Tunnel high-temperature heat disaster advanced geological detection method and system based on heat source inversion

Abstract

The application provides a tunnel high-temperature heat disaster advanced geological detection method and system based on heat source inversion, and the application uses "rock wall + borehole" multi-view combined observation to extract two kinds of collected temperature data to form a new sequence, carries out inversion interpretation on the sequence, constructs a three-dimensional heat source inversion target function and an inversion equation based on least square, and solves the inversion equation; forms a heat source and temperature field imaging result map of high-temperature heat disaster detection in a survey area range according to the solving result, realizes effective positioning and capturing of high-temperature heat sources, divides high-temperature heat disaster grades, evaluates heat disaster risk, and provides a reference basis for determination of a tunnel design and a construction scheme.

Description

Technical Field

[0001] This invention belongs to the field of tunnel geothermal field detection technology, and relates to a method and system for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In some areas with high altitudes, diverse terrains, complex geological conditions, abundant geothermal resources, and frequent hydrothermal activity, hot springs and hot water are prevalent. Tunnel projects traversing these high-temperature regions are constantly emerging, making high ground temperature a major challenge in tunnel construction. The high-temperature hazards caused by geothermal anomalies significantly impact tunnel engineering, especially the construction of deep and long tunnels. High ground temperatures not only increase the difficulty of tunnel construction, delay the construction period, and reduce economic benefits, but also endanger the health of construction workers and the safety of structures. Specific problems are as follows:

[0004] (1) In high-temperature environments, the efficiency of machinery and workers decreases, and equipment failures increase. Working for a long time in high-temperature conditions can lead to heatstroke symptoms such as heat cramps, heat exhaustion, and heatstroke, which seriously endanger the physical and mental health of workers and the safety and quality of engineering projects;

[0005] (2) High ground temperatures not only affect construction machinery and personnel inside the tunnel, but also impact the surrounding rock and the tunnel's structure. Because the temperature of the rock strata in high-temperature tunnels is relatively high, while the air temperature inside the tunnel is relatively low, a temperature difference is created in the lining structure. This temperature difference results in uneven stress distribution, leading to tensile stress on the concrete surface. Since concrete structures have relatively weak tensile strength, this poses a potential safety hazard to the tunnel structure.

[0006] Therefore, during tunnel construction, in order to ensure the smooth progress of tunnel construction, adopting effective advanced geological forecasting methods can help us know the location and scale of high-temperature heat hazards ahead, understand the type and severity of high-temperature heat hazards, and take precautions in advance to effectively ensure the safety of the project construction.

[0007] High-temperature heat hazards in tunnels are classified into high-temperature rock heat and high-temperature hot water. In existing engineering construction, advanced horizontal drilling methods are often used to predict whether there is hot water or hot air ahead, and to measure the temperature inside the borehole to obtain the temperature of the rock or hot water, determine the type and level of heat hazard, and guide and ensure construction safety. However, high-temperature hot water in tunnels often develops in the form of fault-hard rock fissures or fault-karst fissures, pipes, and caves, with complex and diverse occurrence conditions. Moreover, the temperature field is a diffusion field, and the transmission range of small-volume high-temperature heat sources is limited. It is difficult to detect the distribution of hidden high-temperature hot water around the borehole using borehole temperature measurement methods alone, resulting in serious underreporting. Summary of the Invention

[0008] To address the aforementioned problems, this invention proposes a method and system for advanced geological detection of high-temperature heat hazards in tunnels based on heat source inversion. This invention employs a heat source inversion method to rapidly invert and interpret the detection results, obtaining the distribution of the geothermal field of the surrounding rock ahead of the tunnel excavation face. This enables effective location and capture of high-temperature heat sources, classification of high-temperature heat hazard levels, and evaluation of heat hazard risk, providing a reference for determining tunnel design and construction schemes.

[0009] According to some embodiments, the present invention adopts the following technical solution:

[0010] A method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion includes the following steps:

[0011] Based on preliminary survey data and high ground temperature monitoring data inside the tunnel, sections with abnormally high temperatures along the tunnel route are predicted.

[0012] In the initially identified high-temperature thermal anomaly section, advance boreholes were laid out, and temperature measuring equipment was installed in the advance boreholes to measure the internal temperature of the rock mass.

[0013] Obtain the scanning results of the apparent temperature of the surrounding rock in the tunnel;

[0014] The two types of temperature data collected are extracted to form a new sequence. The sequence is then inverted and interpreted. A three-dimensional heat source inversion objective function and inversion equation based on least squares are constructed, and the inversion equation is solved.

[0015] Based on the solution results, a heat source and temperature field imaging result map of the high-temperature heat hazard detection within the survey area is generated. Combined with existing geology, the temperature, location, scale, type and hazard level of the high-temperature heat hazard are analyzed.

[0016] As an alternative implementation method, the specific process of predicting high-temperature abnormal sections along the tunnel includes conducting geophysical exploration and deep borehole temperature measurements along the tunnel excavation axis on the ground surface, dividing the geothermal abnormal sections, and predicting the type of high-temperature heat hazard; monitoring high geothermal data such as the surface temperature of the surrounding rock, the working environment temperature, and the water temperature inside the tunnel, and determining whether a high geothermal abnormal area has been entered based on the temperature and temperature rate changes of the excavated sections along the tunnel.

[0017] After tunnel excavation, routine monitoring of the temperature and rate of change of the surrounding rock at the tunnel face can provide a qualitative understanding of the temperature situation ahead of the tunnel. Generally, if the surrounding rock temperature exceeds the set temperature and the temperature continues to rise and the rate of temperature increase as the tunnel is excavated, it can be qualitatively determined that the excavation is approaching a high geothermal anomaly area.

[0018] As an alternative implementation method, the specific process of deploying advanced boreholes and installing temperature measuring equipment in the advanced boreholes includes excavating ear holes on the left and right sidewalls behind the tunnel face, drilling advanced boreholes from the ear holes to the front of the tunnel, installing distributed optical fibers into the boreholes, filling the boreholes with cement mortar, and collecting and analyzing the temperature data inside the boreholes when the temperature of the surrounding rock and the temperature inside the boreholes reach a stable level.

[0019] As an alternative implementation method, the specific process of obtaining the scanning results of the apparent temperature of the surrounding rock of the tunnel includes moving the scanning of the temperature of the left and right walls, the arch, and the tunnel face, and matching the infrared thermometry results with the measurement space.

[0020] As an alternative implementation method, the objective function is specifically:

[0021] S MP =(ΔT-J(F-F0)) T (ΔT-J(F-F0))+λ(C(F-F0)) T (C(F-F0))+η(W1(FF r )) T (W1(FF r ))

[0022] Where ΔT is the difference vector between the actual observed data and the forward modeling theoretical observed data, F is the model parameter vector to be solved in the inversion, J represents the sensitivity matrix, C represents the smoothness matrix; λ is the Lagrange daily number, used to control the weight between the data variance term and the model variance term; F0 is the model parameter parameter obtained in the previous inversion, F r η is the parameter vector of the reference model for this inversion, W1 is the coefficient matrix of the reference model, and η is the weight coefficient of the reference model constraint.

[0023] As an alternative implementation, the inversion equation is:

[0024]

[0025] Where ΔF is the increment vector of model parameters, J represents the sensitivity matrix, C represents the smoothness matrix; λ is the Lagrange daily number, F r Here is the parameter vector of the reference model for this inversion, W1 is the coefficient matrix of the reference model, and η is the weight coefficient of the reference model constraint.

[0026] Wherein, matrix J is:

[0027] J = K -1

[0028] Where K is the sum of the thermal conductivity coefficients of the discrete nodes of the objects contained in each unit, and is a known quantity.

[0029] As an alternative implementation method, the specific process of solving the inversion equation includes:

[0030] A three-dimensional thermal load model parameter finite difference model is established, and the initial values ​​of the model parameters are determined based on the measured temperature data;

[0031] Geological analysis and geophysical exploration are conducted to determine the prior information of anomalies and map it onto the inversion calculation model to form a reference model.

[0032] Given model parameters, the finite difference method is used to perform simulation calculations to obtain theoretical observation data;

[0033] The inversion convergence is judged by the mean square difference between the measured data and the theoretical data. If the mean square difference obtained by the inversion is less than the set convergence value or the set number of inversions is reached, the inversion ends and the model parameters at this time are output. The temperature distribution is obtained by forward modeling. If the mean square difference is greater than the set value and the set number of inversions is not reached, the inversion steps continue to be executed.

[0034] Based on the reference model constraints and the model parameters in this inversion, the inversion equations are solved to obtain the changes in the model parameter vector.

[0035] Once the new model parameters are obtained, the steps for simulation calculations using the finite difference method are returned, and the next generation of iterative inversion is performed.

[0036] A tunnel high-temperature thermal hazard advanced geological detection system based on heat source inversion includes:

[0037] The first acquisition system is used to measure the internal temperature of the rock mass in the advanced boreholes deployed in the initially identified high-temperature thermal anomaly section.

[0038] The second acquisition system is used to obtain the scanning results of the apparent temperature of the surrounding rock in the tunnel;

[0039] The inversion interpretation module is configured to extract the two types of temperature data collected to form a new sequence, perform inversion interpretation on the sequence, construct a three-dimensional heat source inversion objective function and inversion equation based on least squares, and solve the inversion equation.

[0040] The imaging analysis module is configured to generate an imaging result map of the heat source and temperature field of the high-temperature heat hazard detection within the survey area based on the solution results, and analyze the temperature, location, scale, type and hazard level of the high-temperature heat hazard in combination with the existing geology.

[0041] As an alternative implementation, the first acquisition system consists of multiple distributed fiber optic temperature measurement modules, each installed in one of the advanced boreholes.

[0042] As an alternative implementation, the second acquisition system is a scanning robot.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] This invention proposes for the first time an advanced geological detection method for high-temperature heat hazards in tunnels based on heat source inversion. By using the apparent temperature of the tunnel rock wall and borehole temperature data, the heat source term is inverted and the temperature field in the surrounding rock in front of the tunnel is reconstructed. This enables the effective location and capture of high-temperature heat sources, and the classification of high-temperature heat hazard levels based on temperature distribution, evaluates the risk of heat hazards, and provides technical guidance for early warning and control of high-temperature heat hazards.

[0045] This invention proposes a multi-view joint observation system based on "rock wall + borehole". It uses a rock wall temperature field scanning robot to realize rapid perception of the apparent temperature of the surrounding rock, and uses a borehole distributed fiber optic temperature measurement device to realize the perception of the internal temperature distribution of the rock mass. This can obtain more effective geological information and improve the ability to detect and identify high-temperature thermal hazard anomalies.

[0046] This invention constructs a geothermal field constrained inversion equation carrying a priori reference model, which adds prior information obtained by other geophysical exploration methods, so that the model heat source parameters develop towards the reference model determined by the prior information. Theoretically, this is beneficial to suppressing the problem of multiple solutions in the inversion and achieves a better reflection of the heat source shape, scale, temperature value, etc. Attached Figure Description

[0047] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0048] Figure 1 This is a schematic diagram of the distributed optical fiber temperature measurement arrangement scheme for tunnel drilling according to the present invention;

[0049] Figure 2 This is a schematic diagram of the tunnel rock wall infrared temperature measurement arrangement scheme of the present invention;

[0050] Figure 3(a) is the high-temperature heat hazard distribution model of the numerical example of the present invention;

[0051] Figure 3(b) is a diagram of the heat source and temperature field distribution obtained by the inversion of the present invention. Detailed Implementation

[0052] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0053] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0054] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0055] A method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion includes the following steps:

[0056] A. Based on the preliminary surface survey and borehole temperature measurement data, geothermal anomaly sections are divided from a macroscopic perspective. Based on the high geothermal monitoring data inside the tunnel, the abnormal temperature rate changes in the excavated sections are analyzed. From an engineering perspective, areas that are about to encounter high geothermal disasters are predicted. A scientific and reasonable borehole layout plan is designed for the predicted sections.

[0057] In this embodiment, specifically as follows: Figure 1 As shown, an ear hole was excavated about 2m behind the tunnel sidewall, and a forward borehole was drilled from the ear hole towards the front of the tunnel, as parallel to the tunnel axis as possible.

[0058] Multiple pre-drilling holes can be performed.

[0059] B. Distributed optical fibers were installed in two pre-drilled holes and the holes were filled with cement mortar to allow the temperature inside the holes and the temperature of the surrounding rock to reach equilibrium. The equilibrium required a long time, so a layout scheme for the pre-drilled holes was designed. Subsequently, the temperature measurement data of the distributed optical fibers in the holes were collected and analyzed to preliminarily determine the location of the heat source.

[0060] C. A thermal infrared scanning robot is used to perform mobile scanning of the temperature of the left and right walls, arch, and tunnel face of the tunnel. The thermal infrared scanning robot has a built-in positioning system that matches the infrared temperature measurement results with the measurement space to obtain a large amount of apparent temperature data of the tunnel rock walls.

[0061] Existing robots can be selected for thermal infrared scanning. For example... Figure 2 As shown, a feasible example of a thermal infrared scanning robot structure is given, which specifically includes a walking mechanism, a vertical moving structure on the walking mechanism, and an infrared thermal imager on the vertical moving structure. By adjusting the position of the walking mechanism and the position of the vertical moving structure, infrared scanning areas with each fulcrum in the rock wall region can be realized.

[0062] D. Steps B and C are superimposed to form a new joint observation mode of "borehole + rock wall" multi-view. The data collected by the new observation mode is extracted to form a new sequence. The sequence is comprehensively inverted and interpreted, which greatly increases the amount of data collected and can obtain more effective geological information in front of the tunnel, thus improving the ability to detect and identify high temperature and thermal hazards in front of the tunnel.

[0063] In this embodiment, the new sequence extraction is related to the desired grid size. The extracted point temperatures should all be located on the grid nodes. It is not necessary to sort out the data on the rock wall first or the temperature measurement data inside the borehole first, as long as it can match the forward and inverse modeling program. The extracted temperature data is used to inverse the heat source distribution in front of the tunnel.

[0064] E. To address the issue of multiple solutions in 3D tunnel heat source inversion imaging, a geothermal field-constrained inversion approach with a priori reference model is proposed. The objective function for 3D high-temperature heat source detection and inversion is:

[0065] S MP =(ΔT-J(F-F0)) T (ΔT-J(F-F0))+λ(C(F-F0)) T (C(F-F0))+η(W1(FF r )) T (W1(FF r ))

[0066] Where ΔT is the difference vector between the actual observed data and the forward modeling theoretical observed data, F is the model parameter vector to be solved in the inversion, J represents the sensitivity matrix, C represents the smoothness matrix; λ is the Lagrange daily number, used to control the weight between the data variance term and the model variance term; F r η is the parameter vector of the reference model for this inversion, W1 is the coefficient matrix of the reference model, and η is the weight coefficient of the reference model constraint.

[0067] Finding the minimum value of the objective function formula (1) yields the corresponding inversion equation:

[0068]

[0069] The above formula is the geothermal field constraint inversion equation carrying a priori reference model. Theoretically, applying prior information obtained from other geophysical methods as constraints to the inversion equation will cause the model's heat source parameters to evolve towards the reference model determined by the prior information. This helps to suppress the problem of multiple solutions in the inversion and achieve a better reflection of the heat source's shape, scale, temperature, etc.

[0070] F. In the process of performing three-dimensional heat source inversion, the partial derivative matrix J is calculated differently than in conventional methods, and its calculation expression is as follows:

[0071] J = K -1

[0072] Wherein, K is the sum of the thermal conductivity coefficients of the discrete nodes of the objects contained in each unit. In form, it is symmetrical and reversible, and is a known quantity.

[0073] The specific calculation process for heat source inversion is as follows:

[0074] 1) Establish a three-dimensional thermal load model parameter finite difference model, and determine the initial values ​​of the model parameters based on the measured temperature data;

[0075] 2) Conduct geological analysis and geophysical exploration to determine the prior information of the anomaly and map it onto the inversion calculation model to form a reference model;

[0076] 3) For the given model parameters, the finite difference method is used to perform simulation calculations to obtain theoretical observation data;

[0077] 4) Perform inversion convergence judgment, using the mean square error between measured data and theoretical data as the criterion. If the mean square error obtained by inversion is less than the set convergence value or the set number of inversions is reached, the inversion ends, the model parameters at this time are output, and the temperature distribution is obtained by forward modeling. If the mean square error is greater than the set value and the set number of inversions has not been reached, the inversion steps continue to be executed.

[0078] 5) Based on the reference model constraints and the model parameters in this inversion, solve the inversion equation to obtain the model parameter vector change ΔF.

[0079] 6) Obtain the new model parameters and proceed to step 3) to perform the next generation iterative inversion.

[0080] G. After the above steps are performed on the collected temperature data for inversion and interpretation, the inversion imaging results of the high-temperature geothermal anomaly heat source within the survey area can be obtained. Figure 3(a) shows the numerical example model of the heat source distribution, and Figure 3(b) is the isosurface map of the heat source and temperature field obtained by comprehensive inversion and interpretation using the method described in this invention. The location, shape and scale of the high-temperature heat source can be clearly seen from the figure, which is basically consistent with the original model.

[0081] Three-dimensional heat source detection can obtain a relatively accurate temperature field imaging result of heat source distribution in the tunnel area. Combined with existing geological analysis, it can further infer the type of high-temperature heat hazard and the level of harm to the tunnel, which can provide strong technical support and guarantee for the safe and efficient construction of high-temperature tunnels.

[0082] The type of heat hazard ahead of the tunnel can be determined by the gradient change of the three-dimensional geothermal field distribution obtained by inversion. Generally, if the lateral temperature change is relatively small and there is no hot water exposure, and the ground well temperature shows multiple broken lines, it can be determined that the heat hazard is a conductive heat hazard. If the temperature change is relatively large and there is hot water exposure, and the ground well temperature shows an upward convex shape, it can be determined that the heat hazard is a thermal convection heat hazard with high-temperature hot water.

[0083] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion, characterized in that, Includes the following steps: Based on preliminary survey data and high ground temperature monitoring data inside the tunnel, sections with abnormally high temperatures along the tunnel route are predicted. In the initially identified high-temperature thermal anomaly section, advance boreholes were laid out, and temperature measuring equipment was installed in the advance boreholes to measure the internal temperature of the rock mass. Obtain the scanning results of the apparent temperature of the surrounding rock in the tunnel; The two types of temperature data collected are extracted to form a new sequence. The sequence is then inverted and interpreted. A three-dimensional heat source inversion objective function and inversion equation based on least squares are constructed, and the inversion equation is solved. Based on the solution results, a heat source and temperature field imaging result map of the high-temperature heat hazard detection within the survey area is generated. Combined with existing geology, the temperature, location, scale, type and hazard level of the high-temperature heat hazard are analyzed.

2. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The specific process for predicting high-temperature anomaly sections along the tunnel route includes conducting geophysical exploration and deep borehole temperature measurements along the tunnel excavation axis on the ground surface, dividing the geothermal anomaly sections, and predicting the type of high-temperature heat hazard; monitoring high geothermal data such as the surface temperature of the surrounding rock, the working environment temperature, and the water temperature inside the tunnel; and determining whether a high geothermal anomaly area has been entered based on the temperature and temperature rate changes of the excavated sections along the route.

3. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 2, characterized in that, After tunnel excavation, monitoring the temperature and rate of change of the surrounding rock at the tunnel face is crucial. If the surrounding rock temperature exceeds the set temperature and continues to rise with the tunnel excavation, and the rate of temperature increase, it can be qualitatively determined that the excavation is approaching a high geothermal anomaly area.

4. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The specific process of setting up advance boreholes and installing temperature measuring equipment in the advance boreholes includes excavating ear holes on the left and right sidewalls behind the tunnel face, drilling advance boreholes from the ear holes to the front of the tunnel, installing distributed optical fibers into the boreholes, filling the boreholes with cement mortar, and collecting and analyzing the temperature data inside the boreholes when the temperature of the surrounding rock and the temperature inside the boreholes reach a stable level.

5. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The specific process of obtaining the scanning results of the apparent temperature of the surrounding rock of the tunnel includes moving the scanning of the temperature of the left and right walls, the arch, and the working face of the tunnel, and matching the infrared thermometry results with the measurement space.

6. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The objective function is specifically: S MP =(ΔT-J(F-F0)) T (ΔT-J(F-F0))+λ(C(F-F0)) T (C(F-F0))+η(W1(FF r )) T (W1(FF r )) Where ΔT is the difference vector between the actual observed data and the forward modeling theoretical observed data, F is the model parameter vector to be solved in the inversion, J represents the sensitivity matrix, C represents the smoothness matrix; λ is the Lagrange daily number, used to control the weight between the data variance term and the model variance term; F0 is the model parameter parameter obtained in the previous inversion, F r is the parameter vector of the reference model for this inversion, W1 is the reference model coefficient matrix, and 77 is the weight coefficient of the reference model constraint.

7. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The inversion equation is: Where ΔF is the increment vector of model parameters, J represents the sensitivity matrix, C represents the smoothness matrix; λ is the Lagrange daily number, F r Here is the parameter vector of the reference model for this inversion, W1 is the coefficient matrix of the reference model, and η is the weight coefficient of the reference model constraint. Wherein, matrix J is: J=K -1 Where K is the sum of the thermal conductivity coefficients of the discrete nodes of the objects contained in each unit, and is a known quantity.

8. The method for advanced geological detection of high-temperature thermal hazards in tunnels based on heat source inversion as described in claim 1, characterized in that, The specific process of solving the inversion equation includes: A three-dimensional thermal load model parameter finite difference model is established, and the initial values ​​of the model parameters are determined based on the measured temperature data; Geological analysis and geophysical exploration are conducted to determine the prior information of anomalies and map it onto the inversion calculation model to form a reference model. Given model parameters, the finite difference method is used to perform simulation calculations to obtain theoretical observation data; The inversion convergence is judged by the mean square difference between the measured data and the theoretical data. If the mean square difference obtained by the inversion is less than the set convergence value or the set number of inversions is reached, the inversion ends and the model parameters at this time are output. The temperature distribution is obtained by forward modeling. If the mean square difference is greater than the set value and the set number of inversions is not reached, the inversion steps continue to be executed. Based on the reference model constraints and the model parameters in this inversion, the inversion equations are solved to obtain the changes in the model parameter vector. Once the new model parameters are obtained, the steps for simulation calculations using the finite difference method are returned, and the next generation of iterative inversion is performed.

9. A tunnel high-temperature thermal hazard advanced geological detection system based on heat source inversion, characterized in that, include: The first acquisition system is used to measure the internal temperature of the rock mass in the advanced boreholes deployed in the initially identified high-temperature thermal anomaly section. The second acquisition system is used to obtain the scanning results of the apparent temperature of the surrounding rock in the tunnel; The inversion interpretation module is configured to extract the two types of temperature data collected to form a new sequence, perform inversion interpretation on the sequence, construct a three-dimensional heat source inversion objective function and inversion equation based on least squares, and solve the inversion equation. The imaging analysis module is configured to generate an imaging result map of the heat source and temperature field of the high-temperature heat hazard detection within the survey area based on the solution results, and analyze the temperature, location, scale, type and hazard level of the high-temperature heat hazard in combination with the existing geology.

10. The tunnel high-temperature thermal hazard advanced geological detection system based on heat source inversion as described in claim 9, characterized in that, The first acquisition system consists of multiple distributed fiber optic temperature measurement modules, which are respectively installed in each advanced borehole; Alternatively, the second acquisition system may be a scanning robot.

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