Coal spontaneous combustion tendency monitoring method and system based on RGB curve roughness

Abstract

The invention provides a coal spontaneous combustion tendency monitoring method and system based on RGB curve roughness, and belongs to the field of coal spontaneous combustion fire prevention, and the method comprises the steps: obtaining a combustion image of a target coal type, and processing the combustion image to obtain a plurality of color value sets; determining a temperature change curve corresponding to each color value set; and calculating the curve roughness of each temperature change curve, and determining the coal spontaneous combustion tendency of the target coal type according to the curve roughness of all the temperature change curves. According to the coal spontaneous combustion tendency monitoring method and system based on the RGB curve roughness, large-range and high-precision coal spontaneous combustion early warning can be achieved.

Description

Technical Field

[0001] This application belongs to the field of coal spontaneous combustion fire prevention technology, and more specifically, it relates to a coal spontaneous combustion tendency monitoring method and system based on RGB curve roughness. Background Technology

[0002] As a crucial pillar of the global energy system, the safety of coal mining, storage, transportation, and utilization has always been a focus of industry attention. Spontaneous combustion of coal is a major safety hazard in coal mine production, storage yards, and the transportation chain. Essentially, it occurs when coal reacts with oxygen at room temperature, accumulating heat and ultimately leading to spontaneous combustion or even an explosion.

[0003] Traditional methods for testing the tendency of coal spontaneous combustion often suffer from problems such as long testing cycles and difficulty in adapting to complex field environments. Therefore, there is a need for a method that can achieve large-scale, high-precision early warning of coal spontaneous combustion. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for monitoring the tendency of coal spontaneous combustion based on RGB curve roughness, so as to achieve early warning of coal spontaneous combustion with a wide range and high precision.

[0005] A first aspect of this application provides a method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness, comprising: Obtain combustion images of the target coal type, process the combustion images, and obtain multiple color value sets; Determine the temperature change curve corresponding to each color value set; Calculate the roughness of each temperature change curve, and determine the spontaneous combustion tendency of the target coal type based on the roughness of all temperature change curves.

[0006] A second aspect of this application provides a coal spontaneous combustion tendency monitoring system based on RGB curve roughness, comprising: The first module is used to acquire combustion images of the target coal type, process the combustion images, and obtain multiple color value sets; The second module is used to determine the temperature change curve corresponding to each color value set; The third module is used to calculate the curve roughness of each temperature change curve and determine the spontaneous combustion tendency of the target coal type based on the curve roughness of all temperature change curves.

[0007] 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, wherein the processor executes the computer program to implement the steps of the above-described method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness.

[0008] 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 method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness.

[0009] The beneficial effects of the coal spontaneous combustion tendency monitoring method and system based on RGB curve roughness provided in this application are as follows: This application uses infrared thermal imaging technology to obtain a multi-color numerical set of coal types and calculates the curve roughness of each temperature change curve. The curve roughness is then compared within a specific range to determine the spontaneous combustion tendency of the target coal type. This application uses infrared thermal imaging technology to obtain a multi-color numerical set of the target coal type, enabling large-scale monitoring. Since the calculated curve roughness for different coal types will exhibit certain regularities, this application has designed its own curve roughness calculation formula. This formula characterizes the curve fluctuation by calculating the number of peaks and valleys in the temperature change curve of the target coal type, thereby determining the spontaneous combustion tendency of the target coal type. Attached Figure Description

[0010] 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.

[0011] Figure 1 A flowchart illustrating a method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness, provided in an embodiment of this application. Figure 2 A schematic diagram illustrating the specific process of a coal spontaneous combustion tendency monitoring method based on RGB curve roughness provided in an embodiment of this application; Figure 3 The variation of R-value with coal temperature for different coal types; Figure 4 The variation of G-value with coal temperature for different coal types; Figure 5 The variation of B value with coal temperature for different coal types; Figure 6 The variation of RGB values ​​of different coal types with coal temperature; Figure 7 A structural block diagram of a coal spontaneous combustion tendency monitoring system based on RGB curve roughness provided in an embodiment of this application; Figure 8 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0012] 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.

[0013] 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.

[0014] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness according to an embodiment of this application. The method may include: S101: Obtain the combustion image of the target coal type, process the combustion image, and obtain multiple color value sets.

[0015] In this embodiment, before acquiring the combustion image of the target coal, the method further includes: sealing and storing the acquired target coal, and promptly sending it to the laboratory to pulverize the target coal; the pulverized target coal sample needs to be vacuum-sealed and stored; and processing the pulverized target coal sample to obtain multiple color value sets.

[0016] If coal is not sealed and stored properly during transportation, its physicochemical properties will change, leading to data distortion. Timely testing is necessary to complete the testing before the coal properties change significantly, ensuring the accuracy and predictability of the data.

[0017] For example, for large pieces of fresh coal samples, they can be sealed with plastic wrap, placed in a sampling bucket, and sent to the laboratory within 24 hours. The coal samples are then crushed using a compression crushing method, placed in a sample sealing bag, and vacuum-sealed for later use.

[0018] In this embodiment, the pulverized target coal sample is subjected to combustion treatment. An infrared thermal imager lens can be used to capture the surface of the target coal sample, and software can be linked to collect online infrared thermal video of the target coal sample to obtain multiple color value sets.

[0019] S102: Determine the temperature change curve corresponding to each color value set.

[0020] In this embodiment, the multiple color value sets include R value set, G value set, B value set and RGB value set, and the temperature change curves include the R value change curve of the target coal type with coal temperature, the G value change curve with coal temperature, the B value change curve with coal temperature and the RGB value change curve with coal temperature.

[0021] Exemplarily, multiple sets of color value data are input into the curve generation software to obtain the temperature change curve corresponding to each set of color values.

[0022] Specifically, software such as Tableau software, MATLAB software or Space Curve Explorer software can be used to generate the temperature change curve corresponding to each set of color values.

[0023] S103: Calculate the curve roughness of each temperature change curve, and determine the spontaneous combustion tendency of the target coal type according to the curve roughness of all temperature change curves.

[0024] In this embodiment, the formula for calculating the curve roughness characterizes the fluctuation of the curve by calculating the number of peaks and valleys of each curve. The numerator part of the formula is the total number of curve peaks and valleys, and a more general formula characterization method is obtained by associating with the temperature difference.

[0025] Exemplarily, the classification grades of the spontaneous combustion tendency of Chinese coal are divided into Class I prone to spontaneous combustion, Class II spontaneous combustion and Class III not prone to spontaneous combustion. After analyzing and summarizing the roughness of different coal types obtained by calculation and conducting multiple experiments, it can be concluded that as shown in the roughness division intervals corresponding to the spontaneous combustion tendency of different coal types in Table 1, for the roughness < a, it is divided into Class I prone to spontaneous combustion, and the corresponding coal type is lignite. For the roughness between a and b, it is divided into Class II spontaneous combustion, and the corresponding coal type is bituminous coal. For the roughness > b, it is divided into Class III not prone to spontaneous combustion, and the corresponding coal type is anthracite.

[0026]

[0027] Highly spontaneous combustion prone coal seams are prone to spontaneous combustion due to oxidation heat release during mining, leading to mine fires and even gas explosions. In this embodiment, by determining the spontaneous combustion tendency of coal, the ventilation system and mining process can be designed specifically, and the spontaneous combustion period can be determined to formulate the monitoring frequency. Therefore, it is very important to judge the spontaneous combustion tendency of coal samples during mine mining. In subsequent experiments, a large number of lignite, bituminous coal and anthracite classified according to the existing technology will be measured by this method, and the roughness calculated for different coal types will show certain regularity, so as to determine the division intervals of the spontaneous combustion tendency of coal under this method, that is, the specific values of a, b, and c.

[0028] When obtaining a coal sample whose spontaneous combustion tendency has not been determined, according to the monitoring method and system for the spontaneous combustion tendency of coal based on the RGB curve roughness, an online infrared thermal image video of the coal sample is collected to obtain the R value, G value, B value and RGB value corresponding to the temperature, and the curve roughness of each is calculated respectively. The calculated curve roughness of the coal sample is corresponded to the determination interval of the spontaneous combustion tendency of coal, so as to determine the spontaneous combustion tendency of the coal type.

[0029] Specifically, Figure 2 This is a schematic flowchart illustrating a method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness according to an embodiment of this application. The steps of this embodiment are as follows: First, coal samples are collected from the coal mine and prepared. Then, the coal samples are heated to a programmed temperature and infrared thermographic images are taken. Subsequently, the changes of R, G, B, and RGB values ​​with coal temperature are analyzed based on the infrared thermographic images. The curve roughness of R, G, B, and RGB values ​​is calculated for each value. Then, the curve roughness of all coal types is summarized and analyzed. Finally, the curve roughness intervals of different coal types are divided to obtain a coal spontaneous combustion tendency monitoring method based on RGB curve roughness.

[0030] As can be seen from the above, this application uses infrared thermal imaging technology to obtain multiple color value sets of the target coal type, calculates the curve roughness of each temperature change curve, and compares the curve roughness judgment interval to determine the spontaneous combustion tendency of the target coal type. This disclosure uses infrared thermal imaging technology to obtain multiple color value sets of the target coal type, enabling large-scale monitoring. Since the curve roughness calculated for different coal types will exhibit certain regularities, this disclosure has designed its own curve roughness calculation formula. This formula characterizes the curve fluctuation by calculating the number of peaks and valleys of the temperature change curve of the target coal type, thereby determining the spontaneous combustion tendency of the target coal type.

[0031] In one embodiment of this application, the multiple color value sets include an R value value set, a G value value set, a B value value set, and an RGB value value set.

[0032] 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.

[0033] For example, lignite, bituminous coal, and anthracite are processed separately to obtain their respective sets of R-values, G-values, B-values, and RGB-values.

[0034] As can be seen from the above, using four infrared thermographic values—R, G, B, and RGB—to characterize the temperature-dependent properties of different coal types transforms "invisible temperature information" into "visible color images." This enhances the visualization of temperature differences through color contrast and provides data support for subsequent curve roughness calculations.

[0035] In one embodiment of this application, calculating the roughness of each temperature change curve includes: Calculate the roughness of the temperature change curve corresponding to the set of R-values; Calculate the roughness of the temperature change curve corresponding to the set of G values; Calculate the roughness of the temperature change curve corresponding to the set of B values; Calculate the roughness of the temperature change curve corresponding to the RGB value set.

[0036] In this embodiment, the formula for calculating curve roughness is self-designed, and the formula for calculating curve roughness is:

[0037] Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; A i This indicates the R, G, B, or RGB value corresponding to the temperature. This indicates the temperature difference during the experiment.

[0038] In this embodiment, the numerator of the formula is the total number of peaks and troughs of the calculated curve, and the denominator is the temperature difference during the experiment. For example, in this experiment... =500.

[0039] As can be seen from the above, this formula characterizes the fluctuation of the target coal type's temperature change curve by calculating the number of peaks and valleys, providing a formulaic basis for subsequently classifying the spontaneous combustion tendency of the target coal type.

[0040] In one embodiment of this application, calculating the roughness of the temperature change curve corresponding to the set of R-values ​​includes: The roughness of the curve is calculated using the first formula for the R value:

[0041] Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; R i This represents the R value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The sign (+1, -1, or 0), that is, if The symbol is not equal to If the symbol is '[', then record a number;') This indicates the temperature difference during the experiment.

[0042] In this embodiment, the numerator of the formula is the total number of peaks and troughs in the curve of R-value changing with temperature, and the denominator is the temperature difference during the experiment. For example, in this experiment... =500.

[0043] Figure 3 The variation of R-value with coal temperature for different coal types, such as Figure 3 As shown, lignite exhibits less fluctuation, while anthracite shows a significant increase in fluctuation. Table 2 is obtained by calculating the R-value curves of different coal types using the first formula based on the measured data.

[0044]

[0045] As can be seen from the above, the first formula characterizes the fluctuation of the curve by calculating the number of peaks and valleys of the target coal type's R value as a function of temperature. The roughness of lignite is 2.25%, that of bituminous coal is 6.91%, and that of anthracite is 12.54%.

[0046] In one embodiment of this application, calculating the roughness of the temperature change curve corresponding to the set of G-values ​​includes: The curve roughness of the G value is calculated using the second formula:

[0047] Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; G i This represents the G value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The sign (+1, -1, or 0), that is, if The symbol is not equal to If the symbol is '[', then record a number;') This indicates the temperature difference during the experiment.

[0048] In this embodiment, the numerator of the formula is the total number of peaks and troughs in the curve of G value changing with temperature, and the denominator is the temperature difference during the experiment. For example, in this experiment... =500.

[0049] Figure 4 The variation of G-value with coal temperature for different coal types, such as Figure 4 As shown, lignite exhibits less fluctuation, while anthracite shows a significant increase in fluctuation. The measured data were calculated using the second formula, resulting in Table 3, which shows the roughness of the G-value curves for different coal types.

[0050]

[0051] As can be seen from the above, the second formula characterizes the fluctuation of the curve by calculating the number of peaks and valleys of the curve of the target coal type's G value changing with temperature. The roughness of lignite is 2.64%, the roughness of bituminous coal is 6.91%, and the roughness of anthracite is 12.54%.

[0052] In one embodiment of this application, calculating the roughness of the temperature change curve corresponding to the set of B values ​​includes: The curve roughness of the B value is calculated using the third formula:

[0053] Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; B i This represents the B value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The sign (+1, -1, or 0), that is, if The symbol is not equal to If the symbol is '[', then record a number;') This indicates the temperature difference during the experiment.

[0054] In this embodiment, the numerator of the formula is the total number of peaks and troughs in the curve of B value changing with temperature, and the denominator is the temperature difference during the experiment. For example, in this experiment... =500.

[0055] Figure 5 The variation of B value with coal temperature for different coal types, such as Figure 5 As shown, lignite has less fluctuation, bituminous coal has more fluctuation, and anthracite has a significantly increased number of fluctuations. The measured data were calculated using the third formula, resulting in Table 4, which shows the roughness of the B-value curves for different coal types.

[0056]

[0057] As can be seen from the above, the third formula characterizes the fluctuation of the curve by calculating the number of peaks and valleys of the target coal type B value as a function of temperature. The roughness of lignite is 3.15%, the roughness of bituminous coal is 6.64%, and the roughness of anthracite is 13.02%.

[0058] In one embodiment of this application, calculating the roughness of the temperature change curve corresponding to the RGB value set includes: Calculate the curve roughness using the fourth formula:

[0059] Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; RGB i This represents the RGB value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The sign (+1, -1, or 0), that is, if The symbol is not equal to If the symbol is '[', then record a number;') This indicates the temperature difference during the experiment.

[0060] In this embodiment, the numerator of the formula is the total number of peaks and troughs in the RGB value versus temperature curve, and the denominator is the temperature difference during the experiment. For example, in this experiment... =500.

[0061] Figure 6 The variation of RGB values ​​of different coal types with coal temperature, such as Figure 6 As shown, lignite exhibits less fluctuation, while anthracite shows a significant increase in fluctuation. The measured data were calculated using the fourth formula, resulting in Table 5, which shows the roughness of the RGB value curves for different coal types.

[0062]

[0063] As can be seen from the above, the fourth formula characterizes the fluctuation of the curve by calculating the number of peaks and valleys of the RGB value of the target coal as a function of temperature. The roughness of lignite is 3.60%, that of bituminous coal is 7.44%, and that of anthracite is 12.07%.

[0064] From the above, it can be concluded that the roughness calculation formula for this curve is obtained based on the relationship between the R value, G value, B value, RGB value, and heating temperature. Figures 3-6 It can be seen that the fluctuations of different coal types during the heating process are significantly different, and the curve roughness obtained from the curve roughness calculation formula provides data support for subsequent analysis and division of judgment intervals.

[0065] Corresponding to the coal spontaneous combustion tendency monitoring method based on RGB curve roughness in the above embodiment, Figure 7 This is a structural block diagram of a coal spontaneous combustion tendency monitoring system based on RGB curve roughness, 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 7 The coal spontaneous combustion tendency monitoring system 20 based on RGB curve roughness includes: a first module 21, a second module 22 and a third module 23.

[0066] The first module 21 is used to acquire a combustion image of the target coal type, process the combustion image, and obtain multiple color value sets. The second module 22 is used to determine the temperature change curve corresponding to each color value set; The third module 23 is used to calculate the curve roughness of each temperature change curve and determine the spontaneous combustion tendency of the target coal type based on the curve roughness of all temperature change curves.

[0067] In one embodiment of this application, the multiple color value sets include an R value value set, a G value value set, a B value value set, and an RGB value value set.

[0068] In one embodiment of this application, the third module 23 is specifically used for: Calculate the roughness of the temperature change curve corresponding to the set of R-values; Calculate the roughness of the temperature change curve corresponding to the set of G values; Calculate the roughness of the temperature change curve corresponding to the set of B values; Calculate the roughness of the temperature change curve corresponding to the RGB value set.

[0069] In one embodiment of this application, the third module 23 is further configured to: The roughness of the curve is calculated using the first formula for the R value:

[0070] Where y represents the curve roughness; ∑ is the accumulation symbol, indicating a summation operation; i=2 represents the initial accumulation value, meaning variable i starts taking values ​​from 2; n-1 represents the final accumulation value, meaning variable i ends taking values ​​from n-1; R i This represents the R value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

[0071] In one embodiment of this application, the third module 23 is further configured to: The curve roughness of the G value is calculated using the second formula:

[0072] Where y represents the curve roughness; ∑ is the accumulation symbol, indicating a summation operation; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; G i This represents the G value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

[0073] In one embodiment of this application, the third module 23 is further configured to: The curve roughness of the B value is calculated using the third formula:

[0074] Where y represents the curve roughness; ∑ is the accumulation symbol, indicating a summation operation; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; B i This represents the B value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

[0075] In one embodiment of this application, the third module 23 is further configured to: Calculate the curve roughness using the fourth formula:

[0076] Where y represents the curve roughness; ∑ is the accumulation symbol, indicating a summation operation; i=2 represents the starting value for accumulation, meaning variable i starts taking values ​​from 2; n-1 represents the ending value for accumulation, meaning variable i ends taking values ​​from n-1; RGB i This represents the RGB value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

[0077] See Figure 8 , Figure 8 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 8The 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 system embodiments, for example... Figure 7 The functions of the first module 21, the second module 22, and the third module 23 are shown.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation method described in the coal spontaneous combustion tendency monitoring method based on RGB curve roughness provided in the embodiments of this application, or they can execute the implementation method of the electronic device described in the embodiments of this application, which will not be repeated here.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0089] 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. A method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness, characterized in that, include: Obtain a combustion image of the target coal type, process the combustion image to obtain multiple color value sets; Determine the temperature change curve corresponding to each color value set; Calculate the roughness of each temperature change curve, and determine the spontaneous combustion tendency of the target coal type based on the roughness of all temperature change curves.

2. The method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness as described in claim 1, characterized in that, The multiple color value sets include the R value set, the G value set, the B value set, and the RGB value set.

3. The method for monitoring coal spontaneous combustion tendency based on RGB curve roughness as described in claim 2, characterized in that, The calculation of the curve roughness of each temperature change curve includes: Calculate the roughness of the temperature change curve corresponding to the set of R-values; Calculate the roughness of the temperature change curve corresponding to the set of G values; Calculate the roughness of the temperature change curve corresponding to the set of B values; Calculate the roughness of the temperature change curve corresponding to the RGB value set.

4. The method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness as described in claim 3, characterized in that, The roughness of the temperature change curve corresponding to the set of calculated R-values ​​includes: The roughness of the curve is calculated using the first formula for the R value: Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; R i This represents the R value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

5. The method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness as described in claim 3, characterized in that, The roughness of the temperature change curve corresponding to the calculated G-value set includes: The curve roughness of the G value is calculated using the second formula: Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; G i This represents the G value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

6. The method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness as described in claim 3, characterized in that, The roughness of the temperature change curve corresponding to the set of calculated B values ​​includes: The curve roughness of the B value is calculated using the third formula: Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; B i This represents the B value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

7. The method for monitoring the spontaneous combustion tendency of coal based on RGB curve roughness as described in claim 3, characterized in that, The roughness of the temperature change curve corresponding to the RGB value set is calculated, including: Calculate the curve roughness using the fourth formula: Where y represents the curve roughness; i=2 represents the initial accumulation value, that is, variable i starts taking values ​​from 2; n-1 represents the final accumulation value, that is, variable i ends taking values ​​at n-1; RGB i This represents the RGB value corresponding to the i-th temperature. express The symbol (+1, -1 or 0). express The symbol (+1, -1 or 0); This indicates the temperature difference during the experiment.

8. A coal spontaneous combustion tendency monitoring system based on RGB curve roughness, characterized in that, include: The first module is used to acquire a combustion image of the target coal type, process the combustion image, and obtain multiple color value sets. The second module is used to determine the temperature change curve corresponding to each color value set; The third module is used to calculate the curve roughness of each temperature change curve and determine the spontaneous combustion tendency of the target coal type based on the curve roughness of all temperature change curves.

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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