Intelligent identification and identification method and system for coal-series graphite

Abstract

The invention provides an intelligent coal-series graphite identification method and system, and the method comprises the steps: obtaining a coal-series sample, and collecting the volatile components and reflectivity of the coal-series sample; the volatile components and the reflectivity are compared with set threshold values respectively, and a preliminary identification result is generated; based on the preliminary identification result, performing intelligent spectrum analysis through a preset X-ray polycrystal diffractometer to obtain interplanar spacing; performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; and generating a final identification result based on the interplanar spacing and the interval of the Raman parameter, and classifying the coal-based graphite according to the final identification result. The method solves the problems of low identification efficiency and poor accuracy of existing coal-series graphite identification.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine identification, and in particular to a method and system for intelligently identifying and identifying coal-based graphite. Background Art

[0002] Coal-bearing graphite is a strategic mineral resource and has unique advantages in nuclear graphite, military aircraft tires, etc. The identification and appraisal of coal-bearing graphite is crucial to its exploration, development and reserve guarantee.

[0003] Since coal-bearing graphite is the product of coal and coal-bearing organic matter entering the graphitization stage after undergoing magmatic thermal metamorphism and tectonic stress, it is mainly cryptocrystalline or microcrystalline structure, and is composed of a mixture of new components with different degrees of graphitization and residual coal rock components. It has a continuous transitional nature with high-metamorphic coal, and its identification and appraisal are somewhat difficult, and a single indicator cannot be simply used.

[0004] Therefore, it is urgent to develop an intelligent equipment for identifying and identifying coal-based graphite, so as to quickly and accurately identify coal-based graphite mineral resources in batches and enhance the strategic support capability of coal-based graphite. Summary of the invention

[0005] The present invention provides a method and system for intelligently identifying and identifying coal-based graphite, which are used to solve the problems of low efficiency and poor accuracy in existing identification and identification of coal-based graphite.

[0006] The present invention provides a method for intelligent identification and appraisal of coal-based graphite, comprising: Obtain coal-measure samples, and collect the volatile matter and reflectivity of the coal-measure samples; Comparing the volatile matter and reflectance with set thresholds respectively to generate a preliminary identification result; Based on the preliminary identification results, a preset X-ray multi-crystal diffractometer is used to perform a spectrum intelligent analysis to obtain the interplanar spacing; Performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; A final identification result is generated based on the interval of the interplanar spacing and the Raman parameter, and the coal-based graphite is classified according to the final identification result.

[0007] According to a method for intelligent identification and appraisal of coal-based graphite provided by the present invention, the step of obtaining a coal-based sample and collecting volatile components of the coal-based sample specifically includes: Obtain coal series samples, make samples of specific specifications and weigh the initial weight; heating the sample and weighing the heated sample; The volatile matter is calculated based on the weight of the heated sample and the initial weight.

[0008] According to a method for intelligent identification and appraisal of coal-based graphite provided by the present invention, the step of obtaining a coal-based sample and collecting the reflectivity of the coal-based sample specifically includes: Obtain coal series samples and prepare test specimens, and collect microscopic images of the samples and preset standard materials in sequence through a microscope camera and an automatic stage under set conditions; Grayscale measurement is performed on all measuring points of the microscopic images of the sample and the preset standard material, a grayscale-random reflectivity relationship model is established through the standard material, and random reflectivity values ​​of all measuring points in the microscopic image of the sample are obtained according to the grayscale-random reflectivity relationship model; Based on the random reflectance value, the vitrinite effective measuring points are automatically identified through a preset vitrinite recognition model, and the random reflectance values ​​of each vitrinite effective measuring point are statistically analyzed to obtain the average and standard deviation of the vitrinite random reflectance of the sample.

[0009] According to a method for intelligent identification and appraisal of coal-based graphite provided by the present invention, the method of performing intelligent analysis of the graph based on the preliminary identification result by a preset X-ray polycrystal diffractometer to obtain the interplanar spacing specifically includes: Based on the preliminary identification results, a copper target is irradiated by a preset X-ray polycrystal diffractometer to obtain an X-ray diffraction pattern data set; Based on the X-ray diffraction spectrum data set, the obtained sample X-ray diffraction spectrum is base-subtracted and smoothed, and the crystal plane diffraction peaks are displayed within the set scanning range; The interplanar spacing is calculated based on the crystal plane diffraction peak using a preset Bragg equation.

[0010] According to a method for intelligent identification and appraisal of coal-based graphite provided by the present invention, the Raman spectrum analysis is performed based on the crystal plane spacing to obtain Raman parameters, which specifically includes: Scanning the sample by a preset Raman spectrometer based on the interplanar spacing to obtain a Raman spectrum data set; Based on the Raman spectrum data set, the Raman spectrum background noise is removed by a preset software, and the peak area data of the characteristic peaks of the Raman spectrum are obtained by performing peak fitting by a preset function; The Raman parameters are automatically calculated based on the peak area data of the characteristic peaks of the Raman spectrum through a set program.

[0011] According to a method for intelligent identification and appraisal of coal-based graphite provided by the present invention, the final identification result is generated based on the interval of the crystal plane spacing and the Raman parameter, and the coal-based graphite is classified according to the final identification result, specifically including: Based on the interval of the interplanar spacing and the Raman parameter, determine whether it is coal-based graphite, and generate a final identification result; Coal-bearing graphite is classified based on the interval range in the identification results.

[0012] The present invention also provides a coal-based graphite intelligent identification and appraisal system, the system comprising: The data acquisition module is used to obtain coal-measure samples and collect the volatile matter and reflectivity of the coal-measure samples; A preliminary identification module, used to compare the volatile matter and reflectivity with set thresholds respectively to generate a preliminary identification result; A diffraction analysis module, used to perform intelligent analysis of the spectrum based on the preliminary identification results through a preset X-ray polycrystal diffractometer to obtain the interplanar spacing; A Raman spectrum analysis module, used for performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; The result output module is used to generate a final identification result based on the interval of the crystal plane spacing and the Raman parameter, and classify the coal-based graphite according to the final identification result.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements any of the above-mentioned methods for intelligent identification and appraisal of coal-based graphite.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for intelligent identification and appraisal of coal-based graphite.

[0015] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for intelligent identification and appraisal of coal-based graphite.

[0016] The present invention provides a method and system for intelligently identifying and identifying coal-based graphite. The method obtains the volatile matter and reflectivity of the coal-based sample, performs batch parameter calculation on the sample spectrum, identifies whether it is within the coal-based graphite parameter interval, and determines it to be coal-based graphite if it meets the interval value. The method also intelligently classifies the coal-based graphite by performing spectrum intelligent analysis based on an X-ray polycrystal diffractometer and by performing intelligent analysis through Raman spectroscopy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the process of the intelligent identification and appraisal method of coal-based graphite provided by the present invention.

[0019] Figure 2 This is the architecture diagram of the coal-based graphite intelligent identification and appraisal system provided by the present invention.

[0020] Figure 3 It is a schematic diagram of module connection of the coal-based graphite intelligent identification and appraisal system provided by the present invention.

[0021] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention.

[0022] Figure numerals: 110: data acquisition module; 120: preliminary identification module; 130: diffraction analysis module; 140: Raman spectrum analysis module; 150: result output module; 410: processor; 420: communication interface; 430: memory; 440: communication bus. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Combine the following Figure 1 The invention describes a method for intelligently identifying and authenticating coal-based graphite, comprising: step 100, obtaining a coal-based sample, and collecting the volatile matter and reflectivity of the coal-based sample.

[0025] In the present invention, samples are made based on coal samples respectively, and then the volatile matter and reflectivity are collected; wherein, the volatile matter refers to the organic matter and a part of the minerals in the coal that will decompose into gas (such as carbon oxide, methane and other combustible gases) and liquid overflow when the coal is heated at 900+10 degrees Celsius for 7 minutes under air-tight conditions. The overflow minus the water content in the coal is the volatile matter. The volatile matter content of the coal used in the chain furnace is preferably above 20%.

[0026] The mass loss of coal after moisture correction under specified conditions and heating in an airtight state is called volatile matter. The residue after removing the volatile matter is called coke slag. Volatile matter is not the inherent volatile matter in coal, but the thermal decomposition product of coal when heated under strictly specified conditions. Therefore, the volatile matter in coal is also called volatile matter yield.

[0027] The volatile matter yield of coal is closely related to the coalification degree of coal. The lower the coalification degree, the higher the volatile matter yield. As the coalification degree deepens, the volatile matter yield gradually decreases. The volatile matter yield is an indicator for evaluating coal quality. Coal with high volatile matter yield is prone to produce unburned carbon particles when burning, called "black smoke", and has low thermal efficiency. If the volatile matter yield of coal is too low, the boiler will not be easy to ignite, and it will be easy to extinguish after ignition, making it difficult to ensure stable combustion of the boiler. The results of the determination of the volatile matter yield of coal vary with different test conditions. Therefore, it must be determined strictly according to the standardized experimental operating conditions.

[0028] When coal is heated in an airtight environment, the following general conditions occur: below 100°C, the gas adsorbed in the coal and part of the water escape; below 110°C, all the water escapes; at 200°C, combined water escapes; at 250°C, the first pyrolysis begins, with gas escaping; above 350°C, tar is produced; at 550-600°C, all the tar escapes; above 600°C, the second pyrolysis begins, with gas escaping again and condensing to obtain high-temperature coke; at 900-1000°C, the decomposition stops, and the residue is coke.

[0029] The volatile matter of coal is mainly composed of water, hydrocarbons and hydrocarbons (mainly CH4), but the physical adsorption of water (including external water and internal water) and carbon dioxide generated by minerals are not included in the volatile matter. The determination of volatile matter in coal is a highly standardized test, and its results depend entirely on the test conditions. Among them, the mass of the sample, heating temperature, heating time, heating speed, the material, shape and size of the crucible, the model of the test equipment, and the size and material of the crucible stand can affect the determination results of the volatile matter to a certain extent.

[0030] In the present invention, a coal-measure sample is obtained and the volatile matter of the coal-measure sample is collected, which specifically includes: Obtain coal series samples, make samples of specific specifications and weigh the initial weight; heating the sample and weighing the heated sample; The volatile matter is calculated based on the weight of the heated sample and the initial weight.

[0031] Specifically, according to the instrumental method for industrial analysis of coal in GB / T30732-2014, the volatile matter was determined by measuring the volatile matter V of the sample. daf Determined by automatic industrial analyzer.

[0032] Weigh a certain amount of general analysis test coal sample, heat it in a heating furnace at (900±10)℃ in an air-tight state for 7 minutes, and take the mass fraction of the reduced mass in the coal sample minus the mass fraction of moisture in the coal sample as the mass fraction of volatile matter in the coal sample.

[0033] In the weighing room of the measuring instrument, accurately weigh the crucible that has been dried to a constant mass in advance, add (1±0.01)g of the general analysis test coal sample into the crucible, flatten it and accurately weigh it. The lignite and long flame coal samples should be pressed into cakes first, and then cut into small pieces with a particle size of about 3mm.

[0034] The high-temperature furnace is preheated to 900℃-920℃. The sample receiving and conveying device sends the covered crucible into the constant temperature zone of the high-temperature furnace. After accurate heating for 7 minutes, it is sent back to the weighing room and weighed again after cooling to the set temperature.

[0035] After the volatile matter crucible is placed in the high-temperature furnace, the furnace temperature should be restored to (900±10)℃ within 3 minutes, and then maintained at (900±10)℃, otherwise the test will be invalid. The heating time includes the temperature recovery time.

[0036] Further, coal-measure samples are obtained and the reflectivity of the coal-measure samples is collected, specifically including: Obtain coal series samples and prepare test specimens, and collect microscopic images of the samples and preset standard materials in sequence through a microscope camera and an automatic stage under set conditions; Grayscale measurement is performed on all measuring points of the microscopic images of the sample and the preset standard material, a grayscale-random reflectivity relationship model is established through the standard material, and random reflectivity values ​​of all measuring points in the microscopic image of the sample are obtained according to the grayscale-random reflectivity relationship model; Based on the random reflectance value, the vitrinite effective measuring points are automatically identified through a preset vitrinite recognition model, and the random reflectance values ​​of each vitrinite effective measuring point are statistically analyzed to obtain the average and standard deviation of the vitrinite random reflectance of the sample.

[0037] Specifically, according to the image analysis method for automatic determination of random reflectance of vitrinite in coal in GB / T40485-2021, the reflectance R max Automated assay image analysis.

[0038] Under the conditions of microscope oil immersion objective and reflected light of vertical incident light (λ=546 nm), microscope camera and automatic stage were used to collect microscopic images of standard materials and samples in sequence.

[0039] Grayscale measurements were performed on all measuring points of the standard material and sample microscopic images, and a grayscale-random reflectivity relationship model was established using the standard material. The random reflectivity values ​​of all measuring points in the sample image were calculated based on the model.

[0040] The effective vitrinite measuring points are automatically identified through the vitrinite recognition model, and the random reflectance values ​​of each effective vitrinite measuring point are statistically analyzed to obtain the average and standard deviation of the vitrinite random reflectance of the sample.

[0041] The collection of volatile matter and reflectivity of the sample can assist in the subsequent preliminary judgment of whether the coal-bearing sample is coal-bearing graphite.

[0042] Step 200: Compare the volatile matter and reflectivity with set thresholds respectively to generate a preliminary identification result.

[0043] Specifically, after obtaining the volatile content of the sample, enter the measurement results, set the program batch determination, and the volatile content V daf Samples with a reflectivity of less than 5.0% can be subjected to XRD (X-ray polycrystalline diffraction) spectrum intelligent analysis, otherwise they are judged to be non-coal-based graphite. After obtaining the average and standard deviation of the sample's vitrinite random reflectivity, enter the analysis results, set the program batch judgment, and the reflectivity R max Samples with a content of >6.0% can be subjected to intelligent analysis of XRD patterns, otherwise they are judged to be non-coal-based graphite.

[0044] After comparing the volatile matter and reflectivity with the set threshold, it can be preliminarily determined whether it is coal-based graphite.

[0045] Step 300: Based on the preliminary identification result, a preset X-ray polycrystal diffractometer is used to perform intelligent analysis of the spectrum to obtain the interplanar spacing.

[0046] In the present invention, based on the preliminary identification results, a copper target is irradiated by a preset X-ray polycrystal diffractometer to obtain an X-ray diffraction pattern data set; Based on the X-ray diffraction spectrum data set, the obtained sample X-ray diffraction spectrum is base-subtracted and smoothed, and the crystal plane diffraction peaks are displayed within the set scanning range; The interplanar spacing is calculated based on the crystal plane diffraction peak using a preset Bragg equation.

[0047] Specifically, X-ray diffraction tests were performed using Cu target radiation (λ = 0.15406 nm), an X-ray tube voltage of 40 Kv, a current of 100 mA, a scanning range (2θ) of 5 to 70°, and a scanning rate of 1 to 2° / min.

[0048] An X-ray diffraction spectrum data set was prepared, and the obtained sample X-ray diffraction spectrum was subjected to background subtraction and smoothing by using Jade software, etc., to display a (002) crystal plane diffraction peak near 2θ=26°.

[0049] Set the program to automatically calculate the interplanar spacing parameter d according to the Bragg equation in batches 002 value.

[0050] d 002 =nλ / 2sinθ 002 .

[0051] Where: n is the diffraction order (n=1); d002 is the (002) crystal plane spacing (nm); λ is the X-ray wavelength (λ=0.15406nm); θ 002 is the diffraction angle corresponding to the (002) diffraction peak (°).

[0052] Batch determination of interplanar spacing d 002 Is it between 0.3354 nm and 0.3440 nm? If not, the sample is not coal-based graphite. If so, proceed to the next step of Raman spectrum intelligent analysis to assist in identifying coal-based graphite.

[0053] Since coal-based graphite is a collection of multiple components, the structural parameters obtained from XRD analysis are the average values ​​of the components with the highest and lowest graphitization degrees. Therefore, it is difficult to reflect the uneven characteristics of the structure of coal-based graphite, which may lead to an underestimation of the true graphitization degree of the sample. Raman spectroscopy belongs to micro-area analysis and can obtain the structural parameters of different graphitized components. As an auxiliary analysis of XRD, it can more comprehensively identify coal-based graphite and classify its types.

[0054] Step 400: Perform Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters.

[0055] When a beam of monochromatic light is irradiated to the sample to be measured, the frequency of most of the scattered light is equal to the frequency of the incident light, and this part of the scattering is usually called Rayleigh scattering. Other scatterings with frequencies not equal to the incident frequency are called Raman scattering, and their intensity is generally less than one thousandth of Rayleigh scattering. The difference between the frequency of Raman scattering and the frequency of the incident light is called Raman shift, also commonly called Raman spectrum frequency, which is equal to the transition frequency between the rotational energy level, vibrational energy level and electronic energy level of the molecular system. Raman scattering with a frequency lower than the frequency of the incident light is called Stokes-Raman scattering; Raman scattering with a frequency higher than the frequency of the incident light is called anti-Stokes-Raman scattering, and the latter has a weaker intensity. Because the Raman scattering signal is weak and often encounters interference from fluorescence, different laser light sources are often selected according to different research objects. Commonly used laser wavelengths are 514.5 nanometers (green light) and 488.0 nanometers (blue light).

[0056] In the present invention, the sample is scanned by a preset Raman spectrometer based on the interplanar spacing to obtain a Raman spectrum data set; Based on the Raman spectrum data set, the Raman spectrum background noise is removed by a preset software, and the peak area data of the characteristic peaks of the Raman spectrum are obtained by performing peak fitting by a preset function; The Raman parameters are automatically calculated based on the peak area data of the characteristic peaks of the Raman spectrum through a set program.

[0057] Specifically, a Raman spectrometer equipped with a 532 nm (or 514 nm, 633 nm) excitation source with a spectral resolution better than 2 cm -1 The laser power is 100 mW and the scanning range is set to 100 cm -1 ~3000 cm -1 , the integration time is selected from 10 s to 60s.

[0058] Prepare Raman spectrum data set, remove Raman spectrum background noise through software, use Lorentz function or Gauss function for peak fitting, and obtain peak area data of Raman spectrum characteristic peaks (G peak, D1 peak and D2 peak).

[0059] Set the program to automatically calculate the Raman parameter R2=A in batches D1 / (A D1 +A D2 +A G ) is used to evaluate the degree of defect development in the graphite microcrystalline structure. The smaller the R2 value, the smaller the proportion of disordered carbon, the fewer structural defects, and the more complete the graphite lattice.

[0060] Where: R2 is the area ratio of peak D to peak G; A D1 is the area of ​​D1 peak; A D2 is the area of ​​D2 peak; A G is the area of ​​the G peak.

[0061] Determine in batches whether the Raman parameter R2 is ≤0.6. If not, the sample is not coal-based graphite. If so, it is determined to be coal-based graphite and can be subsequently classified.

[0062] Step 500: Generate a final identification result based on the interval of the interplanar spacing and the Raman parameter, and classify the coal-based graphite according to the final identification result.

[0063] In the present invention, the sample is prepared according to (1) 0.3354 nm ≤ d 002 <0.3380, R2<0.5; (2) 0.3380 nm≤ d 002 <0.3400, 0.5≤ R2≤0.6; (3) 0.3400nm≤ d 002 ≤ 0.3440, 0.5≤ R2≤0.6 are divided into three categories.

[0064] Coal-based graphite No. 1 has a relatively complete graphite crystal structure and has been widely used; Coal-bearing graphite No. 2 has certain structural defects, and its macerals still include residual organic components of coal rock, which are partially processed and utilized; Coal-based graphite No. 3 is a product of the early stage of coal graphitization and has certain graphite performance processing and utilization potential.

[0065] Based on the intelligent identification and appraisal method of coal-based graphite provided by the present invention, the volatile matter and reflectivity of the coal-based sample are obtained, batch parameter calculation is performed on the sample spectrum, and it is identified whether it is in the coal-based graphite parameter range. If it meets the interval value, it is determined to be coal-based graphite; and the coal-based graphite is intelligently classified by performing intelligent analysis of the spectrum based on an X-ray polycrystal diffractometer and intelligent analysis through Raman spectroscopy.

[0066] refer to Figure 2 and Figure 3 The present invention also discloses a coal-based graphite intelligent identification system, the system comprising: The data acquisition module 110 is used to obtain coal-bearing samples and collect volatile matter and reflectivity of the coal-bearing samples; A preliminary identification module 120, for comparing the volatile matter and reflectivity with set thresholds respectively, and generating a preliminary identification result; A diffraction analysis module 130 is used to perform intelligent analysis of the spectrum based on the preliminary identification result through a preset X-ray polycrystal diffractometer to obtain the interplanar spacing; A Raman spectrum analysis module 140 is used to perform Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; The result output module 150 is used to generate a final identification result based on the interval of the interplanar spacing and the Raman parameter, and classify the coal-based graphite according to the final identification result.

[0067] Among them, obtaining coal-measure samples and collecting volatile components of coal-measure samples specifically include: Obtain coal series samples, make samples of specific specifications and weigh the initial weight; heating the sample and weighing the heated sample; The volatile matter is calculated based on the weight of the heated sample and the initial weight.

[0068] Obtain coal-measure samples and collect the reflectivity of coal-measure samples, including: Obtain coal series samples and prepare test specimens, and collect microscopic images of the samples and preset standard materials in sequence through a microscope camera and an automatic stage under set conditions; Grayscale measurement is performed on all measuring points of the microscopic images of the sample and the preset standard material, a grayscale-random reflectivity relationship model is established through the standard material, and random reflectivity values ​​of all measuring points in the microscopic image of the sample are obtained according to the grayscale-random reflectivity relationship model; Based on the random reflectance value, the vitrinite effective measuring points are automatically identified through a preset vitrinite recognition model, and the random reflectance values ​​of each vitrinite effective measuring point are statistically analyzed to obtain the average and standard deviation of the vitrinite random reflectance of the sample.

[0069] Based on the preliminary identification results, the spectrum is intelligently analyzed by a preset X-ray multi-crystal diffractometer to obtain the interplanar spacing, which specifically includes: Based on the preliminary identification results, a copper target is irradiated by a preset X-ray polycrystal diffractometer to obtain an X-ray diffraction pattern data set; Based on the X-ray diffraction spectrum data set, the obtained sample X-ray diffraction spectrum is base-subtracted and smoothed, and the crystal plane diffraction peaks are displayed within the set scanning range; The interplanar spacing is calculated based on the crystal plane diffraction peak using a preset Bragg equation.

[0070] Based on the interplanar spacing, Raman spectrum analysis is performed to obtain Raman parameters, which specifically include: Scanning the sample by a preset Raman spectrometer based on the interplanar spacing to obtain a Raman spectrum data set; Based on the Raman spectrum data set, the Raman spectrum background noise is removed by a preset software, and the peak area data of the characteristic peaks of the Raman spectrum are obtained by performing peak fitting by a preset function; The Raman parameters are automatically calculated based on the peak area data of the characteristic peaks of the Raman spectrum through a set program.

[0071] The final identification result is generated based on the interval of the interplanar spacing and the Raman parameter, and the coal-based graphite is classified according to the final identification result, specifically including: Based on the interval of the interplanar spacing and the Raman parameter, determine whether it is coal-based graphite, and generate a final identification result; Coal-bearing graphite is classified based on the interval range in the identification results.

[0072] An intelligent recognition and identification system for coal-based graphite provided by the present invention obtains the volatile matter and reflectivity of the coal-based sample, performs batch parameter calculation on the sample spectrum, identifies whether it is within the coal-based graphite parameter range, and determines it to be coal-based graphite if it meets the range value; and intelligently classifies the coal-based graphite by performing intelligent spectrum analysis based on an X-ray polycrystal diffractometer and intelligent analysis through Raman spectroscopy.

[0073] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute a method for intelligent identification and appraisal of coal-based graphite, the method comprising: obtaining a coal-based sample, collecting the volatile matter and reflectivity of the coal-based sample; comparing the volatile matter and reflectivity with the set thresholds respectively to generate a preliminary identification result; based on the preliminary identification result, performing intelligent analysis of the spectrum through a preset X-ray polycrystalline diffractometer to obtain the interplanar spacing; performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; generating a final identification result based on the interval of the interplanar spacing and the Raman parameters, and classifying the coal-based graphite according to the final identification result.

[0074] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0075] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a method for intelligent identification and appraisal of coal-based graphite provided by the above methods, the method including: obtaining a coal-based sample, and collecting the volatile matter and reflectivity of the coal-based sample; comparing the volatile matter and reflectivity with set thresholds respectively to generate a preliminary identification result; based on the preliminary identification result, performing intelligent spectrum analysis through a preset X-ray polycrystal diffractometer to obtain the crystal plane spacing; performing Raman spectrum analysis based on the crystal plane spacing to obtain Raman parameters; generating a final identification result based on the interval of the crystal plane spacing and Raman parameters, and classifying the coal-based graphite according to the final identification result.

[0076] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a method for intelligent identification and appraisal of coal-bearing graphite provided by the above-mentioned methods, the method comprising: obtaining a coal-bearing sample, and collecting the volatile matter and reflectivity of the coal-bearing sample; comparing the volatile matter and reflectivity with set thresholds respectively to generate a preliminary identification result; based on the preliminary identification result, performing intelligent spectrum analysis through a preset X-ray polycrystal diffractometer to obtain the crystal plane spacing; performing Raman spectrum analysis based on the crystal plane spacing to obtain Raman parameters; generating a final identification result based on the interval of the crystal plane spacing and the Raman parameters, and classifying the coal-bearing graphite according to the final identification result.

[0077] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0078] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent identification and appraisal of coal-based graphite, characterized in that: include: Obtain coal-measure samples, and collect the volatile matter and reflectivity of the coal-measure samples; Comparing the volatile matter and reflectance with set thresholds respectively to generate a preliminary identification result; Based on the preliminary identification results, a spectrum intelligent analysis is performed using a preset X-ray polycrystal diffractometer to obtain the interplanar spacing; Performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; A final identification result is generated based on the interval of the interplanar spacing and the Raman parameter, and the coal-based graphite is classified according to the final identification result.

2. The method for intelligent identification and appraisal of coal-based graphite according to claim 1, characterized in that: The step of obtaining the coal-measure sample and collecting the volatile matter of the coal-measure sample specifically includes: Obtain coal series samples, make samples of specific specifications and weigh the initial weight; heating the sample and weighing the heated sample; The volatile matter is calculated based on the weight of the heated sample and the initial weight.

3. The method for intelligent identification and appraisal of coal-based graphite according to claim 1, characterized in that: The obtaining of the coal-measure sample and collecting the reflectivity of the coal-measure sample specifically includes: Obtain coal series samples and prepare test specimens, and collect microscopic images of the samples and preset standard materials in sequence through a microscope camera and an automatic stage under set conditions; Grayscale measurement is performed on all measuring points of the microscopic images of the sample and the preset standard material, a grayscale-random reflectivity relationship model is established through the standard material, and random reflectivity values ​​of all measuring points in the microscopic image of the sample are obtained according to the grayscale-random reflectivity relationship model; Based on the random reflectance value, the vitrinite effective measuring points are automatically identified through a preset vitrinite recognition model, and the random reflectance values ​​of each vitrinite effective measuring point are statistically analyzed to obtain the average and standard deviation of the vitrinite random reflectance of the sample.

4. The method for intelligent identification and appraisal of coal-based graphite according to claim 1, characterized in that: The method of performing intelligent analysis of the spectrum based on the preliminary identification result by a preset X-ray polycrystal diffractometer to obtain the interplanar spacing specifically includes: Based on the preliminary identification results, a copper target is irradiated by a preset X-ray polycrystal diffractometer to obtain an X-ray diffraction pattern data set; Based on the X-ray diffraction spectrum data set, the obtained sample X-ray diffraction spectrum is base-subtracted and smoothed, and the crystal plane diffraction peaks are displayed within the set scanning range; The interplanar spacing is calculated based on the crystal plane diffraction peak using a preset Bragg equation.

5. The method for intelligent identification and appraisal of coal-based graphite according to claim 1, characterized in that: The Raman spectrum analysis based on the interplanar spacing is performed to obtain Raman parameters, specifically including: Scanning the sample by a preset Raman spectrometer based on the interplanar spacing to obtain a Raman spectrum data set; Based on the Raman spectrum data set, the Raman spectrum background noise is removed by a preset software, and the peak area data of the characteristic peaks of the Raman spectrum are obtained by performing peak fitting by a preset function; The Raman parameters are automatically calculated based on the peak area data of the characteristic peaks of the Raman spectrum through a set program.

6. The method for intelligent identification and appraisal of coal-based graphite according to claim 1, characterized in that: The generating of the final identification result based on the interval of the interplanar spacing and the Raman parameter, and classifying the coal-based graphite according to the final identification result, specifically includes: Based on the interval of the interplanar spacing and the Raman parameter, determine whether it is coal-based graphite, and generate a final identification result; Coal-bearing graphite is classified based on the interval range in the identification results.

7. An intelligent identification system for coal-based graphite, characterized in that: The system comprises: The data acquisition module is used to obtain coal-measure samples and collect the volatile matter and reflectivity of the coal-measure samples; A preliminary identification module, used to compare the volatile matter and reflectivity with set thresholds respectively to generate a preliminary identification result; A diffraction analysis module, used to perform intelligent analysis of the spectrum based on the preliminary identification results through a preset X-ray polycrystal diffractometer to obtain the interplanar spacing; A Raman spectrum analysis module, used for performing Raman spectrum analysis based on the interplanar spacing to obtain Raman parameters; The result output module is used to generate a final identification result based on the interval of the crystal plane spacing and the Raman parameter, and classify the coal-based graphite according to the final identification result.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for intelligent identification and appraisal of coal-based graphite as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method for intelligent identification and appraisal of coal-based graphite as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the method for intelligent identification and appraisal of coal-based graphite as described in any one of claims 1 to 6.

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