal imagers in locations that can cover the mining impact area, fault areas, and possible water inrush paths;

[0053] S4.2. Set the measurement range and resolution of the infrared thermal imager to ensure that it can monitor local temperature changes during mining.

[0054] S5. During the mining process, infrared thermal imagers are used to obtain real-time thermal images and temperature values, thereby enabling preliminary identification and monitoring of the water inrush path;

[0055] S5.1. During the mining process, use an infrared thermal imager to monitor the test in real time, and obtain real-time thermal images and temperature values through its built-in conversion function;

[0056] S5.11. The infrared thermal imager continuously scans the mining area to collect temperature data in real time.

[0057] S5.12. Infrared thermal imagers detect infrared energy non-contactly and convert it into electrical signals, which then generate visual thermal images and temperature values on the display.

[0058] S5.2. Real-time analysis of thermal images can be used to visualize the bottom plate water inrush path formed during the high-pressure water diversion process;

[0059] S5.21. In thermal images, high-pressure water flow reacts chemically with components in exothermic materials, releasing heat energy and causing localized temperature anomalies. By identifying areas of rapid temperature increase or decrease and analyzing the trajectory of the water flow, the path of the water inrush is gradually revealed in the thermal image.

[0060] S5.22. Generate a continuous sequence of thermal images at a set frequency for real-time monitoring. By comparing thermal images at different times, analyze the dynamic process of temperature changes. The expansion and direction of the water inrush path are manifested in the image as the displacement and diffusion of the temperature anomaly area.

[0061] S6. After the mining is completed, the measurement results are exported, the measurement data are obtained and analyzed, and the water inrush path is obtained;

[0062] S6.1. After the mining is completed, the measurement results in the infrared thermal imager storage system are exported to obtain the measurement data;

[0063] S6.2. Process the exported image data using the TV-Retinex algorithm to obtain a specific water inrush path;

[0064] S6.21. Preprocessing of raw image data:

[0065] Noise removal: Use Gaussian filtering or median filtering techniques to remove image noise and eliminate random temperature changes that may affect path recognition;

[0066] Contrast enhancement: adjust the image contrast through histogram equalization to enhance the overall visibility of the image and make the water inrush path more obvious in the image;

[0067] S6.22. Use the TV-Retinex algorithm combined with Retinex theory and total variation regularization technology to enhance the preprocessed image:

[0068] Use the Retinex theoretical model to perform illumination correction and color constancy processing on thermal images;

[0069] The images are further processed using a total variation regularization method to remove noise and artifacts introduced during the processing.

[0070] S7. Compare and analyze the thermal image obtained by real-time monitoring with the path map obtained through algorithm processing to obtain detailed and accurate test results;

[0071] By comparing thermal images and processed images at different times, the dynamic changes in the speed, direction and range of the water inrush path expansion during the pressurized water diversion process are analyzed.

[0072] The specific implementation is as follows:

[0073] Based on the mining area's geological survey data, the lithology, thickness, and related parameters of each rock layer in the mining area, particularly the characteristics of the floor rock layer, are determined. Using this data, suitable analog materials are designed and formulated. The analog materials used in the experiment must not only simulate the mechanical properties of each rock layer but also reflect its response to temperature changes.

[0074] In this embodiment, the original geological data of the similarity simulation test is obtained by analyzing the geological materials of a mine in Huainan. At the same time, in order to simulate fault water inrush through the similarity test, the prepared rock layer should meet a certain geometric similarity ratio.

[0075] Geometric similarity means that the spatial dimensions of the model and the prototype are in a certain ratio. The formula is as follows:

[0076]

[0077] Among them, C1 is the geometric similarity ratio;

[0078] x', y', z' are the geometric dimensions of the prototype along the x, y, and z directions, in cm;

[0079] x", y", z" are the geometric dimensions of the model along the x, y, and z directions, in cm.

[0080] According to the effective size of the test bench used and the relative spatial position of the fault and aquifer under study, combined with the geometric similarity ratio of 1:100 obtained by the above formula, the model size of the test can be determined. Figure 2 As shown, based on the above-mentioned geometric similarity ratio of 1:100, the dimensions of each rock layer in the similar simulation test of this embodiment are obtained.

[0081] When laying the model, the water temperature and geological conditions of the mine were combined with the relevant requirements of the test. The overlying rock layer used a similar simulation material with hydrophilic properties, as shown in Table 1, and the floor rock layer used a similar simulation material with non-hydrophilic fluid-solid coupling, as shown in Table 2:

[0082] Table 1

[0083]

[0084] Table 2

[0085]

[0086] During this process, exothermic materials were selected as the layering materials in the experiment. These materials release heat during chemical reactions, simulating the heat flow conditions in actual underground environments. By incorporating exothermic materials into the experimental system, the generation of thermal anomalies during water inrush experiments in coal seam floors can be accurately simulated, providing reliable temperature change data for subsequent infrared thermal imaging monitoring.

[0087] After setting up a similar simulation experiment platform, select a suitable location to deploy the infrared thermal imager. The infrared thermal imager should be positioned to cover the entire mining area, faults, and possible water inrush paths. By setting a reasonable measurement range and resolution, accurate monitoring of temperature changes along the water inrush path is ensured. In this example, the infrared thermal imager has a resolution of 640 × 480 pixels.

[0088] During the mining process, an infrared thermal imager continuously scans the test area non-contact, collecting real-time temperature data and generating thermal images. The infrared thermal imager detects infrared radiation, converts it into electrical signals, and displays them on a monitor, creating intuitive thermal images. These images reveal the temperature distribution of the floor during mining, allowing for the initial identification of water inrush paths by locating areas of temperature anomalies.

[0089] During mining, floor water inrush is accompanied by the flow of pressurized water. As the water flows through the exothermic material, it chemically reacts with it, releasing heat and causing abnormal temperature fluctuations. Real-time monitoring of these temperature changes with an infrared thermal imager can initially identify the formation of the water inrush path.

[0090] Infrared thermal imagers generate continuous thermal image sequences at a frequency of seconds or minutes. Abnormal temperature fluctuations will appear as increases or decreases in localized areas of the thermal image. By analyzing these continuous thermal images, the dynamic changes in the water inrush path can be further analyzed, including the direction and speed of path expansion.

[0091] like Figure 3 As shown, it is a comparison between the infrared thermal imager and normal shooting after the excavation of the working face in a similar simulation test. It can be clearly seen in the figure that a high-temperature concentrated area appears near the fault. This is because the exothermic material in this area reacts more strongly with water, indicating that a high-pressure water conduction path has been formed in this area, thereby realizing preliminary monitoring of the water conduction path.

[0092] After the mining is completed, the measurement results of the infrared thermal imager are exported and the image data are processed using the TV-Retinex algorithm.

[0093] like Figure 4 As shown, this embodiment provides a method for processing exported image data using the TV-Retinex algorithm. The method mainly includes two parts: data preprocessing and TV-Retinex algorithm processing, and the data preprocessing includes two parts: denoising and contrast enhancement.

[0094] First, the raw images exported from the infrared thermal imager are preprocessed, including denoising and contrast enhancement:

[0095] Noise removal: Use Gaussian filters to smooth out noise and ensure that the temperature change information in the image is more reliable.

[0096] Contrast enhancement: Use histogram equalization to adjust the brightness range of the image to make the temperature differences along the water inrush path more apparent.

[0097] The preprocessed image is then enhanced using the TV-Retinex algorithm. This algorithm, which combines Retinex theory with total variation (TV) regularization technology, can highlight local temperature anomalies in thermal images and reduce the interference of illumination inhomogeneity on the visualization of water inrush paths.

[0098] Retinex theory: Using the Retinex model to perform illumination correction and color constancy processing on thermal images. By separating the illumination and reflection components in an image, Retinex emphasizes subtle temperature variations along the water inrush path. As a result of illumination correction, high-temperature areas within the water inrush path become more distinct than the surrounding background, facilitating observation and analysis.

[0099] Retinex theory states that an image can be represented as the product of a reflectance map and an illumination map:

[0100] S(x,y)=R(x,y)·L(x,y)

[0101] Among them, S(x,y) represents the pixel value of the point (x,y) in the image;

[0102] R(x,y) is the reflectivity map, which represents the inherent temperature characteristics of the object surface;

[0103] L(x,y) is the light map, which shows the effect of light on the object.

[0104] Convert the multiplicative relationship to additive form by logarithmic transformation:

[0105] log(S(x,y))=log(R(x,y))+log(L(x,y))

[0106] The problem then becomes separating log(R(x,y)) and log(L(x,y)) from log(S(x,y)).

[0107] Total Variation (TV) Regularization: The image is further processed using TV regularization to remove noise and artifacts that may have been introduced during the processing. TV regularization preserves the image's edge structure and the sharp boundaries of the water inrush path, avoiding the destruction of path details while enhancing image contrast.

[0108] Its expression is as follows:

[0109]

[0110] in, is the image gradient; S represents the image function value at the point (x, y) in the image.

[0111] The goal of TV regularization is to make the boundary of the water inrush path clearer by minimizing the image gradient.

[0112] TV-Retinex comprehensive processing: The TV-Retinex algorithm combines the advantages of Retinex and TV regularization.

[0113] Its objective function is:

[0114]

[0115] in, represents the gradient of the reflectivity map, that is, the rate of change of zero degrees in the image; S represents the image function value of the point (x, y) in the image; R is the reflectivity map, which represents the inherent temperature characteristics of the object surface; L is the illumination map, which represents the influence of illumination on the object; λ is the weight parameter that controls the balance between total variation regularization and data fidelity terms.

[0116] The TV-Retinex algorithm suppresses noise and highlights the edges and details in the reflectivity image by minimizing the objective function.

[0117] The TV-Retinex algorithm significantly improves the temperature images generated by infrared thermal imagers, particularly by highlighting the details of floor water inrush paths. This highlights areas of temperature anomalies, helping to quickly and accurately identify water inrush paths in complex environments and providing strong support for mine water hazard prevention.

[0118] By comparing thermal images at different times with processed images, the dynamic changes in the water inrush path can be analyzed, specifically the speed, direction, and extent of path expansion during the confined water rise process. Real-time monitoring data can reflect the latest status of the water inrush, while algorithm-processed images provide clearer and more detailed path information.

Claims

1. A method for identifying and monitoring water source rise paths in sudden flood disasters based on similar simulation tests, characterized in that: include: S1. Collect mining area data, determine the lithology and paving thickness of each rock layer in the mining area, and make similar material proportions for each rock layer with determined lithology; S2. Use exothermic materials as layering materials in similar simulation tests; S3. Use the mining coal seam floor water inrush similarity simulation test system to lay the test materials and build a similar simulation test environment; S4. Deploy an infrared thermal imager to measure the infrared heat of the target; S5. During the mining process, infrared thermal imagers are used to obtain real-time thermal images and temperature values, thereby enabling preliminary identification and monitoring of the water inrush path; S6. After the mining is completed, the measurement results are exported, the measurement data are obtained and analyzed, and the water inrush path is obtained; S7. Compare and analyze the thermal image obtained by real-time monitoring with the path map obtained through algorithm processing to obtain detailed and accurate test results; The S5 specifically includes: S5.

1. During the mining process, use an infrared thermal imager to monitor the test in real time, and obtain real-time thermal images and temperature values through its built-in conversion function; S5.

2. Real-time analysis of thermal images can be used to visualize the bottom plate water inrush path formed during the high-pressure water diversion process; S5.1 specifically includes: S5.

11. The infrared thermal imager continuously scans the mining area to collect temperature data in real time. S5.

12. Infrared thermal imagers detect infrared energy through non-contact detection and convert it into electrical signals, which then generate visual thermal images and temperature values on a display. S5.2 specifically includes: S5.

21. In thermal images, high-pressure water flow reacts chemically with components in exothermic materials, releasing heat energy and causing localized temperature anomalies. By identifying areas of rapid temperature increase or decrease and analyzing the trajectory of the water flow, the path of the water inrush is gradually revealed in the thermal image. S5.

22. Generate a continuous sequence of thermal images at a set frequency for real-time monitoring. By comparing thermal images at different times, analyze the dynamic process of temperature changes. The expansion and direction of the water inrush path are reflected in the image as the displacement and diffusion of the temperature anomaly area. The S6 specifically includes: S6.

1. After the mining is completed, the measurement results in the infrared thermal imager storage system are exported to obtain the measurement data; S6.

2. Process the exported image data using the TV-Retinex algorithm to obtain a specific water inrush path; S6.2 processes the exported image data using the TV-Retinex algorithm, specifically: S6.

21. Preprocessing of raw image data: Noise removal: Use Gaussian filtering or median filtering techniques to remove image noise and eliminate random temperature changes that may affect path recognition; Contrast enhancement: adjust the image contrast through histogram equalization to enhance the overall visibility of the image and make the water inrush path more obvious in the image; S6.

22. Use the TV-Retinex algorithm combined with Retinex theory and total variation regularization technology to enhance the preprocessed image: Use the Retinex theoretical model to perform illumination correction and color constancy processing on thermal images; The images are further processed using a total variation regularization method to remove noise and artifacts introduced during the processing.

2. The method for identifying and monitoring water source rise paths of sudden flood disasters based on similar simulation tests according to claim 1 is characterized by: In S4, an infrared thermal imager is deployed to measure the infrared heat of the target, specifically: S4.

1. Deploy infrared thermal imagers at locations that can cover the mining impact area, fault areas, and possible water inrush paths; S4.

2. Set the measurement range and resolution of the infrared thermal imager to ensure that it can monitor local temperature changes during mining.

3. The method for identifying and monitoring water source rise paths of sudden flood disasters based on similar simulation tests according to claim 1 is characterized in that: The S7 is specifically: By comparing thermal images and processed images at different times, the dynamic changes in the speed, direction and range of the water inrush path expansion during the pressurized water diversion process are analyzed.

Images