Thermal conduction temperature compensation method for infrared response information of coal and rock crack damage

Abstract

The present invention discloses a thermal conduction temperature compensation method for infrared response information of crack damage of coal and rock, which belongs to the technical field of monitoring and early warning of damage and destruction of coal and rock mass in mines and prevention and control of water inrush disasters in water conservation and mining. Determine the target area for infrared radiation monitoring of the bearing coal and rock, set reference coal and rock to perform time domain denoising on the infrared radiation information of the bearing coal and rock, extract the time domain change data, initial temperature field data and thermodynamic parameters of the boundary heat source of the bearing coal and rock; establish a COMSOL solid heat transfer numerical calculation model, derive and convert the calculation results into a two-dimensional matrix of time series; test the COMSOL numerical calculation results, and use the effective calculation results to perform thermal conduction temperature compensation on the infrared radiation response information of the bearing coal and rock. It can effectively reduce the influence of environmental heat sources on the law of infrared radiation changes, help to realize infrared quantitative characterization of coal and rock damage evolution and infrared precise identification of damage precursors, and provide safety guarantees for water resource protective mining and mine water disaster prevention and control.

Description

Technical Field

[0001] The invention relates to a heat conduction temperature compensation method for carrying infrared response information of coal rock crack damage, belonging to the technical field of monitoring and early warning of coal rock damage and destruction in mines and prevention and control of water inrush disasters in water-saving mining. Background Art

[0002] Under the action of external loads, internal cracks in coal and rock will gradually initiate, expand and penetrate. The development of microcracks is generally considered to be a process of rock damage accumulation, which eventually leads to macroscopic destruction of the rock. This is also the root cause of disasters such as coal pillar instability, impact mining pressure, and roof collapse in mines. Accurately and effectively monitoring the evolution of coal and rock damage and identifying precursor information of coal and rock instability are the key to ensuring safe and efficient production in mines. During the evolution of coal and rock damage, part of the elastic energy accumulated inside will be released in the form of heat energy, stimulating infrared electromagnetic waves. Therefore, infrared radiation, as a non-destructive remote sensing detection technology, is a potential and effective means to determine the scope of coal and rock damage and fracture and monitor the evolution of coal and rock damage.

[0003] Effectively extracting the infrared radiation temperature increment caused by crack evolution is the key to using infrared radiation to characterize the evolution process of coal and rock damage. However, the infrared radiation temperature increment caused by the evolution of microcracks in coal and rock is relatively weak and easily affected by noise. To this end, the existing technology uses background noise correction models, median filtering and other methods to correct the infrared radiation temperature field. These methods can better remove environmental noise and improve the clarity of infrared radiation images, but it is difficult to reduce the influence of the heat conduction effect of interfering heat sources during infrared monitoring.

[0004] During infrared radiation monitoring, there is often a temperature difference between the bearing coal rock mass (monitoring target) and the bearing end (interference heat source). The infrared radiation temperature field on the coal rock surface will change due to the temperature gradient. On the one hand, it makes the heat caused by microcrack extension unclear in the infrared thermal image, and on the other hand, it makes the characteristic parameters of the infrared radiation temperature field show an obvious upward (or downward) trend, which leads to misjudgment of the stability of the bearing coal rock mass. Therefore, it is urgent to study a heat conduction temperature compensation method for the infrared response information of crack damage in the bearing coal rock, and to correct the infrared radiation temperature field of the bearing coal rock mass, so as to achieve accurate early warning of coal rock damage and quantitative characterization of the damage evolution process. Summary of the invention

[0005] Purpose of the invention: In view of the problems of the prior art, the present invention proposes a thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage, which corrects the infrared radiation temperature field of the bearing coal rock mass to solve the influence of the thermal conduction effect of the interfering heat source on the infrared radiation temperature field and improve the accuracy of infrared radiation monitoring and early warning of rock engineering disasters.

[0006] Technical solution: To achieve the purpose of the present invention, a thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage includes the following steps:

[0007] Step 1: Collect infrared radiation monitoring data of bearing coal rock: set reference coal rock of the same type as the bearing coal rock within one meter of the bearing coal rock in the area to be detected, and use an infrared thermal imager to simultaneously monitor the infrared radiation information of the bearing and reference coal rock surfaces;

[0008] Step 2, correcting the time domain noise of the infrared radiation information of the coal rock: using the mean value of the reference infrared temperature matrix to perform time domain noise correction on the target infrared temperature matrix obtained by the infrared thermal imager, and obtaining the target infrared temperature matrix after time domain noise correction;

[0009] Step 3: Use an infrared thermal imager to collect information to obtain the time domain variation data and initial temperature field data of the interfering heat source bearing the coal-rock boundary: Take the target infrared radiation temperature matrix after time domain noise correction as the object, and determine the time domain variation data and initial temperature field data of the heat source bearing the coal-rock boundary;

[0010] Step 4: Obtain the thermodynamic parameters of the bearing coal rock: Based on laboratory thermodynamic experiments, determine the main thermodynamic parameters of the monitored coal rock mass, including: heat capacity at normal pressure, density, thermal conductivity, thermal expansion coefficient, Young's modulus, and Poisson's ratio;

[0011] Step 5, establish a COMSOL rectangular model of the evolution of the coal rock surface temperature field under the influence of heat conduction: according to the actual situation of the monitoring area, use COMSOL numerical software to establish a rectangular model of the coal rock heat transfer module, wherein a grid divided by the number of rows and columns of the infrared temperature matrix is ​​provided in the rectangular model;

[0012] Step 6, assigning parameters to the COMSOL rectangular model: assigning the initial temperature field data obtained in step 3 to the COMSOL rectangular model, assigning the boundary heat source time domain variation data obtained in step 3 to the dynamic heat source of the COMSOL rectangular model, and inputting the coal rock thermodynamic parameters obtained in step 4 as material properties into the COMSOL rectangular model;

[0013] Step 7, COMSOL numerical calculation process: according to the monitoring frequency of the infrared thermal imager, set the time step of the transient temperature field calculation of the COMSOL rectangular model, and calculate the time domain variation process of the infrared radiation temperature field of the bearing coal rock under the influence of the boundary heat source;

[0014] Step 8, export the numerical calculation results of the COMSOL rectangular model: set the grid spacing based on the target infrared radiation temperature matrix, export the infrared radiation heat conduction temperature matrix data of each time step obtained by the COMSOL rectangular model calculation, convert the exported bearing coal rock heat conduction temperature data into a two-dimensional matrix, record it as the heat conduction temperature matrix (HCTM(t)), and calculate the target infrared temperature matrix and the heat conduction temperature matrix row average value at each moment;

[0015] Step 9, verify the COMSOL numerical calculation results: take the infrared radiation temperature matrix of the first 30% frames in the monitoring process as samples, take the target infrared temperature matrix row average as the independent variable, and the heat conduction temperature matrix row average as the dependent variable, perform a univariate linear regression operation on the target infrared temperature matrix row average and the heat conduction temperature matrix row average, and calculate the correlation coefficient of each frame of experimental data and simulation data, and use the average value of the correlation coefficient at each moment to verify the numerical calculation results of the COMSOL rectangular model;

[0016] Step 10, thermal conduction compensation of the infrared radiation temperature field of the bearing coal rock: subtract the target infrared radiation temperature matrix after noise correction from the thermal conduction temperature matrix to obtain the bearing coal rock infrared radiation temperature matrix after thermal conduction temperature compensation, and use the bearing coal rock infrared radiation temperature matrix to perform thermal conduction temperature compensation on the infrared radiation response information of the bearing coal rock, thereby effectively reducing the influence of environmental heat sources on the changing law of infrared radiation, making the infrared radiation information present a real changing trend, amplifying the abnormal infrared radiation response at the moment of coal rock crack damage, realizing infrared quantitative characterization of coal rock damage evolution and infrared precise identification of damage precursors, providing safety guarantees for water resource protective mining and mine water hazard prevention and control.

[0017] Further, the method for collecting infrared radiation monitoring data of the loaded coal rock described in step 1 is: resampling the loaded coal rock and the reference coal rock using rectangular data frames of the same size to obtain the target infrared temperature matrix IRM of the loaded coal rock L And reference coal rock reference infrared temperature matrix IRM R .

[0018] Further, the time domain noise correction method of the infrared radiation of the coal rock described in step 2 is: calculating the time domain change value of the reference infrared temperature matrix mean, the formula is as follows:

[0019]

[0020] Where: AIRM R (t) is the time domain variation value of the reference infrared temperature matrix mean, i and j are the row and column numbers of the reference coal rock infrared temperature matrix, x and y are the matrix row and column numbers, t is time, IRM R(t) is the mean value of the reference infrared temperature matrix at time t;

[0021] The target infrared temperature matrix is ​​subtracted from the mean of the reference infrared radiation temperature matrix to obtain the target infrared temperature matrix after time domain noise correction. The formula is as follows:

[0022] IRM' L (t) = IRM L (t)-AIRM R (t)

[0023] Where: IRM' L (t) is the target infrared temperature matrix after time domain noise correction.

[0024] Further, the method for extracting the time domain variation data and initial temperature field data of the boundary heat source described in step 3 is: determine the non-air-facing boundary of the target infrared temperature matrix after time domain noise correction, and the temperature matrix rows and columns corresponding to the non-air-facing boundary are the time domain variation data of the boundary heat source, as shown in the following formula:

[0025] BHS U (t) = IRM' L (1,:,t)

[0026] BHS L (t) = IRM' L (m,:,t)

[0027] Where: BHS U (t) is the heat source on the air boundary of the coal rock at time t, BHS L (t) is the heat source loaded at the air boundary under the coal rock at time t. Afterwards, the target infrared temperature matrix at the initial time is selected as the initial temperature field data IRM' L (t0).

[0028] Furthermore, the COMSOL rectangular model establishment method described in step 5 is: establishing a rectangular rock material model including a heat conduction module in COMSOL, dividing the rectangular rock material model into grids according to the number of rows and columns of the target infrared temperature matrix, and each grid node in the rectangular rock material model corresponds to an element in the temperature matrix; then, setting a time dynamic heat source assigned by the detection result at the non-air boundary of the rectangular rock material model, the dynamic heat source changes with time, and setting the air boundary as thermal insulation, thereby calculating the heat conduction result of the same scale as the infrared temperature matrix obtained by monitoring.

[0029] Furthermore, the COMSOL rectangular model parameter assignment method described in step 6 is: taking the first row and first column element of the target infrared temperature matrix as the origin, and using the actual area of ​​the monitoring area to convert the coordinate values ​​of each element of the target infrared temperature matrix; assigning the initial temperature field data obtained in step 3 to the grid corresponding to the coordinate value in the COMSOL rectangular model, and assigning the boundary heat source time domain change data obtained in step 3 to the dynamic heat source of the model.

[0030] Further, the formula for calculating the time step of the transient temperature field of the COMSOL rectangular model described in step 7 is:

[0031]

[0032] Where: ts is the calculation time step of the transient temperature field of the COMSOL numerical model, and f is the monitoring frequency of the infrared thermal imager.

[0033] Furthermore, the target infrared temperature matrix and the heat conduction temperature matrix row average calculation formula described in step 8 are as follows:

[0034]

[0035] Where: AHCT(t) is the row average of the heat conduction temperature matrix, T m,n (t) is the temperature value of the mth row and nth column of the heat conduction temperature matrix, is the average value of the mth row of the thermal conduction temperature matrix. ATIT(t) is the average value of the target infrared radiation temperature matrix, T m ' ,n (t) is the temperature value of the mth row and nth column of the target infrared temperature matrix, The mth row is the average value of the target infrared temperature matrix.

[0036] Furthermore, the COMSOL numerical calculation result verification method described in step 9 is: setting the judgment threshold to 0.95, calculating the average value of the correlation coefficient corresponding to the linear regression at each moment, when the average value is greater than the preset value of 0.95, the calculation result is valid; when the average value is less than the preset value of 0.95, return to step 6, within the material parameter error range, fine-tune the thermodynamic parameters in the COMSOL model, and recalculate the COMSOL numerical model until the correlation coefficient average value is greater than the preset value of 0.95.

[0037] Furthermore, the heat conduction compensation formula of the infrared radiation temperature field of the bearing coal rock used in step 10 is as follows:

[0038] CITM(t)=IRM' L (t)-HCTM(t)

[0039] Where: CITM(t) is the infrared radiation temperature matrix of the bearing coal rock after thermal conduction temperature compensation.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1) The present invention uses reference coal rock to perform time domain denoising on the infrared radiation temperature matrix of the monitored target, eliminating the influence of environmental convection and temperature drift defects of uncooled thermal imagers on the monitoring results, thereby extracting the real time domain change data of the boundary heat source.

[0042] 2) The present invention adopts COMSOL numerical modeling software to calculate the thermal conduction effect of non-air boundary heat sources in the target area and compensate for the target infrared radiation temperature field, which can effectively overcome the influence of the thermal conduction effect of the interfering heat source on the infrared radiation information of the bearing coal rock, avoid the erroneous trend of the infrared radiation characteristic value due to the thermal conduction effect, and ensure the authenticity of the monitoring results.

[0043] 3) The present invention can effectively enhance the manifestation of heat caused by coal rock crack expansion in the infrared radiation temperature field, laying a foundation for realizing the infrared radiation quantitative characterization of the coal rock damage evolution process, obtaining the real infrared radiation temperature change, effectively improving the early warning accuracy, and providing a guarantee for accurate early warning of infrared radiation precursors of coal rock damage and instability, which is of great significance to water resource protective mining and mine water disaster prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of the thermal conduction temperature compensation method for carrying infrared radiation response information of coal rock crack evolution according to the present invention;

[0045] Figure 2 This is a schematic diagram of the structure of the verification experiment system used in the present invention;

[0046] Figure 3 A schematic diagram of meshing using the COMSOL numerical model of the present invention;

[0047] Figure 4 The target infrared temperature matrix row average value and the heat conduction temperature matrix row average value distribution and fitting in the embodiment of the present invention;

[0048] Figure 5 The linear regression correlation coefficient variation curve in the embodiment of the present invention;

[0049] Figure 6 is the average infrared radiation temperature of the bearing coal rock before and after the heat conduction temperature compensation in the embodiment of the present invention;

[0050] Figure 7These are row average thermal images of the infrared temperature field of the bearing coal rock before and after thermal conduction compensation in the embodiment of the present invention, where (a) is the row average thermal image of the target infrared temperature matrix; (b) is the row average thermal image of the thermal conduction temperature matrix; and (c) is the row average thermal image after thermal conduction temperature compensation.

[0051] In the figure: 1. Loading coal rock; 2. Reference coal rock; 3. Loading coal rock platform; 4. Reference coal rock platform; 5. Press; 6. Infrared thermal imager; 7. Infrared data acquisition system; 8. Pressure data acquisition system. DETAILED DESCRIPTION

[0052] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings:

[0053] like Figure 1 As shown, taking the uniaxial compression test of coal rock as a specific implementation case, a thermal conduction temperature compensation method carrying infrared response information of coal rock crack damage includes the following steps:

[0054] Step 1: Infrared radiation monitoring data collection: Conduct infrared radiation observation experiments on uniaxial compression coal rock, such as Figure 2 As shown, the loaded coal rock 1 is placed on the loaded coal rock platform 3, and the reference coal rock platform 4 is set 10 cm to the left of the loaded coal rock 1, and the reference coal rock 2 is placed on it. The infrared thermal imager 6 is placed 1 m in front of the loaded coal rock 1, and the loaded coal rock and the reference coal rock are recorded at a rate of 10 frames per second. During the experiment, the press 5 is used to apply a load to the loaded coal rock 1, and the reference coal rock 2 is not applied with a load. During this period, computers 7 and 8 are used to collect the infrared radiation and pressure data of the coal rock, respectively. During the experiment, the loaded coal rock is determined as the target area for infrared radiation observation and analysis. The outlines of the loaded coal rock 1 and the reference coal rock 2 are used as boundaries, and they are resampled using rectangular data frames to obtain the target infrared temperature matrix (IRM) of the loaded coal rock 1. L ) and reference coal rock 2 reference infrared temperature matrix (IRM R ).

[0055] Step 2: Time domain noise correction of infrared radiation information of coal and rock: Calculate the time domain change value of the reference infrared temperature matrix mean value, the formula is as follows:

[0056]

[0057] Where: i and j are the row and column numbers of the reference coal rock infrared temperature matrix, x and y are the row and column numbers of the matrix, t is the time, IRM R (t) is the mean value of the reference infrared temperature matrix at time t. The target infrared temperature matrix is ​​subtracted from the mean value of the reference infrared radiation temperature matrix to obtain the target infrared temperature matrix after time domain noise correction. The formula is as follows:

[0058] IRM' L (t) = IRM L (t)-AIRM R (t)

[0059] Where: IRM' L (t) is the target infrared temperature matrix after time domain noise correction.

[0060] Step 3, extract the time domain variation data and initial temperature field data of the boundary heat source: take the target infrared temperature matrix after time domain noise correction as the object, determine the temperature matrix rows and columns corresponding to the non-air boundary at each moment as the time domain variation data of the boundary heat source. In this example, the non-air boundary of the uniaxially loaded coal rock is its upper and lower ends, then the time domain variation data of the loaded coal rock boundary heat source are the first row and the last row of the target infrared temperature matrix, as shown in the following formula:

[0061] BHS U (t) = IRM' L (1,:,t)

[0062] BHS L (t) = IRM' L (m,:,t)

[0063] Where: BHS U (t) is the upper boundary heat source of coal rock loaded at time t, BHS L (t) is the heat source loaded at the lower boundary of coal rock at time t. Then, the target infrared temperature matrix at the initial time is selected as the initial temperature field data (IRM' L (t0)).

[0064] Step 4: Obtain the thermodynamic parameters of the bearing coal rock: Based on laboratory thermodynamic experiments, determine the main thermodynamic parameters of the monitored coal rock mass, including heat capacity at normal pressure, density, thermal conductivity, thermal expansion coefficient, Young's modulus, and Poisson's ratio.

[0065] Step 5. COMSOL numerical model of the evolution of the surface temperature field of coal and rock under the influence of heat conduction: According to the actual situation of the monitoring area, a rectangular model including a solid heat transfer module is established in the COMSOL numerical software, and the grid is divided according to the number of rows and columns of the target infrared temperature matrix, where each grid node in the model corresponds to an element in the temperature matrix. After that, a time-dynamic heat source is set at the non-air boundary of the model, and an adiabatic edge is set at the air boundary. The model is as follows Figure 3 shown.

[0066] Step 6, COMSOL numerical model parameter assignment: Take the first row and first column element of the target infrared temperature matrix as the origin, and use the actual area of ​​the monitoring area to convert the coordinate values ​​of each element of the target infrared temperature matrix. Use this coordinate value as the interface, assign the initial temperature field data obtained in step 3 to the COMSOL model, and assign the boundary heat source time domain variation data obtained in step 3 to the upper and lower dynamic heat sources. Finally, input the coal and rock thermodynamic parameters obtained in step 4 into the model material properties.

[0067] Step 7, COMSOL numerical calculation process: According to the infrared thermal imager monitoring frequency, set the time step of the COMSOL numerical model transient temperature field calculation. The formula is:

[0068]

[0069] Where: ts is the time step for calculating the transient temperature field of the COMSOL numerical model, and f is the monitoring frequency of the infrared thermal imager. After that, the time domain variation process of the infrared radiation temperature field of the bearing coal rock under the influence of the boundary heat source is calculated. In this example, the monitoring frequency is 10 frames and the time step is 0.1s.

[0070] Step 8. Export the results of COMSOL numerical calculations: Set the grid spacing based on the target infrared radiation temperature matrix, and export the infrared radiation heat conduction temperature matrix data for each time step after calculation. Convert the exported bearing coal rock heat conduction temperature data into a two-dimensional matrix, recorded as the heat conduction temperature matrix (HCTM(t)), and calculate the row averages of the target infrared temperature matrix and the heat conduction temperature matrix at each moment. The formula is as follows:

[0071]

[0072] Where: AHCT(t) is the row average of the heat conduction temperature matrix, T m,n (t) is the temperature value of the mth row and nth column of the heat conduction temperature matrix, is the average value of the mth row of the thermal conduction temperature matrix. ATIT(t) is the average value of the target infrared radiation temperature matrix, T m ' ,n (t) is the temperature value of the mth row and nth column of the target infrared temperature matrix, The mth row is the average value of the target infrared temperature matrix.

[0073] Step 9, COMSOL numerical calculation result verification: Take the infrared radiation temperature matrix of the first 30% frames in the monitoring process as samples, take the target infrared temperature matrix row average as the independent variable, and the heat conduction temperature matrix row average as the dependent variable, perform a univariate linear regression operation on the two, and calculate the correlation coefficient corresponding to the linear regression at each moment, such as Figure 4 and 5Calculate the average value of the correlation coefficient at each moment. When the average value is greater than 0.95, the calculation result is valid. When the average value is less than 0.95, return to step 6, fine-tune the thermodynamic parameters in the COMSOL model, and recalculate the COMSOL numerical model.

[0074] Step 10, thermal conduction compensation of infrared radiation temperature field of bearing coal rock: subtract the target infrared radiation temperature matrix after noise correction from the thermal conduction temperature matrix to obtain the infrared radiation temperature matrix of bearing coal rock after thermal conduction temperature compensation. The formula is as follows:

[0075] CITM(t)=IRM' L (t)-HCTM(t)

[0076] Where: CITM(t) is the infrared radiation temperature matrix of the bearing coal rock after thermal conduction temperature compensation. The thermal conduction temperature compensation effect is as follows: Figure 6 and Figure 7 As shown, Figure 7 (a) in the figure shows the target infrared temperature matrix row average thermal image; (b) shows the thermal conduction temperature matrix row average thermal image; (c) shows the thermal conduction temperature compensation row average thermal image. This method can effectively reduce the influence of environmental heat sources on the infrared radiation variation law, so that the infrared characteristic value shows a real variation trend. In addition, this method can effectively enhance the infrared radiation anomaly during the evolution of coal and rock cracks, which is helpful for the accurate identification of infrared radiation precursors of rock damage.

Claims

1. A thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage, characterized in that: The steps include: Step 1: Collect infrared radiation monitoring data of bearing coal rock: set reference coal rock of the same type as the bearing coal rock within one meter of the bearing coal rock in the area to be detected, and use an infrared thermal imager to simultaneously monitor the infrared radiation information of the bearing and reference coal rock surfaces; Step 2, correcting the time domain noise of the infrared radiation information of the coal rock: using the mean value of the reference infrared temperature matrix to perform time domain noise correction on the target infrared temperature matrix obtained by the infrared thermal imager, and obtaining the target infrared temperature matrix after time domain noise correction; The time domain noise correction method for the infrared radiation of coal rock is to calculate the time domain change value of the reference infrared temperature matrix mean, and the formula is as follows: Where: AIRM R (t) is the time domain variation value of the reference infrared temperature matrix mean, i and j are the row and column numbers of the reference coal rock infrared temperature matrix, x and y are the matrix row and column numbers, t is time, IRM R (t) is the mean value of the reference infrared temperature matrix at time t; The target infrared temperature matrix is ​​subtracted from the mean of the reference infrared radiation temperature matrix to obtain the target infrared temperature matrix after time domain noise correction. The formula is as follows: IRM' L (t)=IRM L (t)-ARMS R (t) Where: IRM' L (t) is the target infrared temperature matrix after time domain noise correction; Step 3: Use an infrared thermal imager to collect information to obtain the time domain variation data and initial temperature field data of the interfering heat source bearing the coal-rock boundary: Take the target infrared radiation temperature matrix after time domain noise correction as the object, and determine the time domain variation data and initial temperature field data of the heat source bearing the coal-rock boundary; Step 4: Obtaining thermodynamic parameters of the bearing coal rock: Based on laboratory thermodynamic experiments, determine the thermodynamic parameters of the monitored coal rock mass, including: heat capacity at normal pressure, density, thermal conductivity, thermal expansion coefficient, Young's modulus and Poisson's ratio; Step 5, establish a COMSOL rectangular model of the evolution of the coal rock surface temperature field under the influence of heat conduction: according to the actual situation of the monitoring area, use COMSOL numerical software to establish a rectangular model of the coal rock heat transfer module, wherein a grid divided by the number of rows and columns of the infrared temperature matrix is ​​provided in the rectangular model; Step 6, assigning parameters to the COMSOL rectangular model: assigning the initial temperature field data obtained in step 3 to the COMSOL rectangular model, assigning the boundary heat source time domain variation data obtained in step 3 to the dynamic heat source of the COMSOL rectangular model, and inputting the coal rock thermodynamic parameters obtained in step 4 as material properties into the COMSOL rectangular model; Step 7, COMSOL numerical calculation process: according to the monitoring frequency of the infrared thermal imager, set the time step of the transient temperature field calculation of the COMSOL rectangular model, and calculate the time domain variation process of the infrared radiation temperature field of the bearing coal rock under the influence of the boundary heat source; Step 8, export the numerical calculation results of the COMSOL rectangular model: set the grid spacing based on the target infrared radiation temperature matrix, export the infrared radiation heat conduction temperature matrix data of each time step obtained by the COMSOL rectangular model calculation, convert the exported bearing coal rock heat conduction temperature data into a two-dimensional matrix, record it as the heat conduction temperature matrix HCTM(t), and calculate the row averages of the target infrared temperature matrix and the heat conduction temperature matrix at each moment; Step 9, verify the COMSOL numerical calculation results: take the infrared radiation temperature matrix of the first 30% frames in the monitoring process as samples, take the target infrared temperature matrix row average as the independent variable, and the heat conduction temperature matrix row average as the dependent variable, perform a univariate linear regression operation on the target infrared temperature matrix row average and the heat conduction temperature matrix row average, and calculate the correlation coefficient of each frame of experimental data and simulation data, and use the average value of the correlation coefficient at each moment to verify the numerical calculation results of the COMSOL rectangular model; Step 10, thermal conduction compensation of the infrared radiation temperature field of the bearing coal rock: subtract the target infrared radiation temperature matrix after noise correction from the thermal conduction temperature matrix to obtain the bearing coal rock infrared radiation temperature matrix after thermal conduction temperature compensation, and use the bearing coal rock infrared radiation temperature matrix to perform thermal conduction temperature compensation on the infrared radiation response information of the bearing coal rock, thereby effectively reducing the influence of environmental heat sources on the changing law of infrared radiation, making the infrared radiation information present a real changing trend, amplifying the abnormal infrared radiation response at the moment of coal rock crack damage, realizing infrared quantitative characterization of coal rock damage evolution and infrared precise identification of damage precursors, providing safety guarantees for water resource protective mining and mine water hazard prevention and control.

2. A thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1, characterized in that: The method for collecting infrared radiation monitoring data of the loaded coal rock described in step 1 is: resampling the loaded coal rock and the reference coal rock using rectangular data frames of the same size to obtain the target infrared temperature matrix IRM of the loaded coal rock L And reference coal rock reference infrared temperature matrix IRM R .

3. A thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1, characterized in that: The method for extracting the time domain variation data and initial temperature field data of the boundary heat source is as follows: determine the non-airborne boundary of the target infrared temperature matrix after time domain noise correction, and the temperature matrix rows and columns corresponding to the non-airborne boundary are the time domain variation data of the boundary heat source, as shown in the following formula: BHS U (t)=IRM' L (1,:,t) BHS L (t)=IRM' L (m,:,t) Where: BHS U (t) is the heat source on the air boundary of the coal rock at time t, BHS L (t) is the heat source loaded at the air boundary under the coal rock at time t; then, the target infrared temperature matrix at the initial time is selected as the initial temperature field data IRM' L (t0).

4. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1 is characterized in that: The COMSOL rectangular model establishment method described in step 5 is: establish a rectangular rock material model including a heat conduction module in COMSOL, divide the rectangular rock material model into grids according to the number of rows and columns of the target infrared temperature matrix, and each grid node in the rectangular rock material model corresponds to an element in the temperature matrix; then, set a time dynamic heat source assigned by the detection result at the non-air boundary of the rectangular rock material model, the dynamic heat source changes with time, and the air boundary is set as thermal insulation, so as to calculate the heat conduction result of the same scale as the infrared temperature matrix obtained by monitoring.

5. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1 is characterized in that: The COMSOL rectangular model parameter assignment method described in step 6 is: taking the first row and first column element of the target infrared temperature matrix as the origin, and using the actual area of ​​the monitoring area to convert the coordinate values ​​of each element of the target infrared temperature matrix; assigning the initial temperature field data obtained in step 3 to the grid corresponding to the coordinate value in the COMSOL rectangular model, and assigning the boundary heat source time domain change data obtained in step 3 to the dynamic heat source of the model.

6. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1 is characterized in that: The formula for the time step of the transient temperature field calculation of the COMSOL rectangular model described in step 7 is: Where: ts is the calculation time step of the transient temperature field of the COMSOL numerical model, and f is the monitoring frequency of the infrared thermal imager.

7. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1 is characterized in that: The target infrared temperature matrix and the heat conduction temperature matrix row average calculation formula described in step 8 are as follows: Where: AHCT(t) is the row average of the heat conduction temperature matrix, T m,n (t) is the temperature value of the mth row and nth column of the heat conduction temperature matrix, is the row average of the mth row of the thermal conduction temperature matrix; ATIT(t) is the row average of the target infrared radiation temperature matrix, T m ' ,n (t) is the temperature value of the mth row and nth column of the target infrared temperature matrix, The mth row is the average value of the target infrared temperature matrix.

8. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1 is characterized in that: The COMSOL numerical calculation result verification method described in step 9 is: set the judgment threshold to 0.95, calculate the average value of the correlation coefficient corresponding to the linear regression at each moment, and when the average value is greater than the preset value of 0.95, the calculation result is valid; when the average value is less than the preset value of 0.95, return to step 6, within the material parameter error range, fine-tune the thermodynamic parameters in the COMSOL model, and recalculate the COMSOL numerical model until the average value of the correlation coefficient is greater than the preset value of 0.

95.

9. The thermal conduction temperature compensation method for carrying infrared response information of coal rock crack damage according to claim 1, characterized in that: The heat conduction compensation formula for the infrared radiation temperature field of the bearing coal rock used in step 10 is as follows: CITM(t)=IRM' L (t)-HCTM(t) Where: CITM(t) is the infrared radiation temperature matrix of the bearing coal rock after thermal conduction temperature compensation.

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