Coal vitrinite reflectivity identification method

Abstract

The invention belongs to the technical field of coal vitrinite reflectance detection, and particularly relates to a coal vitrinite reflectance identification method, which is characterized in that the initial reflectance of a coal sample measured by a reflectance detection instrument is compensated based on the evaluation result of the influence brought by the test temperature to obtain the accurate vitrinite reflectance; the method comprises the following steps: firstly, performing compensation on the coal vitrinite reflectivity, secondly, performing evaluation calculation on an accurate abnormal coefficient of the vitrinite reflectivity obtained after compensation, and finally, calculating multiple groups of vitrinite reflectivity with qualified abnormal coefficient evaluation calculation, so that in the process of detecting the vitrinite reflectivity of the coal, not only is the influence brought by test temperature considered, but also the detection accuracy is improved. The abnormal influence of the impurities locally accumulated in the coal on the detection result is more comprehensively considered, and the comprehensiveness and accuracy of the detection result can be effectively improved by effectively and organically combining the influence of the test temperature and the influence of the impurities locally accumulated in the coal on the detection result in the same evaluation system.

Description

Technical Field

[0001] This invention belongs to the field of coal vitrinite reflectance detection technology, and specifically relates to a method for identifying coal vitrinite reflectance. Background Technology

[0002] The vitrinite reflectance of coal is an important indicator for evaluating the degree of coal metamorphism and classification. It is widely used in coal exploration, washing and processing, and coking industries. Its measurement results are directly related to the rational utilization of coal resources and the quality control of industrial production. The traditional determination of vitrinite reflectance mainly relies on optical microscopes in conjunction with photoelectric detection equipment. The reflectance value is calculated by measuring the intensity of reflected light from the vitrinite under a specific wavelength of light.

[0003] Because the core detector of a reflectance microscope is a photomultiplier tube, which is highly sensitive to temperature, the dark current of the photomultiplier tube, i.e., thermal noise, increases significantly as the ambient temperature rises. This noise is superimposed on the actual reflected light signal, thus affecting the accuracy of the measurement readings. Current technologies generally eliminate the influence of dynamic changes in ambient temperature on reflectance measurements by controlling the temperature in the laboratory. This is not only cumbersome and increases experimental costs, but also, in some special testing situations, it is not conducted in a laboratory where constant temperature conditions are not available. The above-mentioned method of eliminating the influence of dynamic changes in ambient temperature on reflectance measurements has limitations. Furthermore, current measurement technologies do not introduce anomaly coefficient evaluation and secondary verification mechanisms, resulting in limited reliability of measurement data.

[0004] To address the aforementioned issues, this application presents a method for identifying the vitrinite reflectance of coal. Summary of the Invention

[0005] To address the shortcomings of the prior art mentioned in the background section, this application proposes a method for identifying the reflectance of coal vitrinite, which fully considers the impact of changes in test temperature on the accuracy of reflectance measurement, thereby solving the problems in the background section.

[0006] Firstly, to achieve the above objectives, this application provides a method for identifying the vitrinite reflectance of coal, which includes the following specific steps:

[0007] S1. Calibrate the reflectivity measuring instrument using a certified standard sheet under standard operating voltage and temperature;

[0008] S2. Sample coal samples are tested using a calibrated reflectance testing instrument to obtain the initial reflectance of the coal samples. ;

[0009] S3. Based on the initial reflectance of the coal sample measured in step S2. vitrinite reflectance of coal samples The formula for calculating the reflectance of the vitrinite group is as follows: ,in ;

[0010] S4. The vitrinite reflectance calculated from the sampling in step S3. Process the data to remove outliers with large errors;

[0011] The vitrinite reflectance calculated from the sampling in step S3 The process of removing outlier data with significant detection errors includes the following steps:

[0012] S41. Extract the vitrinite reflectance calculated from the sampling in step S3. ,right The anomaly coefficient is evaluated and calculated. The formula for calculating the anomaly coefficient is: Where a is the weighting coefficient 0 a 1, The reflectance of the vitrinite group measured for group t. The value, vitrinite reflectance Maximum safe range For the first vitrinite group reflectance The value;

[0013] S42. Calculate the anomaly coefficient. The value is compared with the set interval threshold, and if the calculated anomaly coefficient is... If the value is outside the set threshold range, a secondary detection calculation is performed on that point. If the abnormality coefficient calculated in the secondary detection is... If the value is within the set threshold range, it is retained; otherwise, the abnormality coefficient calculated by the secondary detection is not considered. If the value is still outside the set range threshold, then the data item is excluded;

[0014] S43, Regarding the outlier coefficient Multiple sets of vitrinite reflectance falling within the interval threshold Calculations were performed to obtain the reflectance of the vitrinite group. average As the final vitrinite reflectance of coal;

[0015] S5. Calculated vitrinite reflectance average Records are stored, reflectivity distribution maps and test reports are generated, and pushed to pre-designated managers or auditors.

[0016] Based on the above scheme, the preferred embodiment is the initial reflectance of the coal sample measured in step S2. vitrinite reflectance of coal samples The calculation includes the following steps:

[0017] S31, Based on the initial reflectance measured in step S2 Reflectance of vitrinite Calculations were performed to determine the initial reflectance when the actual measurement temperature was higher than the reference temperature. The value of vitrinite reflectance will be lower due to the influence of external temperature. The calculation formula is: Conversely, when the actual measurement temperature is lower than the reference temperature, the measured initial reflectance... The value will be too high, at which point the reflectance of the vitrinite group will be higher. The calculation formula is: ,in The set standard temperature value, , All are actual temperature values ​​measured during the measurement, and , for ;

[0018] S32. Calculate the vitrinite reflectance. Import it into step S4 for processing.

[0019] Based on the above scheme, the preferred option is... The following methods are included:

[0020] Method 1: Repeatedly test the standard sheet under the same voltage but different temperatures to measure the reflectivity of the standard sheet at different temperatures, and then perform curve fitting on the discrete data points obtained from the experiment to obtain a continuous function.

[0021] Method 2: Based directly on discrete data obtained from measuring the standard sample, calculate the difference. This is used to approximate the rate of change within the corresponding temperature range.

[0022] Based on the above scheme, the preferred option is the one regarding the anomaly coefficient. Multiple groups of vitrinite reflectance falling within the threshold range Calculations were performed to obtain the reflectance of the vitrinite group. average The calculation formula is: = ,in, The vitrinite reflectance measured for the i-th time , The reflectance of the vitrinite group used in the calculation The quantity.

[0023] In a preferred embodiment of the above scheme, when calibrating the reflectivity testing instrument using a certified standard sheet at standard operating voltage and temperature, the software inside the reflectivity testing instrument will automatically adjust the amplification gain and offset of its photoelectric signal so that the measured value of the standard sheet is equal to the true value on its certificate.

[0024] Based on the above scheme, the preferred method involves repeatedly testing the standard sheet under the same voltage but different temperatures to measure its reflectivity at different temperatures. Then, the discrete data points obtained from the experiment are fitted with a curve to obtain a continuous function. Specifically, this includes the following steps:

[0025] Step 1: Select a standard film with stable reflectivity;

[0026] Step 2: Under the set reference temperature and the instrument's standard operating voltage, measure the reflectivity of the standard sheet to obtain the reading R1, and use R1 as the standard value.

[0027] Step 3: Gradually increase or decrease the temperature during the test, and measure the reflectance of the same standard sheet at different temperatures to obtain the reading R2;

[0028] Step 4: Enter the measured data points into plotting software such as Excel for linear fitting to obtain the results. .

[0029] Secondly, this application provides a coal vitrinite reflectance identification system, which is based on the aforementioned coal vitrinite reflectance identification method. Specifically, it includes: a reflectance detection instrument used to sample and test coal to obtain the initial reflectance of the coal sample. ;

[0030] A calculation module with temperature compensation function is used to calculate the initial reflectance of the coal sample measured in step S2. vitrinite reflectance of coal samples Perform calculations;

[0031] The calculation module with anomaly data evaluation function is used to evaluate the vitrinite reflectance calculated from the sampling data in step S3. The data is processed to remove outliers with large detection errors, and the reflectance of the vitrinite group is finally calculated. average ;

[0032] The smart terminal calculates the reflectance of the vitrinite group. average Records are stored, reflectivity distribution maps and test reports are generated, and pushed to pre-designated management or auditing personnel;

[0033] The control module is used to control the operation of the reflectivity detection instrument, the calculation module with temperature compensation function, the calculation module with abnormal data evaluation function, and the smart terminal.

[0034] Thirdly, this application provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0035] The processor executes the aforementioned method for identifying the reflectance of vitrinite in coal by calling a computer program stored in the memory.

[0036] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the coal vitrinite reflectance identification method described above.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] This invention first evaluates and calculates the impact of test temperature on data obtained from repeated measurements of standard samples at different experimental temperatures. Then, based on the evaluation results of the impact of test temperature, the initial reflectance of the coal sample measured by the reflectance testing instrument is compensated to obtain a more accurate vitrinite reflectance. Next, the anomaly coefficient of the more accurate vitrinite reflectance obtained after compensation is evaluated and calculated. Finally, the average vitrinite reflectance is calculated from multiple sets of vitrinite reflectances that have passed the anomaly coefficient evaluation. As the final vitrinite reflectance of coal, the detection process not only considers the influence of test temperature, but also the abnormal influence of locally accumulated impurities in the coal on the test results. By effectively combining the influence of test temperature and the influence of locally accumulated impurities in the coal on the test results in the same evaluation system, the comprehensiveness and accuracy of the test results can be effectively improved. Attached Figure Description

[0039] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0040] Figure 1 This is a schematic diagram of the overall process of a method for identifying the vitrinite reflectance of coal according to the present invention;

[0041] Figure 2 This is a flowchart of step S4 in the coal vitrinite reflectance identification method of the present invention.

[0042] Figure 3This is a system block diagram of a method for identifying the vitrinite reflectance of coal according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1

[0045] To address the technical problems raised in the background art, this application provides a preferred embodiment: such as Figures 1-3 As shown, a method for identifying the vitrinite reflectance of coal includes the following specific steps:

[0046] S1. Calibrate the reflectivity measuring instrument using a certified standard sheet under standard operating voltage and temperature;

[0047] S2. Sample coal samples are tested using a calibrated reflectance testing instrument to obtain the initial reflectance of the coal samples. ;

[0048] S3. Based on the initial reflectance of the coal sample measured in step S2. vitrinite reflectance of coal samples The formula for calculating the reflectance of the vitrinite group is as follows: ,in ;

[0049] S4. The vitrinite reflectance calculated from the sampling in step S3. Process the data to remove outliers with large errors;

[0050] The vitrinite reflectance calculated from the sampling in step S3 The process of removing outlier data with significant detection errors includes the following steps:

[0051] S41. Extract the vitrinite reflectance calculated from the sampling in step S3. ,right The anomaly coefficient is evaluated and calculated. The formula for calculating the anomaly coefficient is: Where a is the weighting coefficient 0 a 1, The reflectance of the vitrinite group measured for group t. The value, vitrinite reflectance Maximum safe range For the first vitrinite group reflectance The value;

[0052] S42. Calculate the anomaly coefficient. The value is compared with the set interval threshold, and if the calculated anomaly coefficient is... If the value is outside the set threshold range, a secondary detection calculation is performed on that point. If the abnormality coefficient calculated in the secondary detection is... If the value is within the set threshold range, it is retained; otherwise, the abnormality coefficient calculated by the secondary detection is not considered. If the value is still outside the set range threshold, then the data item is excluded;

[0053] S43, Regarding the outlier coefficient Multiple groups of vitrinite reflectance falling within the threshold range Calculations were performed to obtain the reflectance of the vitrinite group. average As the final vitrinite reflectance of coal;

[0054] S5. Calculated vitrinite reflectance average Records are stored, reflectivity distribution maps and test reports are generated, and pushed to pre-designated managers or auditors.

[0055] Furthermore:

[0056] In an optional embodiment, based on the initial reflectance of the coal sample measured in step S2 vitrinite reflectance of coal samples The calculation includes the following steps:

[0057] S31, Based on the initial reflectance measured in step S2 Reflectance of vitrinite Calculations were performed to determine the initial reflectance when the actual measurement temperature was higher than the reference temperature. The value of vitrinite reflectance will be lower due to the influence of external temperature. The calculation formula is: Conversely, when the actual measurement temperature is lower than the reference temperature, the measured initial reflectance... The value will be too high, at which point the reflectance of the vitrinite group will be higher. The calculation formula is: ,in The set standard temperature value, , All are actual temperature values ​​measured during the measurement, and , for ;

[0058] S32. Calculate the vitrinite reflectance. Import it into step S4 for processing.

[0059] It should be noted that the core detector of a reflectance microscope is a photomultiplier tube (PMT), which is highly sensitive to temperature. As the ambient temperature rises, the dark current of the PMT, i.e., thermal noise, increases significantly. This noise is superimposed on the actual reflected light signal, causing the detector's output signal baseline to rise. When measuring coal samples, this can lead to an overestimation of the voltage reading, because the instrument calculates reflectance based on... The calculation is performed because of noise. The noise is superimposed on both the sample signal and the standard sample signal, which will change the ratio and distort the ratio. This will eventually lead to the measured reflectance value being lower than the standard value. Conversely, when the laboratory temperature is low, the measured reflectance value will be higher than the standard value. The purpose of step S31 is to add the amount of the lower value when the actual measurement temperature is higher than the reference temperature and the measured reflectance is lower than the standard value, and to subtract the amount of the higher value when the actual measurement temperature is lower than the reference temperature and the measured reflectance is higher than the standard value, so as to eliminate the error.

[0060] In an optional embodiment, the reflectivity-temperature change rate function is obtained through pre-calibration experiments, including the following methods:

[0061] Method 1: Repeatedly test the standard sheet under the same voltage but different temperatures to measure the reflectivity of the standard sheet at different temperatures, and then perform curve fitting on the discrete data points obtained from the experiment to obtain a continuous function.

[0062] Method 2: Based directly on discrete data obtained from measuring the standard sample, calculate the difference. This is used to approximate the rate of change within the corresponding temperature range.

[0063] Furthermore:

[0064] In an optional embodiment, the anomaly coefficient is... Multiple groups of vitrinite reflectance falling within the threshold range Calculations were performed to obtain the reflectance of the vitrinite group. average The calculation formula is: = ,in, The vitrinite reflectance measured for the i-th time , The reflectance of the vitrinite group used in the calculation The quantity.

[0065] In an optional embodiment, when calibrating the reflectivity meter using a certified standard sheet at standard operating voltage and temperature, the reflectivity meter's internal software automatically adjusts the amplification gain and offset of its photoelectric signal so that the measured value of the standard sheet equals the true value on its certificate.

[0066] In an optional embodiment, the standard sheet is repeatedly tested at the same voltage but different temperatures to measure its reflectivity at different temperatures. The discrete data points obtained from the experiment are then fitted with a curve to obtain a continuous function. Specifically, this includes the following steps:

[0067] Step 1: Select a standard film with stable reflectivity;

[0068] Step 2: Under the set reference temperature and the instrument's standard operating voltage, measure the reflectivity of the standard sheet to obtain the reading R1, and use R1 as the standard value.

[0069] Step 3: Gradually increase or decrease the temperature during the test, and measure the reflectance of the same standard sheet at different temperatures to obtain the reading R2;

[0070] Step 4: Enter the measured data points into plotting software such as Excel for linear fitting to obtain the reflectance-temperature change rate function.

[0071] It should be noted that the discrete data points measured in the above experiment were completed on the same instrument, at the same time, and using the same standard sample.

[0072] Example 2

[0073] Based on the same inventive concept as in Embodiment 1, such as Figure 1 As shown, this embodiment provides a coal vitrinite reflectance identification system, which specifically includes: a reflectance detection instrument, used to sample and test coal to obtain the initial reflectance of the coal sample to be tested. ;

[0074] A calculation module with temperature compensation function is used to calculate the initial reflectance of the coal sample measured in step S2. vitrinite reflectance of coal samples Perform calculations;

[0075] The calculation module with anomaly data evaluation function is used to evaluate the vitrinite reflectance calculated from the sampling data in step S3. The data is processed to remove outliers with large detection errors, and the reflectance of the vitrinite group is finally calculated. average ;

[0076] The smart terminal calculates the reflectance of the vitrinite group. average Records are stored, reflectivity distribution maps and test reports are generated, and pushed to pre-designated management or auditing personnel;

[0077] The control module is used to control the operation of the reflectivity detection instrument, the calculation module with temperature compensation function, the calculation module with abnormal data evaluation function, and the smart terminal.

[0078] The parameters and steps of each unit module in the coal vitrinite reflectance identification method of the present invention described above can be referred to the parameters and steps in the embodiments of the coal vitrinite reflectance identification method described above, and will not be repeated here.

[0079] Example 3

[0080] Based on the same inventive concept as Embodiment 1, this embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0081] The processor executes the aforementioned method for identifying the reflectance of vitrinite in coal by calling a computer program stored in the memory.

[0082] It should be noted that all computer programs for a method of identifying the reflectance of vitrinite in coal are implemented in C language. The reflectance detection instrument, the calculation module with temperature compensation function, the calculation module with abnormal data evaluation function, the intelligent terminal, and the control module are all controlled by a remote server.

[0083] Example 4

[0084] Based on the same inventive concept as in Embodiment 1, this embodiment proposes a computer-readable storage medium having an erasable and rewritable computer program stored thereon.

[0085] When a computer program runs on a computer device, it causes the computer device to execute the aforementioned method for identifying the reflectance of vitrinite in coal.

[0086] For example, computer-readable storage media can be read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, and optical data storage devices.

[0087] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, the embodiments for IoT devices and media are relatively simple in description because they are fundamentally similar to the method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0088] The systems, media, and methods provided in the embodiments of the present invention are in one-to-one correspondence. Therefore, the systems and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be repeated here.

[0089] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0094] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0095] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0096] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. The above are merely embodiments of the present invention and are not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A coal vitrinite reflectance identification method, characterized by, It comprises the following steps: S1, under standard working voltage and standard temperature, using certified standard pieces to calibrate the reflectance detection instrument; S2, sample detection is performed on the coal through the calibrated reflectance detection instrument to obtain the initial reflectivity of the coal sample to be detected ; S3, based on the initial reflectance of the coal sample measured in step S2 The vitrinite reflectance of the coal sample The calculation is performed, and the calculation formula of the vitrinite reflectance is wherein ; S4, calculating the vitrinite reflectance of the sample collected in step S3 The abnormal data with large error is removed by processing. The vitrinite reflectance calculated in the sampling and collecting of step S3 The processing to remove abnormal data having a large detection error includes the following steps. S41, extracting the vitrinite reflectivity calculated in the sampling and collecting step S3 The abnormal coefficient of the vitrinite reflectivity is calculated and evaluated, The abnormal coefficient of the vitrinite reflectivity is calculated and evaluated, The abnormal coefficient of the vitrinite reflectivity is calculated and evaluated, Wherein, a is the weight coefficient 0 a 1, is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group is the value of the vitrinite reflectivity measured in the tth group S42, comparing the value of the calculated abnormality coefficient with a set interval threshold value, if the value of the calculated abnormality coefficient is outside the set interval threshold value, performing a secondary detection calculation on the point, if the value of the abnormality coefficient calculated by the secondary detection calculation is within the set interval threshold value, retaining it, if the value of the abnormality coefficient calculated by the secondary detection calculation is still outside the set interval threshold value, excluding the data S43, abnormality coefficient groups of vitrinite reflectance falling within the interval threshold performing a calculation to obtain a mean value of the vitrinite reflectance of the coal as a final vitrinite reflectance of the coal S5, record the average value of the calculated vitrinite reflectance The reflectance distribution graph and the detection report are generated and pushed to the preset manager or auditor.​ 2. The coal vitrinite reflectance identification method according to claim 1, characterized in that: based on the initial reflectance of the coal sample measured in step S2 vitrinite reflectance of the coal sample The calculations include the following steps: S31, based on the initial reflectance measured in step S2 vitrinite reflectance When the temperature at the time of actual measurement is higher than the reference temperature, the measured initial reflectance is affected by the outside temperature and is lower in value, and the vitrinite reflectance is calculated by the following formula: On the other hand, when the temperature at the time of actual measurement is lower than the reference temperature, the measured initial reflectance is affected by the outside temperature and is higher in value, and the vitrinite reflectance is calculated by the following formula: wherein is a standard temperature value set in advance, , are temperature values at the time of actual measurement, and , is ; S32, the vitrinite reflectance calculated in S31 is stored in the database 2. The data imported into step S4 is processed.

3. The coal vitrinite reflectance identification method according to claim 2, characterized in that: The , including the following acquisition mode: Method one: under the same voltage and different temperatures, repeatedly test the standard pieces, measure the reflectance of the standard pieces at different temperatures, and perform curve fitting on the discrete data points measured in the experiment to obtain a continuous function; Method two: directly based on the discrete data obtained by measuring the standard piece, through the calculation of the difference to approximate the rate of change in the corresponding temperature interval.

4. The coal vitrinite reflectance identification method of claim 3, wherein: The abnormal coefficient Multiple groups of vitrinite reflectance falling within the threshold range Calculations were performed to obtain the reflectance of the vitrinite group. average The calculation formula is: = ,in, The vitrinite reflectance measured for the i-th time , The reflectance of the vitrinite group used in the calculation The quantity.

5. The coal vitrinite reflectance identification method according to claim 4, characterized in that: When the certified standard pieces are used to calibrate the reflectance detection instrument under standard working voltage and standard temperature, the software inside the reflectance detection instrument will automatically adjust the amplification gain and offset of the photoelectric signal, so that the measured value of the standard piece is equal to the true value on its certificate.

6. The coal vitrinite reflectance identification method according to claim 5, characterized in that: Under the same voltage and different temperatures, repeatedly test the standard pieces, measure the reflectance of the standard pieces at different temperatures, and perform curve fitting on the discrete data points measured in the experiment to obtain a continuous function, which comprises the following steps: Step one: select a standard piece with stable reflectance; Step two: under the standard working voltage of the instrument and the set reference temperature, measure the reflectance of the standard piece to obtain reading R1, and take R1 as the standard value; Step three: gradually increase or decrease the temperature during the test, measure the reflectance of the same standard piece at different temperatures to obtain reading R2; Step four: The measured multiple sets of data points are entered into a plotting software such as Excel for linear fitting, i.e. to obtain .

7. A coal vitrinite reflectance identification system based on the coal vitrinite reflectance identification method according to any one of claims 1 to 6, characterized in that, Specifically, the application comprises: a reflectivity detection instrument for sampling and detecting coal to obtain the initial reflectivity of the coal sample to be detected ; A computing module with temperature compensation function is used to calculate the initial reflectivity of the coal sample measured in step S2 The vitrinite reflectivity of the coal sample is calculated; A computing module with abnormal data evaluation function is used to calculate the vitrinite reflectivity of the sample collected in step S3 The abnormal data with larger detection error is removed by processing, and the average value of the vitrinite reflectivity is finally obtained ;​ The intelligent terminal records and stores the average value of the calculated vitrinite reflectivity generates a reflectivity distribution graph and a detection report, and pushes them to a preset manager or auditor​ A control module for controlling the operation of the reflectance detection instrument, the calculation module with temperature compensation function, the calculation module with abnormal data evaluation function, and the intelligent terminal.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor, characterized in that the processor executes a coal maceral reflectance identification method according to any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: An instruction is stored, which, when executed on a computer, causes the computer to execute a coal maceral reflectance identification method according to any one of claims 1-6.

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