Online infrared thermography characterization method and system for coal spontaneous combustion characteristics and material performance

Abstract

The invention provides an on-line infrared thermography characterization method and system for coal spontaneous combustion characteristics and material performance, and belongs to the technical field of coal spontaneous combustion fire prevention and control and material performance characterization, the method comprises the following steps: obtaining combustion data of a target coal type, the combustion data comprising a plurality of color value sets, combustion temperature data and combustion time data of the target coal type; determining a first function and a second function based on the combustion data, the first function being a function that the first data varies with the combustion temperature data, the second function being a function that the second data varies with the combustion time data, the first data comprising a plurality of color data values and the combustion time data, the second data comprising a plurality of color value sets and the combustion temperature data; and determining the combustion state of the target coal type based on the first function and the second function. According to the online infrared thermography characterization method and system for the coal spontaneous combustion characteristics and the material performance, the coal spontaneous combustion characteristics and the material performance can be studied, and combustion early warning can be conducted.

Description

Technical Field

[0001] This application belongs to the field of coal spontaneous combustion fire prevention and material performance characterization technology, and more specifically, it relates to an online infrared thermographic characterization method and system for coal spontaneous combustion characteristics and material performance. Background Technology

[0002] Coal spontaneous combustion is one of the major hazards in coal mining, seriously threatening safe production in coal mines. In recent years, with the development of new testing technologies, methods such as temperature monitoring, gas detection, and quantum chemical calculations have been gradually applied by researchers in related studies. However, the monitoring of precursory information for coal spontaneous combustion is easily affected by the underground environment. Therefore, it is essential to determine the type of coal in a coal mine and to provide early warning of combustion. Summary of the Invention

[0003] The purpose of this application is to provide an online infrared thermographic characterization method and system for the spontaneous combustion characteristics and material properties of coal, so as to study the spontaneous combustion characteristics and material properties of coal and to provide early warning of combustion.

[0004] A first aspect of this application provides an online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal, including: Obtain combustion data for the target coal type, including multiple color value sets, combustion temperature data, and combustion time data for the target coal type; The first function and the second function are determined based on the combustion data. The first function is a function of the first data changing with the combustion temperature data, and the second function is a function of the second data changing with the combustion time data. The first data includes multiple color data values ​​and combustion time data, and the second data includes multiple color value sets and combustion temperature data. The combustion state of the target coal type is determined based on the first and second functions.

[0005] A second aspect of this application provides an online infrared thermal imaging characterization system for the spontaneous combustion characteristics and material properties of coal, including: The data acquisition module is used to acquire combustion data of the target coal type. The combustion data includes multiple color value sets, combustion temperature data, and combustion time data of the target coal type. The function determination module is used to determine a first function and a second function based on combustion data. The first function is a function that changes the first data with the combustion temperature data, and the second function is a function that changes the second data with the combustion time data. The first data includes multiple color data values ​​and combustion time data, and the second data includes multiple color value sets and combustion temperature data. The combustion state determination module is used to determine the combustion state of the target coal type based on the first function and the second function.

[0006] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the above-described online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal.

[0007] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal.

[0008] The beneficial effects of the online infrared thermographic characterization method and system for coal spontaneous combustion characteristics and material properties provided in this application are as follows: This application obtains combustion data of the target coal type, generates curves showing the changes of R, G, B, and RGB values ​​with time and temperature, and analyzes the variation patterns of the curves segment by segment to obtain functions for the corresponding intervals. This allows for the acquisition of combustion state data of the target coal type at different times and temperatures, and in-depth analysis of its combustion characteristics and evolution trends. This enables dynamic monitoring and accurate prediction of coal spontaneous combustion risks, providing timely and effective risk prevention and control guidance for coal mine safety production, significantly reducing the probability of coal spontaneous combustion disasters during coal mining, and comprehensively ensuring the safety and stability of coal mining operations. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart of an online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal provided in an embodiment of this application; Figure 2 A schematic flowchart illustrating the online infrared thermographic characterization system and method for the spontaneous combustion characteristics and material properties of coal provided in the embodiments of this disclosure; Figure 3 The temperature curves of coal samples and the programmed temperature curves during the heating process of lignite; Figure 4 The curve is a fitting curve for the exponential function of the coal sample temperature; Figure 5 The curves show the changes in heating time and R value of lignite as a function of coal sample temperature. Figure 6 The curves show the changes in temperature and R-value of lignite as a function of heating time. Figure 7The variation of R-value of lignite with temperature and its fitting curve (31.2 ℃~55.3 ℃); Figure 8 The variation of R value of lignite with time and the fitted curve (5 min~42 min); Figure 9 The variation of R-value of lignite with temperature and its fitting curve (90.8 ℃~474.2 ℃) are shown. Figure 10 The variation of R value of lignite with time and the fitting curve (81 min~105 min). Figure 11 The curves showing the relationship between the heating time and G value of lignite and the temperature of the coal sample are shown. Figure 12 The curves show the changes in temperature and G value of lignite with the heating time of the coal sample; Figure 13 The variation of G value of lignite with temperature and the fitting curve (30 ℃~249.2 ℃); Figure 14 The variation law of G value of lignite with time and the fitting curve (5 min~78 min). Figure 15 The variation of G value of lignite with time and the fitted curve (78 min~101 min). Figure 16 The variation of G value of lignite with temperature and the fitting curve (249.2 ℃~474.2 ℃); Figure 17 The variation of G value of lignite with time and the fitting curve (101 min~105 min). Figure 18 The curves showing the relationship between the heating time and B value of lignite and the temperature of the coal sample are presented. Figure 19 The curves show the changes in temperature and B value of lignite as a function of heating time. Figure 20 The variation of B value of lignite with temperature and the fitted curve (31.2 ℃~55.3 ℃); Figure 21 The variation of B value of lignite over time and the fitted curve (5 min~42 min). Figure 22 The variation of B value of lignite with temperature and the fitted curve (90.8 ℃~474.2 ℃); Figure 23 The variation of B value of lignite over time and the fitted curve (81 min~105 min). Figure 24 The curves showing the relationship between the heating time and RGB values ​​of lignite and the temperature of the coal sample are presented. Figure 25 The curves show the changes in temperature and RGB values ​​of lignite as a function of heating time. Figure 26 A structural block diagram of an online infrared thermographic characterization system for the spontaneous combustion characteristics and material properties of coal provided in an embodiment of this application; Figure 27 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0011] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0013] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating an online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal provided in an embodiment of this application. The method may include: S101: Obtain combustion data for the target coal type. The combustion data includes multiple color value sets, combustion temperature data, and combustion time data for the target coal type.

[0014] In this embodiment, the target coal is subjected to combustion, and combustion data of the target coal is obtained.

[0015] For example, the target coal is programmed to heat up, and an infrared thermal imager is used to capture online infrared thermal video of the target coal. This video is then connected to software to acquire combustion data of the target coal. The combustion data includes multiple color value sets, combustion temperature data, and combustion time data for the target coal.

[0016] In this embodiment, the multiple color value sets include: R value value set, G value value set, B value value set and RGB value value set; the combustion temperature data includes: coal type temperature and program temperature; the combustion time data includes: coal type heating time.

[0017] For example, the measured R, G, B and RGB values ​​are the average values ​​of a 100×100 pixel matrix, and each is represented by 5 significant digits.

[0018] In this embodiment, in order to ensure the timeliness of the target coal and prevent the target coal from deteriorating due to prolonged storage and affecting the experimental results, the experimental testing was completed within 48 hours after the coal sample of the target coal was prepared.

[0019] For example, the coal sample is kept at an initial temperature of 30°C for 5 minutes to stabilize the initial temperature; then the experimental coal sample is heated at a heating rate of 2°C / min, with the maximum programmed temperature set to 500°C.

[0020] S102: Determine a first function and a second function based on combustion data. The first function is a function of the first data changing with combustion temperature data, and the second function is a function of the second data changing with combustion time data. The first data includes multiple color data values ​​and combustion time data, and the second data includes multiple color value sets and combustion temperature data.

[0021] In this embodiment, before determining the first function and the second function based on combustion data, it is also necessary to obtain the coal temperature curve and the programmed temperature curve during the heating process of the target coal.

[0022] For example, the acquired coal temperature data and programmed temperature data can be input into curve generation software to obtain curves of coal temperature and programmed temperature. Specifically, Tableau or MATLAB software can be used to generate curves of coal temperature and programmed temperature changing over time, such as... Figure 3 As shown.

[0023] In this embodiment, the curves of coal temperature and programmed temperature changing over time are analyzed, and corresponding fitting curves and functions are obtained.

[0024] For example, from Figure 3 It can be seen that the programmed temperature was increased at a rate of 2℃ / min. The coal temperature and the programmed temperature intersected at 231.2℃ (100.6 min). Before 231.2℃, the coal temperature was consistently lower than the programmed temperature, and after 231.2℃, it was higher. Throughout the heating process, the coal temperature followed an exponential function relationship with time. In this embodiment, the coal temperature curve was fitted to obtain a fitted curve, as shown below. Figure 3 As shown; simultaneously, the corresponding functional relationship of the coal type temperature fitting curve was obtained:

[0025] Where y is the temperature of the lignite sample in °C; x is the heating time of the lignite in min; A1 and t1 are constants, dimensionless; and y0 is the initial temperature of the lignite in °C.

[0026] For the lignite coal type selected in this application, the constant A1 = 3.0240 × 10-5 Given t1 = 6.3838 and y0 = 55.586, the functional relationship between the temperature of lignite and time is:

[0027] Where y is the temperature of the lignite sample in °C; and x is the heating time of the lignite in min.

[0028] In this embodiment, a first curve is determined based on the first data and the coal temperature, a first fitted curve is determined based on the first curve, and a first function is determined based on the first fitted curve; a second curve is determined based on the second data and the coal heating time, a second fitted curve is determined based on the second curve, and a second function is determined based on the second fitted curve.

[0029] For example, the first curve includes: the curve of coal heating time and multiple color value sets changing with coal temperature; the second curve includes: the curve of coal temperature and multiple color value sets changing with combustion time; the first fitting curve includes: the fitting curve of multiple color value sets of lignite changing with time in different time ranges; the second fitting curve includes: the fitting curve of multiple color value sets of lignite changing with programmed temperature in different temperature ranges.

[0030] S103: Determine the combustion state of the target coal type based on the first function and the second function.

[0031] In this embodiment, the S101-S102 method is used to operate on the target coal type to obtain the first function and the second function of the target coal type. By analyzing the relationship between the first function and the second function, the regularity and fitting curve of each stage of the target coal type can be obtained. Based on the regularity of each stage, the corresponding temperature range can be found, that is, the combustion state of the target coal type can be determined.

[0032] As can be seen from the above, this application obtains combustion data of the target coal type, generates curves showing the changes of the corresponding R, G, B, and RGB values ​​with time and temperature, analyzes the changing patterns of the curves segment by segment, obtains functions for the corresponding intervals, and thus obtains combustion state data of the target coal type at different times and temperatures. Furthermore, it deeply analyzes its combustion characteristics and evolution trends, achieving dynamic monitoring and accurate prediction of coal spontaneous combustion risks. This provides timely and effective risk prevention and control guidance for coal mine safety production, significantly reduces the probability of coal spontaneous combustion disasters during coal mining, and comprehensively ensures the safety and stability of coal mining operations.

[0033] In one embodiment of this application, the multiple color value sets include: R value value set, G value value set, B value value set and RGB value value set; the combustion temperature data includes: coal type temperature and programmed temperature; the combustion time data includes: coal type heating time.

[0034] In this embodiment, the R value represents the intensity or brightness of the red component in the color, the G value represents the intensity or brightness of the green component in the color, and the B value represents the intensity or brightness of the blue component in the color. RGB values ​​are an additive color model that represents all colors by mixing different intensities of the three primary colors: red, green, and blue.

[0035] For example, combustion data is obtained by performing combustion treatment on the target coal type, resulting in the R value set, G value set, B value set, RGB value set, coal temperature, coal heating time, and programmed temperature of the target coal type during the experiment.

[0036] As can be seen from the above, obtaining combustion data of the target coal type can comprehensively capture the intrinsic changes during coal combustion. Combined with temperature and time data, the intrinsic changes of the experimental sample during the heating process can be discovered, and more information can be obtained more easily, thus providing data support for the study of the mechanism of coal or materials.

[0037] In one embodiment of this application, determining a first function and a second function based on combustion data includes: A first curve is determined based on the first data and the coal type temperature, and a first function is determined based on the first curve. The second curve is determined based on the second data and the coal type's heating time, and the second function is determined based on the second curve.

[0038] In this embodiment, the first data includes: multiple color data values ​​and combustion time data; the second data includes: multiple color value sets and combustion temperature data; the first curve includes: coal heating time and multiple color value sets as a function of coal temperature; the second curve includes: coal temperature and multiple color value sets as a function of coal heating time.

[0039] For example, the first data and coal temperature data can be input into Tableau or MATLAB software to generate the corresponding first curve, and the second data and coal heating time data can be input into Tableau or MATLAB software to generate the corresponding second curve.

[0040] In this embodiment, the first curve and the second curve are input into the fitting software to obtain the corresponding first function and second function.

[0041] For example, the first and second curves of the target coal type can be input into MATLAB or Origin software. The functional relationship between the first and second functions, as well as the corresponding functional relationship parameters, can be directly viewed in the results.

[0042] As can be seen from the above, this application obtains combustion data of the target coal type, then determines the first curve and the second curve, and then inputs the first curve and the second curve into fitting software to obtain the corresponding first function, second function and their related parameters. This series of operations accurately captures the key features and changing patterns in the coal combustion process, laying a solid data foundation for subsequent analysis of the inherent regularity of coal spontaneous combustion through curve analysis.

[0043] In one embodiment of this application, determining the first function based on the first curve includes: A first fitting curve is determined based on the first curve, and a first function is determined based on the first fitting curve. The first fitting curve is a fitting curve of multiple color value sets as the program temperature changes.

[0044] In this embodiment, the first fitting curve includes: a fitting curve of the change of multiple color values ​​of lignite over time in different time ranges, and the first fitting curve is obtained by inputting the first curve into the fitting software.

[0045] For example, the first curve can be input into MATLAB or Origin software to display the fitting results in real time and obtain the first fitted curve.

[0046] In this embodiment, the first fitted curve specifically includes: Figure 8 The variation of R-value of lignite over time and its fitting curve (5 min ~ 42 min). Figure 10 The variation of R-value of lignite over time and its fitting curve (81 min ~ 105 min). Figure 14 The variation of G value of lignite over time and its fitting curve (5 min ~ 78 min). Figure 15 The variation of G value of lignite with time and the fitting curve (78 min ~ 101 min) Figure 17 The variation of G value of lignite with time and the fitting curve (101 min ~ 105 min) Figure 21 The variation law of lignite B value with time and the fitting curve (5min~42min) and Figure 23 The variation of B value of lignite with time and the fitted curve (81min~105min) are shown.

[0047] For example, the first fitted curve uses time as the independent variable. In the first stage of the R-value change over time, within the time period of 5 min to 42 min, the R-value exhibits an approximately parabolic relationship with time. Fitting the R-value curve for this time period yields the fitted curve of the lignite R-value from 5 min to 42 min, as shown below. Figure 8 As shown, the functional relationship between the R value and time from 5 min to 42 min was obtained as follows:

[0048] Where y is the R value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B1, B2, and B3 are coefficients.

[0049] For the selected lignite type, the constant term A = 7.4470; coefficients B1 = 15.250, B2 = -0.56764, and B3 = 4.7600 × 10⁻⁶. -3 The functional relationship between the R value of lignite and the heating time is as follows:

[0050] Where y is the R value, which is dimensionless; and x is the heating time, in minutes.

[0051] In the second stage of the R-value change over time, during the period from 42 min to 81 min, the R-value of lignite is approximately unchanged. That is, the R-value of lignite approaches 0 and remains stable within the period from 42 min to 81 min, with basically no change. This is the change law of the R-value of lignite during the second stage of the critical transformation process of oxidation and spontaneous combustion.

[0052] In the third stage of the R-value change over time, during the period from 81 min to 105 min, the R-value of lignite exhibits an approximately parabolic relationship with time. This embodiment obtains the fitted curve of the R-value for lignite from 81 min to 105 min by fitting the curve for this period, as shown below. Figure 10 As shown, the functional relationship between the R value and time from 81 min to 105 min was also obtained:

[0053] Where y is the R value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B1, B2, and B3 are coefficients.

[0054] For the lignite sample selected in the experiment, with constant term A = 39452; coefficients B1 = -1329.8, B2 = 14.781, and B3 = -0.054030, the functional relationship between the lignite R value and the heating time is as follows:

[0055] Where y is the R value, which is dimensionless; and x is the heating time, in minutes.

[0056] The first stage of the G-value change over time corresponds to the time period of 5 min to 101 min. Within the time period of 5 min to 78 min, the G-value of lignite exhibits an approximately parabolic relationship with the heating time. Fitting the G-value curve for this time period yields the fitted curve of the lignite G-value from 5 min to 101 min, as shown below. Figure 14As shown, the functional relationship between the G value and time from 5 min to 101 min was obtained as follows:

[0057] Where y is the G value, dimensionless; x is the heating time, in min; A is a constant term; B1, B2, and B3 are coefficients.

[0058] For the selected lignite type, the constant term A = 152.27; coefficients B1 = 5.0761, B2 = -0.18933, and B3 = 1.5100 × 10⁻⁶. -3 The functional relationship between the G value of lignite and the heating time is:

[0059] Where y is the G value, which is dimensionless; and x is the heating time, in minutes.

[0060] Within the time period of 78 min to 95 min, the G-value of lignite showed a linear relationship with the heating time. Fitting the G-value curve within this time period yielded the fitted curve for the lignite G-value from 78 min to 95 min, as shown below. Figure 15 As shown, the functional relationship between the G value and time from 78 min to 95 min was obtained as follows:

[0061] Where y is the G value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B is a coefficient.

[0062] For the selected lignite type, the constant term A = -349.25; the coefficient B = 5.9334. Therefore, the functional relationship between the lignite's G value and the heating time is:

[0063] Where y is the G value, which is dimensionless; and x is the heating time, in minutes.

[0064] Within the time period of 95 min to 101 min, the G-value of lignite showed a linear relationship with the heating time. Fitting the G-value curve for this time period yielded the following fitted curve for the lignite G-value from 95 min to 101 min: Figure 15 As shown, the functional relationship between the G value and time from 95 min to 101 min was obtained as follows:

[0065] Where y is the G value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B is a coefficient.

[0066] For the selected lignite type, the constant term A = 3932.4; the coefficient B = -38.361. Therefore, the functional relationship between the lignite's G value and the heating time is:

[0067] Where y is the G value, which is dimensionless; and x is the heating time, in minutes.

[0068] The second stage of the G-value change over time corresponds to the time period of 101 min to 105 min. During this time period, the G-value of lignite shows a linear relationship with the heating time. Fitting the G-value curve for this time period yields the fitted curve of the lignite G-value from 101 min to 105 min, as shown below. Figure 17 As shown, the functional relationship between the G value and time from 101 min to 105 min was obtained as follows:

[0069] Where y is the G value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B is a coefficient.

[0070] For the selected lignite type, the constant term A = -749.73; the coefficient B = 8.0683. Therefore, the functional relationship between the lignite's G value and the heating time is:

[0071] Where y is the G value, which is dimensionless; and x is the heating time, in minutes.

[0072] The first stage of the B-value change over time corresponds to the time period of 5 min to 42 min. During this period, the B-value of lignite exhibits an approximately parabolic relationship with the heating time. Fitting the B-value curve for this time period yields the fitted curve of the lignite B-value from 5 min to 42 min, as shown below. Figure 21 As shown, the functional relationship between the B value and time from 5 min to 42 min was obtained as follows:

[0073] Where y is the B value, dimensionless; x is the heating time, in min; A is a constant term; B1, B2, B3, and B4 are coefficients.

[0074] For the selected lignite type, the constant term A = 155.85; coefficients B1 = -21.611, B2 = 1.2828, B3 = -0.035270, and B4 = 4.1890 × 10⁻⁶. -4 The functional relationship between the B value of lignite and the heating time is as follows:

[0075] Where y is the B value, which is dimensionless; and x is the heating time, in minutes.

[0076] The second stage of the change of B value over time corresponds to the time period of 42 min to 81 min. This stage is consistent with the second stage of the R value of lignite in terms of time and temperature range. During this stage, the fluctuation range of the B value of lignite is relatively small and remains relatively stable.

[0077] The third stage of the B-value change over time corresponds to the time period of 81 min to 105 min. During this period, the B-value of lignite exhibits an approximately parabolic relationship with the heating time. Fitting the B-value curve for this time period yields the fitted curve for the lignite B-value from 81 min to 105 min, as shown below. Figure 23 As shown, the functional relationship between the B value and time from 81 min to 105 min was obtained as follows:

[0078] Where y is the B value, which is dimensionless; x is the heating time, in minutes; A is a constant term; and B1 and B2 are coefficients.

[0079] For the selected lignite type, the constant term A = 9492.0; coefficients B1 = -200.42, B2 = 1.0588. The functional relationship between the lignite B value and heating time is then:

[0080] Where y is the B value, which is dimensionless; and x is the heating time, in minutes.

[0081] Based on the above exemplary explanation of the first fitted curve, we can conclude that: regarding the change of R value, during the process of lignite from oxidation heat storage to combustion criticality, the R value first fluctuates with time up to 42 min, and between 42 min and 81 min, the R value basically approaches 0. Subsequently, it rises sharply with time and approaches the maximum value of 255, until it basically stops changing. Regarding the changes in the G-value, from the 78-minute mark up to the 78-minute mark, the G-value exhibits an approximately parabolic relationship with time, decreasing to 93.59, reaching a trough. From 78 to 95 minutes, the G-value of lignite shows a linear relationship with time, with the G-value rising sharply from 93.59 to 212.45, reaching a peak. From 95 to 101 minutes, the G-value of lignite shows a linear relationship with the heating time, with the G-value rapidly decreasing from 212.45 to 64.42, reaching a trough. Finally, from 101 to 105 minutes, the G-value of lignite shows a linear relationship with the heating time, with the G-value slowly increasing from 64.42 to 96.59. Regarding the changes in the B value, the B value of lignite first decreased to a peak and then gradually increased after 42 minutes. After that, the B value fluctuated less in the next 81 minutes, mostly fluctuating between 210 and 220, remaining relatively stable. Then, until 105 minutes, the B value first decreased to a peak and then increased, showing an approximately parabolic relationship.

[0082] As can be seen from the above, the R, G, and B values ​​of the experimental lignite coal type show certain regularity, which can provide data for mine monitoring and provide a basis for subsequent coal type classification and coal spontaneous combustion early warning.

[0083] In one embodiment of this application, determining the second function based on the second curve includes: The second fitting curve is determined based on the second curve, and the second function is determined based on the second fitting curve. The second fitting curve is a fitting curve of multiple color value sets changing with the heating time of coal type.

[0084] In this embodiment, the second fitting curve includes: a fitting curve of multiple color numerical values ​​of lignite changing with the program temperature in different temperature ranges, and the second curve is input into the fitting software to obtain the second fitting curve.

[0085] For example, the second curve can be input into MATLAB or Origin software to display the fitting results in real time and obtain the second fitted curve.

[0086] In this embodiment, the second fitted curve specifically includes: Figure 7 The variation of R-value of lignite with temperature and its fitting curve (31.2℃~55.3℃). Figure 9 The variation of R-value of lignite with temperature and its fitting curve (90.8℃~474.2℃). Figure 13The variation law and fitting curve of G value of lignite with temperature (30℃~249.2℃) Figure 16 The variation of G-value of lignite with temperature and its fitting curve (249.2℃~474.2℃). Figure 20 The variation of lignite B-value with temperature and its fitting curve (31.2℃~55.3℃) and Figure 22 The variation of B value of lignite with temperature and its fitting curve (90.8℃~474.2℃).

[0087] For example, the second fitted curve uses temperature as the independent variable. In the first stage of the R-value change with temperature, within the temperature range of 31.2℃ to 55.3℃, the R-value exhibits an approximately parabolic relationship with temperature. Fitting the R-value curve within this temperature range yields the fitted curve of the lignite R-value from 31.2℃ to 55.3℃, as shown below. Figure 7 As shown, the functional relationship between the R value and temperature within the range of 31.2℃ to 55.3℃ was obtained as follows:

[0088] Where y is the R value, which is dimensionless; x is the temperature of lignite, in °C; A is a constant term; and B1, B2, and B3 are coefficients.

[0089] For the selected lignite type, the constant term A = 110.30; coefficients B1 = -21.438, B2 = 1.0390, and B3 = -0.012360. Therefore, the functional relationship between the lignite's R value and temperature is:

[0090] Where y is the R value, which is dimensionless; x is the temperature of lignite, in °C.

[0091] In the second stage of the R-value change with temperature, within the temperature range of 55.3℃ to 90.8℃, the R-value of lignite is approximately unchanged. That is, the R-value of lignite approaches 0 within the temperature range of 55.3℃ to 90.8℃, remaining stable and basically unchanged. This is the change law of the R-value of lignite during the second stage of the critical transformation process of oxidation and spontaneous combustion.

[0092] The third stage of the R-value change with temperature corresponds to a temperature range of 90.8℃ to 474.2℃. Within the temperature range of 90.8℃ to 149℃, the R-value of lignite exhibits a linear relationship with temperature. This embodiment obtains the fitted curve of the R-value of lignite from 90.8℃ to 474.2℃ by fitting the R-value curve within this temperature range, as shown below. Figure 9 As shown, the functional relationship between the R value and temperature within the range of 90.8℃ to 474.2℃ was also obtained:

[0093] Where y is the R value, which is dimensionless; x is the temperature of lignite, in °C; A is a constant term; and B is a coefficient.

[0094] For the selected lignite type, the constant term A = -432.92; the coefficient B = 4.6994. Therefore, the functional relationship between the lignite R value and temperature is:

[0095] Where y is the R value, which is dimensionless; x is the temperature of lignite, in °C.

[0096] Within the temperature range of 149℃ to 474.2℃, the temperature of lignite increases sharply, but the R value of lignite remains basically unchanged. That is, the R value of lignite approaches the maximum value of 255 within the temperature range of 149℃ to 474.2℃ and remains stable with basically no change.

[0097] In the first stage of the G-value variation with temperature, within the temperature range of 31.2℃ to 249.2℃, the G-value exhibits an approximately polynomial relationship with temperature. Fitting the G-value curve within this temperature range yields the fitted graph of the lignite G-value from 31.2℃ to 249.2℃, as shown below. Figure 13 As shown, the functional relationship between the G value and temperature within the range of 31.2℃ to 249.2℃ was obtained as follows:

[0098] Where y is the R value, dimensionless; x is the temperature of lignite, in °C; A is a constant term; and B1, B2, B3, B4, B5, B6, and B7 are coefficients.

[0099] For the selected lignite type, the constant term A = -2274.1; coefficients B1 = -204.37, B2 = -6.5397, B3 = 0.10487, and B4 = -9.3532 × 10⁻⁶. -4 B5 = 4.7410 × 10 -6 B6 = -1.2840 × 10 -8 B7 = -1.4467 × 10 -11 The functional relationship between the G value of lignite and temperature is:

[0100] Where y is the R value, which is dimensionless; x is the temperature of lignite, in °C.

[0101] In the second stage of the G-value variation with temperature, within the temperature range of 249.2℃-474.2℃, the G-value exhibits an approximately parabolic relationship with temperature. Fitting the G-value curve within this temperature range yields the fitted graph of the lignite G-value from 249.2℃ to 474.2℃, as shown below. Figure 16As shown, the functional relationship between the G value and temperature within the range of 249.2℃-474.2℃ was obtained as follows:

[0102] Where y is the G value, dimensionless; x is the temperature of lignite, in °C; A is a constant term; B1 and B2 are coefficients.

[0103] For the selected lignite type, the constant term A = 61.335; coefficients B1 = -0.051770, B2 = 2.6259 × 10 -4 The functional relationship between the G value of lignite and temperature is:

[0104] Where y is the G value, which is dimensionless; x is the temperature of lignite, in °C.

[0105] In the first stage of the B-value variation with temperature, within the temperature range of 31.2℃ to 55.3℃, the B-value exhibits an approximately parabolic relationship with temperature. Fitting the B-value curve within this temperature range yields the fitted curve for lignite's B-value in the 31.2℃ to 55.3℃ range, as shown below. Figure 20 As shown, the functional relationship between the B value and temperature within the range of 249.2℃-474.2℃ was obtained as follows:

[0106] Where y is the B value, dimensionless; x is the temperature of lignite, in °C; A is a constant term; B1, B2, B3, and B4 are coefficients.

[0107] For the selected lignite coal type, the constant term A = 15844; coefficients B1 = -1524.3, B2 = 54.953, B3 = -087829, B4 = 5.2500 × 10⁻⁶. -3 The functional relationship between the B value of lignite and temperature is:

[0108] Where y is the B value, which is dimensionless; x is the temperature of lignite, in °C.

[0109] The second stage of the change in B value with temperature, within the temperature range of 55.3℃ to 90.8℃, is consistent with the second stage of the R value of lignite in terms of temperature range. That is, the B value of lignite remains relatively stable in the temperature range of 55.3℃ to 90.8℃, with a small change range.

[0110] In the third stage of the B-value variation with temperature, within the temperature range of 90.8℃ to 474.2℃, the B-value exhibits an approximately polynomial relationship with temperature. Fitting the B-value curve within this temperature range yields the fitted curve for lignite's B-value in the 90.8℃ to 474.2℃ range, as shown below. Figure 22 As shown, the functional relationship between the B value and temperature within the range of 90.8℃ to 474.2℃ was obtained as follows:

[0111] Where y is the B value, dimensionless; x is the temperature of lignite, in °C; A is a constant term; B1, B2, B3, B4, B5, and B6 are coefficients.

[0112] For the selected lignite type, the constant term A = 3779.0; coefficients B1 = -90.504, B2 = 0.85293, and B3 = -4.0600 × 10⁻⁶. -3 B4 = 1.0403 × 10 -5 B5 = -1.3707 × 10 -8 B6 = 7.2913 × 10 -12 The functional relationship between the B value of lignite and temperature is:

[0113] Where y is the B value, which is dimensionless; x is the temperature of lignite, in °C.

[0114] Based on the above exemplary explanation of the second fitted curve, we can conclude that: Regarding the change in R value, during the process of lignite from oxidation and heat storage to combustion criticality, the temperature first increases slightly, and the R value rises sharply with the temperature, approaching the maximum value of 255. Its change characteristics conform to a certain linear law. Then, the lignite temperature rises sharply, and during this process, the R value remains close to the maximum value and essentially stops changing. Regarding the change in G value, as the lignite temperature increases, the G value rises from 173.43 to 194.51, reaching the first peak; secondly, the G value decreases from 194.51 to 93.59, reaching the first trough; thirdly, the G value rises from 93.59 to 212.45, reaching the second peak; fourthly, the G value rapidly decreases from 212.45 to 64.42, reaching the second trough, at which point the coal temperature approaches the ignition point temperature of 276℃ for this type of lignite; finally, the G value slowly rises from 64.42 to 96.59. Regarding the change in the B value, within the temperature range of 31.2℃ to 55.3℃, the B value exhibits an approximately parabolic relationship with temperature; within the temperature range of 55.3℃ to 90.8℃, it remains relatively stable with a small range of change, but it is at the highest point of the B value; within the temperature range of 90.8℃ to 474.2℃, the B value has an approximately polynomial relationship with temperature, with the B value first decreasing to near 0 and then increasing again as the temperature rises.

[0115] As can be seen from the above, the R, G, and B values ​​of the experimental lignite coal type show certain regularity, which can provide data for mine monitoring and provide a basis for subsequent coal type classification and coal spontaneous combustion early warning.

[0116] In one embodiment of this application, the first curve includes: the curve of R value versus combustion time versus coal temperature, the curve of G value versus combustion time versus coal temperature, the curve of B value versus combustion time versus coal temperature, and the curve of RGB value versus combustion time versus coal temperature. The second curve includes: the curves of R value versus coal temperature versus combustion time, the curves of G value versus coal temperature versus combustion time, the curves of B value versus coal temperature versus combustion time, and the curves of RGB value versus coal temperature versus combustion time.

[0117] In this embodiment, the first curve includes: Figure 5 Curves showing the changes in lignite heating time and R-value as a function of coal sample temperature. Figure 11 Curves showing the relationship between lignite heating time and G-value as a function of coal sample temperature. Figure 18 Curves showing the relationship between lignite heating time and B-value as a function of coal sample temperature. Figure 24 Curves showing the relationship between lignite heating time and RGB values ​​as a function of coal sample temperature; the second curve includes: Figure 6 Curves showing the changes in temperature and R-value of lignite over heating time. Figure 12 The curves showing the changes in temperature and G value of lignite with the heating time of the coal sample are shown. Figure 19 Curves showing the changes in temperature and B-value of lignite over heating time. Figure 25 Curves showing the changes in lignite temperature and RGB values ​​over time. Based on the obtained first and second curves, the corresponding first and second functions can be determined.

[0118] In this embodiment, from Figure 5 and Figure 6 It can be seen that the R-value of lignite fluctuates during the spontaneous combustion process and exhibits a clear regularity. To facilitate piecewise curve fitting, the Lignite R-value variation curve with temperature is divided into three stages: Stage 1: 31.2℃~55.3℃ (5min~42min), Stage 2: 55.3℃~90.8℃ (42min~81min), and Stage 3: 90.8℃~474.2℃ (81min~105min). Figure 11 and Figure 12 It can be seen that the G value fluctuates during the heating process of the lignite sample, exhibiting a clear regularity. To facilitate piecewise curve fitting, the curve of the lignite G value versus temperature is divided into two stages: Stage 1: 30℃~249.2℃ (5min~101min) and Stage 2: 249.2℃~474.2℃; from Figure 18 and Figure 19 It can be seen that the B value of lignite fluctuates during the coal oxidation and spontaneous combustion process and shows obvious regularity. In order to facilitate the segmented fitting of the curve, the curve of the change of lignite B value with temperature is divided into three stages: stage 1: 31.2℃~55.3℃ (5min~42min), stage 2: 55.3℃~90.8℃ (42min~81min), and stage 3: 90.8℃~474.2℃ (81min~105min).

[0119] In this embodiment, from Figure 24 and Figure 25 It can be seen that the RGB values ​​of lignite fluctuate during the unoxidized natural process and exhibit certain regularities. First, within the temperature range of 30℃ to 121℃ or the time range of 0 to 92 min, the RGB values ​​of lignite fluctuate only slightly. Second, within the temperature range of 121℃ to 249.2℃ or the time range of 92 min to 101 min, the RGB values ​​of lignite show a parabolic relationship with the coal sample temperature or heating time. That is, as the coal sample temperature rises sharply, the RGB values ​​of lignite increase slightly from 112.87 to 149.44, corresponding to a temperature of 149℃, and then decrease slightly from 149.44 to 126.47, corresponding to a temperature of 249.2℃. Finally, within the temperature range of 249.2℃ to 474.2℃ or the time range of 101 min to 105 min, the temperature of lignite rises sharply, and the RGB values ​​increase slowly with temperature, with a relatively small increase. Therefore, the RGB value of lignite only shows a slight change of first rising and then falling within the middle temperature range of 121℃ to 249.2℃; it remains basically stable within the two extreme temperature ranges without significant changes.

[0120] The above analysis of the first and second curves reveals that the changes in R, G, and B values ​​during the spontaneous combustion of coal with temperature and time exhibit certain regularities. These curves, along with the color characteristics (RGB values), temperature, and time during coal combustion, provide a clear and intuitive reflection of the changing combustion states at different stages, offering a quantitative basis for accurately judging the combustion process and providing early warning of anomalies.

[0121] In one embodiment of this application, after determining the combustion state of the target coal type based on the first function and the second function, the method further includes: Early warning of combustion of target coal types is provided based on combustion status.

[0122] In this embodiment, the first and second functions of the target coal type can be analyzed, with temperature or time as the independent variable, to determine the functional relationship of the function expressions in each interval, thereby determining the type of the target coal type and its spontaneous combustion characteristics, and providing combustion warnings for the detected coal type based on temperature division.

[0123] For example, combustion data is acquired for a target coal type to be monitored, and then a first function and a second function are obtained. The functional relationship expression of the first function and the second function in each interval is analyzed. For example, with time as the independent variable, the trend of the R value of the target coal type to be monitored is as follows: first, it shows an approximately parabolic relationship, then it decreases and remains stable close to 0, and finally it shows an approximately parabolic relationship, with the R value rising sharply and approaching the maximum R value of 255. Then the target coal type conforms to the trend of the R value of lignite. If the G value, B value and RGB value all conform to the trend of the multiple color value sets of lignite, then the target coal type is judged to be lignite.

[0124] In this embodiment, in subsequent mine applications, the corresponding temperature and combustion stage can be directly analyzed by analyzing the captured infrared thermal images, thus completing a quantitative analysis of the mine's internal temperature.

[0125] For example, by monitoring the trend and pattern of changes in the RGB values ​​of coal types, if the analysis shows that the target coal type is slowly entering the accelerated oxidation stage, a level one warning can be set; if the target coal type is approaching its auto-ignition point under conditions such as severe oxidation and significant exothermic reaction, an emergency warning needs to be triggered.

[0126] As can be seen from the above, this application can directly determine the combustion stage of coal at the corresponding temperature by analyzing the changing trends of RGB values ​​of coal through function analysis. Combined with the division of oxidation stages, it can realize graded early warning, which can specifically monitor the spontaneous combustion state of coal, improve the targeting and reliability of monitoring, effectively prevent and control the risk of spontaneous combustion in coal mines, and ensure mining safety.

[0127] In one embodiment of this disclosure, such as Figure 2 As shown, the specific process of the online infrared thermographic characterization system and method for the spontaneous combustion characteristics and material properties of coal is as follows: In this embodiment, firstly, a target coal type is collected, and a coal sample is obtained by programmed heating of the target coal type. An infrared thermal imager is used to capture an infrared thermal image of the target coal sample to obtain the R value, G value, B value, and RGB value. Secondly, the change curves of the R value, G value, B value, and RGB value during the oxidation process of the target coal sample are analyzed to obtain the regularity of the R value, G value, B value, and RGB value at different stages. Thirdly, this embodiment obtains a fitting curve by fitting the change curves of the R value, G value, B value, and RGB value, and at the same time obtains the corresponding functional relationship.

[0128] Corresponding to the online infrared thermographic characterization method for coal spontaneous combustion characteristics and material properties in the above embodiments, Figure 26 This is a structural block diagram of an online infrared thermographic characterization system for the spontaneous combustion characteristics and material properties of coal, provided as an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 26The infrared thermographic characterization system 20 for the spontaneous combustion characteristics and material properties of coal includes: a data acquisition module 21, a function determination module 22, and a combustion state determination module 23.

[0129] Among them, the data acquisition module 21 is used to acquire the combustion data of the target coal type. The combustion data includes multiple color value sets, combustion temperature data and combustion time data of the target coal type. The function determination module 22 is used to determine a first function and a second function based on combustion data. The first function is a function of the first data changing with the combustion temperature data, and the second function is a function of the second data changing with the combustion time data. The first data includes multiple color data values ​​and combustion time data, and the second data includes multiple color value sets and combustion temperature data. Combustion state determination module 23 is used to determine the combustion state of the target coal type based on the first function and the second function.

[0130] In one embodiment of this application, the multiple color value sets include: R value value set, G value value set, B value value set and RGB value value set; the combustion temperature data includes: coal type temperature and programmed temperature; the combustion time data includes: coal type heating time.

[0131] In one embodiment of this application, the function determination module 22 is specifically used for: A first curve is determined based on the first data and the coal type temperature, and a first function is determined based on the first curve. The second curve is determined based on the second data and the coal type's heating time, and the second function is determined based on the second curve.

[0132] In one embodiment of this application, the function determination module 22 is further configured to: A first fitting curve is determined based on the first curve, and a first function is determined based on the first fitting curve. The first fitting curve is a fitting curve of multiple color value sets as the program temperature changes.

[0133] In one embodiment of this application, the function determination module 22 is further configured to: The second fitting curve is determined based on the second curve, and the second function is determined based on the second fitting curve. The second fitting curve is a fitting curve of multiple color value sets changing with the heating time of coal type.

[0134] In one embodiment of this application, the first curve includes: the curves of R value and combustion time as a function of coal temperature, G value and combustion time as a function of coal temperature, B value and combustion time as a function of coal temperature, and RGB value and combustion time as a function of coal temperature; the second curve includes: the curves of R value and combustion time as a function of coal temperature, G value and combustion time, B value and combustion time as a function of coal temperature, and RGB value and combustion time as a function of coal temperature.

[0135] In one embodiment of this application, the combustion state determination module 23 is specifically used for: Early warning of combustion of target coal types is provided based on combustion status.

[0136] See Figure 27 , Figure 27 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 27 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of the modules in the aforementioned device embodiments, for example... Figure 26 The functions of the data acquisition module 21, function determination module 22, and combustion state determination module 23 are shown.

[0137] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0138] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0139] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory.

[0140] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation methods described in the online infrared thermal imaging characterization method for coal spontaneous combustion characteristics and material properties provided in the embodiments of this application, or they can execute the implementation methods of the electronic devices described in the embodiments of this application, which will not be elaborated here.

[0141] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0142] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., provided on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0143] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0144] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0145] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules, or it may be an electrical, mechanical, or other form of connection.

[0146] The modules described as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0147] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal, characterized in that, include: Obtain combustion data for the target coal type, wherein the combustion data includes multiple color value sets, combustion temperature data, and combustion time data for the target coal type; Based on the combustion data, a first function and a second function are determined. The first function is a function of the first data changing with the combustion temperature data, and the second function is a function of the second data changing with the combustion time data. The first data includes the plurality of color data values ​​and the combustion time data, and the second data includes the plurality of color value sets and the combustion temperature data. The combustion state of the target coal is determined based on the first function and the second function.

2. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 1, characterized in that, The multiple color value sets include: R value set, G value set, B value set, and RGB value set; the combustion temperature data includes: coal type temperature and programmed temperature; the combustion time data includes: coal type heating time.

3. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 2, characterized in that, The determination of the first function and the second function based on the combustion data includes: A first curve is determined based on the first data and the coal type temperature, and a first function is determined based on the first curve. The second curve is determined based on the second data and the coal type's heating time, and the second function is determined based on the second curve.

4. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 3, characterized in that, The step of determining the first function based on the first curve includes: A first fitting curve is determined based on the first curve, and a first function is determined based on the first fitting curve. The first fitting curve is a fitting curve of multiple color value sets as the program temperature changes.

5. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 4, characterized in that, The step of determining the second function based on the second curve includes: A second fitting curve is determined based on the second curve, and a second function is determined based on the second fitting curve. The second fitting curve is a fitting curve of multiple color value sets changing with the heating time of coal type.

6. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 2, characterized in that, The first curve includes: the curve of R value versus combustion time as a function of coal type and temperature, the curve of G value versus combustion time as a function of coal type and temperature, the curve of B value versus combustion time as a function of coal type and temperature, and the curve of RGB value versus combustion time as a function of coal type and temperature. The second curve includes: the curves of R value versus coal temperature versus combustion time, the curves of G value versus coal temperature versus combustion time, the curves of B value versus coal temperature versus combustion time, and the curves of RGB value versus coal temperature versus combustion time.

7. The online infrared thermographic characterization method for the spontaneous combustion characteristics and material properties of coal as described in claim 1, characterized in that, After determining the combustion state of the target coal type based on the first function and the second function, the method further includes: A combustion warning is issued for the target coal type based on the combustion status.

8. An online infrared thermographic characterization system for the spontaneous combustion characteristics and material properties of coal, characterized in that, include: The data acquisition module is used to acquire combustion data of the target coal type, wherein the combustion data includes multiple color value sets, combustion temperature data and combustion time data of the target coal type; The function determination module is used to determine a first function and a second function based on the combustion data. The first function is a function that changes the first data with the combustion temperature data, and the second function is a function that changes the second data with the combustion time data. The first data includes the plurality of color data values ​​and the combustion time data, and the second data includes the plurality of color value sets and the combustion temperature data. The combustion state determination module is used to determine the combustion state of the target coal type based on the first function and the second function.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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