A coal quality detection method, device, equipment and medium based on target calibration

Abstract

An embodiment of the present invention discloses a coal quality detection method, device, equipment and medium based on target calibration, which relates to the field of laser detection. The method includes: receiving current spectral data for a target substance, and determining a deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance. Among them, the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of spectral peaks and provide a reference benchmark for the determination of the deviation coefficient; receiving spectral data for coal quality, and calibrating the spectral data of the coal quality according to the deviation coefficient; determining the coal quality components according to the calibrated spectral data of the coal quality. The technical solution provided by the present invention can improve the accuracy of determining coal quality components and solve the problem of time-consuming and laborious manual detection of coal quality components.

Description

Technical Field

[0001] The present invention relates to the field of laser detection, and in particular, to a coal quality detection method, device, equipment and medium based on target calibration. Background Art

[0002] As an important current energy material, coal is widely used in various industrial productions. However, since other substances may be included in the coal mining process, it is necessary to detect its components to determine the concentration of coal or other substances, and then apply it to industrial production.

[0003] The current coal component detection method is mainly manual sampling, and then the sampled substances are detected in the laboratory to determine their components. However, the current detection method is time-consuming and laborious. Further, due to the limitations of the manual sampling method itself, the differences between different samples are large, resulting in low accuracy of coal component detection. Summary of the Invention

[0004] The present invention provides a coal quality detection method, device, equipment and medium based on target calibration. Through the technical solution provided by the present invention, the accuracy of coal quality component detection can be improved, and the problem of time-consuming and laborious manual detection can be solved.

[0005] In a first aspect, an embodiment of the present invention provides a coal quality detection method based on target calibration, including:

[0006] Receiving current spectral data for a target substance, and determining a deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance, wherein the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of spectral peaks and provide a reference benchmark for the determination of the deviation coefficient;

[0007] Receiving spectral data for coal quality, and calibrating the spectral data for coal quality according to the deviation coefficient;

[0008] Determining coal quality components according to the calibrated spectral data of coal quality.

[0009] In a second aspect, an embodiment of the present invention provides a coal quality detection device based on target calibration, including:

[0010] A deviation coefficient determination module, configured to receive current spectral data for a target substance, and determine a deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance, wherein the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of spectral peaks and provide a reference benchmark for the determination of the deviation coefficient;

[0011] A calibration module, configured to receive spectral data of coal quality and calibrate the spectral data of the coal quality according to the deviation coefficient;

[0012] A composition determination module, configured to determine the coal quality composition according to the calibrated spectral data of the coal quality.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, which includes:

[0014] At least one processor; and,

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the coal quality detection method based on target calibration according to any one of the embodiments of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions for enabling a processor to implement the coal quality detection method based on target calibration according to any one of the embodiments of the present invention when executed.

[0018] An embodiment of the present invention provides a coal quality detection method, device, equipment and medium based on target calibration. The method includes: receiving current spectral data of a target substance, determining a deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance, wherein the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize physical parameters of spectral peaks and provide a reference benchmark for determining the deviation coefficient; receiving spectral data of coal quality, calibrating the spectral data of the coal quality according to the deviation coefficient; and determining the coal quality composition according to the calibrated spectral data of the coal quality. Specifically, since the detection environment will affect the detection result, by determining the theoretical spectral data and the current spectral data of the target substance, the deviation coefficient characterizing the environmental impact can be determined, and then the spectral data of the coal quality can be calibrated with the deviation coefficient, so as to improve the accuracy of the spectral data of the coal quality, and further improve the accuracy of the coal quality composition detection. The technical solution provided by the present invention can improve the accuracy of the coal quality composition detection and solve the problem of time-consuming and laborious manual detection. Description of the Drawings

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0020] Figure 1 It is a flowchart of a coal quality detection method based on target calibration provided in Embodiment 1 of the present invention;

[0021] Figure 2 It is a flowchart of a coal quality detection method based on target calibration provided in Embodiment 2 of the present invention;

[0022] Figure 3 It is a schematic structural diagram of a coal quality detection device based on target calibration provided in Embodiment 3 of the present invention;

[0023] Figure 4 It is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed implementation manners

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0026] It should be noted that in the technical solutions of the present disclosure, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information and other processes all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0027] Embodiment 1

[0028] Figure 1 The figure is a flowchart of a coal quality detection method based on target calibration provided in the first embodiment of the present invention. This method can be applied to the component detection of coal mixtures / coal quality and can be executed by a coal quality detection device based on target calibration. This device can be implemented by software and / or hardware and is configured in various servers or computers.

[0029] As Figure 1 shown, it includes:

[0030] Step 110: Receive the current spectral data for the target substance, and determine the deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance. Among them, the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of the spectral peaks and provide a reference benchmark for the determination of the deviation coefficient.

[0031] Among them, the target substance is a high-purity substance containing specific spectral data and characteristics. The deviation impact of the detection environment on the overall detection work can be determined according to the laboratory data of the target substance and the actual data on site. In the embodiment of the present invention, the deviation coefficient can be determined according to the theoretical spectral data and the current spectral data of the target substance. Among them, the theoretical spectral data can be the spectral data of the target substance in the laboratory, and the current spectral data is the spectral data of the target substance in the current detection environment. Further spectral data can be a kind of laser-induced breakdown spectroscopy (LIBS) data, and this spectral data can be obtained by a LIBS detector, which is not limited here. It should be noted that the target substance can be substances with stable properties at room temperature, such as silicon dioxide, aluminum, copper, or graphite with a purity greater than 99.9%.

[0032] Since spectral detection has strict requirements on temperature, light, and humidity in the environment, and the actual detection environment is often very complex, the deviation coefficient is used to characterize the degree of deviation impact of the current environment on the detection result. If the deviation coefficient is too large, it means that there is a large deviation between the current spectral data and the theoretical spectral data, indicating that the current environment has a great impact on the detection result. If the coal quality component detection is carried out in the current environment, a large deviation will occur. Therefore, the deviation coefficient can be determined, and then the detection result can be calibrated using the deviation coefficient to improve the accuracy of the detection.

[0033] Specifically, the spectral data includes multiple spectral peaks. To accurately characterize the spectral peaks in the theoretical spectral data, corresponding spectral reference lines can be generated based on the spectral peaks in the theoretical spectral data, and then, based on the spectral reference lines, a standard reference can be provided for the determination of the calibration coefficient. For example, the corresponding deviation coefficient can be determined according to the intensity and wavelength of the spectral peaks in the current spectral data and the intensity and wavelength of the spectral peaks characterized by the spectral reference lines.

[0034] Optionally, the method for determining the spectral reference line of the theoretical spectral data includes:

[0035] Obtain the theoretical spectral data of the target substance in a preset environment, determine a set number of theoretical spectral peaks according to the physical parameters of the spectral peaks in the theoretical spectral data, and determine the spectral reference line according to the theoretical spectral peaks.

[0036] Among them, the physical parameters include the intensity and wavelength of the spectral peaks. Further, a reference system is established with the wavelength as the horizontal axis and the intensity as the vertical axis, and the perpendicular line from the peak point of the spectral peak to the horizontal axis is used as the spectral reference line of the spectral peak.

[0037] Optionally, obtain the theoretical spectral map of the target substance in a preset environment, where the number of spectral peaks in different optical bands of the theoretical spectral map exceeds a set number threshold;

[0038] For any optical band in the theoretical spectral map, determine a set number of theoretical spectral peaks according to the intensity of the spectral peaks in the optical band;

[0039] Determine the spectral reference line according to the intensity and wavelength of the theoretical spectral peaks.

[0040] Among them, the preset environment is the standard environment of the laboratory. The environment of the actual coal quality detection site can also be obtained in advance, and then the same environment can be set up in the laboratory as the preset environment, which is not limited here. Further, to ensure the accuracy of the calibration coefficient, the spectral lines of multiple spectral peaks can be determined, and the set number threshold is used to represent the minimum number of spectral peaks required for the determination of the deviation coefficient

[0041] Exemplarily, select the spectral peaks with the highest and the second highest intensities as the target theoretical spectral peaks, and then determine the spectral reference line according to the intensity and wavelength of the theoretical spectral peaks. Further, to ensure the accuracy of the test, multiple spectral reference lines can also be determined, and then a more accurate deviation coefficient can be determined, which is not limited here.

[0042] Step 120: Receive the spectral data of the coal quality, and calibrate the spectral data of the coal quality according to the deviation coefficient.

[0043] Specifically, the spectral data of coal quality can be the spectral data of LIBS for coal quality. The spectral data of coal quality includes the spectral data of each coal quality component in the coal quality, including the spectral peaks corresponding to each coal quality component. Specifically, due to the complexity of the detection environment, the spectral data of the actually detected coal quality will deviate, affecting the accuracy of detection. Therefore, the spectral data of coal quality can be calibrated according to the determined deviation coefficient. Specifically, the deviation coefficient can include an intensity deviation coefficient and a wavelength deviation coefficient, which are respectively used to calibrate the intensity and wavelength of the spectral peaks of coal quality. Then, the calibrated spectral data of coal quality is used for component detection to improve the accuracy of component detection.

[0044] Exemplarily, if the theoretical spectral data is A0 and the current spectral data is A1, the deviation coefficient P between A1 and A0 can be determined through the properties of A1 and A0. Here, P represents the fixed deviation caused by the detection environment in the detection result. Since the current detection environment is consistent, when detecting the spectral data of coal quality, the spectral data of coal quality will have the same deviation due to the detection environment. Therefore, the spectral data B0 of coal quality can be calibrated according to the deviation coefficient P to generate the calibrated spectral data B1 of coal quality. Then, the calibrated spectral data B1 of coal quality is used for component detection to improve the accuracy rate of component detection.

[0045] Optionally, determine the spectral peaks of coal quality components according to the spectral data of coal quality;

[0046] Calibrate the wavelength of the spectral peaks of the coal quality components according to the wavelength deviation coefficient;

[0047] Calibrate the intensity of the spectral peaks of the coal quality components according to the intensity deviation coefficient.

[0048] Among them, coal quality components can include coal, sand, iron or other components in the coal mixture. Each coal quality component corresponds to a unique spectral peak in the spectral data of coal quality. However, due to problems in the detection environment, the spectral peaks in the spectral data of coal quality may deviate. Therefore, the wavelength of the spectral peaks of the coal quality components can be calibrated according to the wavelength deviation coefficient; the intensity of the spectral peaks of the coal quality components can be calibrated according to the intensity deviation coefficient.

[0049] Step 130: Determine the coal quality components according to the calibrated spectral data of coal quality.

[0050] Optionally, step 130 includes: obtaining a base model, where the base model includes the wavelength data and intensity data of each coal quality component that may exist in the coal quality;

[0051] Based on the base model, determine the coal quality components actually existing in the coal quality represented by the spectral data according to the wavelength and intensity of the calibrated spectral peaks.

[0052] Specifically, the base model includes the wavelength data and intensity data of each coal quality component that may exist in the coal quality. By comparing the wavelength and intensity of the calibrated spectral peak with the wavelength data and intensity data in the base model, if the comparison is successful, it indicates that the coal quality includes this coal quality component.

[0053] Optionally, the embodiments of the present invention also provide a determination method for the base model and theoretical spectral data. Exemplarily, the training process of the base model includes:

[0054] The spectral, temperature, and humidity data generated by the LIBS instrument for the same batch of samples and the test result data obtained by traditional instruments according to national standards must be obtained under the same environmental temperature and humidity conditions, and this environmental temperature and humidity condition is set as the calibration reference condition. Generate the spectral, temperature, and humidity data of each sample under different temperature and humidity conditions, where the spectrum needs to subtract the background data of hitting air without placing the sample, that is, the original spectral data; the output data of the same batch of dry basis coal samples are obtained by traditional instruments of the manufacturer according to national standards, which can be the concentration of C, S, heavy metal elements, calorific value, ash content, etc., and the samples with outlier data must be excluded; clean the original spectral data set, and then screen out the abnormal outlier data;

[0055] Find 5 - 15 characteristic wavelengths with good repeatability and their intensities from the original spectral data as input data, and the 5 - 15 characteristic wavelengths and the range of about 5 nm on both sides of the wavelength are set as the sample characteristic wavelength detection range; establish a mapping data set by corresponding the input data and output data one by one according to the sample; divide the training set and prediction set, and use algorithms such as multiple linear algorithms or neural network fitting for fitting. When fitting, the output index is a single coal quality index, and optimize the parameter adjustment according to the prediction effect feedback; obtain a single - index output fitting model with spectral, temperature, and humidity data as input and data such as element content, calorific value, or ash content as output; package multiple single - index output fitting models in parallel, so that the entire model group takes spectral, temperature, and humidity data as input and multiple data such as element content, calorific value, or ash content as output, and multiple independent models inside are identified in parallel, and finally combine to obtain the base model under the calibration reference condition of the LIBS instrument.

[0056] Exemplarily, the generation method of theoretical spectral data includes:

[0057] Adjust the laboratory environment to the generation environment of the calibration reference condition, where the calibration reference condition includes conditions such as environmental temperature, humidity, and brightness.

[0058] The target is placed into the LIBS instrument for multiple detections respectively. The surface of the target is exactly located at the focal point of the pulsed laser for irradiation until spectral data with high repeatability and a relative standard deviation of <2% is obtained. The wavelengths and intensities of the extreme value peaks in each segmented spectrum are taken and set as the target characteristic wavelengths and intensities of the target under the calibration reference conditions. Targets of at least two substances are selected for detection to ensure that significant extreme value peaks exist in each segmented spectrum, and these extreme value peaks significantly exist during multiple observations and re-boot observations. Finally, the characteristic wavelengths and intensities of the extreme value peaks of multiple targets together form a spectral reference line in the full wavelength range.

[0059] Furthermore, at least two spectral reference lines can be set within each spectral segment, including their wavelength and intensity data. Exemplarily, when setting two spectral reference lines, the highest point and the second highest point can be taken to form a binary target reference system, such as target A + B. When there are multiple spectral segments, the calibration reference target characteristics under the calibration reference conditions are as follows: for the first spectral segment, the wavelength of peak 1 is a nm and the intensity is X, the wavelength of peak 2 is b nm and the intensity is Y; for the second spectral segment, the wavelength of peak 1 is c nm and the intensity is Z, the wavelength of peak 2 in the second spectral segment is d nm and the intensity is V, and so on. After combining the data of each spectral segment, theoretical spectral data is obtained.

[0060] An embodiment of the present invention provides a coal quality detection method based on target calibration. The method includes: receiving current spectral data for a target substance, determining the deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance. Among them, the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of spectral peaks and provide a reference benchmark for the determination of the deviation coefficient; receiving spectral data for coal quality, calibrating the spectral data of the coal quality according to the deviation coefficient; and determining the coal quality components according to the calibrated spectral data of the coal quality. Specifically, since the detection environment will affect the detection results, by determining the theoretical spectral data and the current spectral data of the target substance, the deviation coefficient characterizing the environmental impact can be determined, and then the spectral data of the coal quality can be calibrated with the deviation coefficient, which can improve the accuracy of the spectral data of the coal quality, and further improve the accuracy of the detection of the coal quality components. Among them, the deviation coefficient includes a wavelength deviation coefficient and an intensity deviation coefficient, which are used to calibrate the wavelength and intensity of the spectral peaks of the coal quality components. The technical solution provided by the present invention can improve the accuracy of the detection of the coal quality components and solve the problem of time-consuming and laborious manual detection.

[0061] Embodiment Two

[0062] Figure 2 As shown in the flowchart of a coal quality detection method based on target calibration provided by Embodiment Two of the present invention, on the basis of the above embodiments, the method for determining the deviation coefficient is further defined, such as Figure 2 shown, including:

[0063] Step 210: Receive the current spectral data for the target substance.

[0064] Step 220: Determine the wavelength region of the spectral peaks in the current spectral data.

[0065] Among them, the wavelength regions of the spectral peaks of different substances are different, and the same substance may also have multiple spectral peaks. Therefore, it is necessary to locate the spectral peaks in the current spectral data, determine the wavelength regions of the spectral peaks, and use them to compare with the spectral peaks in the corresponding regions of the theoretical spectral data.

[0066] Step 230: Determine the wavelength region of the theoretical spectral data as the target region, where the number of spectral peaks in the target region is the same as the number of spectral peaks in the wavelength region.

[0067] Step 240: Determine the deviation coefficient between the theoretical spectral data and the current spectral data according to the intensity and wavelength of the spectral reference line in the target region, and the intensity and wavelength of the spectral peaks in the wavelength region.

[0068] Among them, the target region is the region where the spectral peaks to be compared are located.

[0069] Specifically, due to the complexity of the detection environment, the spectral peaks in the current spectral data may be deformed, such as causing changes in wavelength and intensity. Therefore, it is necessary to determine the spectral peaks to be compared in the target region, and then determine the deviation coefficient through the spectral peaks in the current spectral data and the spectral reference lines in the theoretical spectral data.

[0070] Specifically, the target region contains spectral reference lines representing the corresponding spectral peaks. The spectral reference lines are generated according to the wavelength and intensity of the corresponding spectral peaks. Therefore, the required deviation coefficient can be determined according to the wavelength and intensity of the spectral reference lines in the theoretical spectral data, and the wavelength and intensity of the corresponding spectral peaks in the current spectral data.

[0071] Optionally, step 240 includes:

[0072] Determine the spectral peaks in the wavelength region as actual spectral peaks, and determine the wavelength and intensity of the actual spectral peaks;

[0073] Determine the intensity and wavelength of the corresponding theoretical spectral peaks according to the intensity and wavelength of the spectral reference lines;

[0074] Generate at least one theoretical spectral peak group containing two different theoretical spectral peaks according to the theoretical spectral peaks;

[0075] Generate at least one actual spectral peak group containing two different actual spectral peaks according to the actual spectral peaks;

[0076] Based on the correspondence between the theoretical spectral peaks and the actual spectral peaks, determine the group correspondence between the theoretical spectral peak group and the actual spectral peak group;

[0077] According to the wavelength and intensity of the theoretical spectral peaks, the wavelength and intensity of the actual spectral peaks, the theoretical wavelength difference of the theoretical spectral peak group, the actual wavelength difference of the actual spectral peak group, and the group correspondence, determine the deviation coefficient between the theoretical spectral data and the current spectral data.

[0078] Among them, the spectral peaks within the wavelength region are the actual spectral peaks in the current spectral data, and thus the wavelength and intensity of the actual spectral peaks can be determined. According to the spectral reference line, the wavelength and intensity of the theoretical spectral peaks in the theoretical spectral data can be determined.

[0079] Among them, the theoretical spectral peak group includes two different spectral peaks in the theoretical spectral data; the actual spectral peak group includes two different spectral peaks in the current spectral data.

[0080] Specifically, since there is a one-to-one correspondence between the spectral peaks in the current spectral data and the spectral peaks in the theoretical spectral data, there is also a one-to-one correspondence between the theoretical spectral peak group and the actual spectral peak group. Specifically, if the spectral peaks in the theoretical spectral peak group and the actual spectral peak group correspond one by one, then the theoretical spectral peak group and the actual spectral peak group are corresponding spectral peak groups.

[0081] Exemplarily, the deviation coefficient can be determined by the following formula, where the deviation coefficient includes the intensity deviation coefficient and the wavelength deviation coefficient.

[0082] Intensity deviation coefficient = Intensity at the peak of the theoretical spectral peak ÷ Intensity at the peak of the actual spectral peak

[0083] The wavelength deviation coefficient includes the intercept of the wavelength direction transformation and the wavelength direction transformation coefficient.

[0084] Intercept of the wavelength direction change = Wavelength of the highest peak of the actual spectral peak - Wavelength of the highest peak of the theoretical spectral peak.

[0085] Wavelength direction transformation coefficient = Wavelength difference between the spectral peaks in the theoretical spectral peak group - Wavelength difference between the spectral peaks in the actual spectral peak group.

[0086] It should be noted that the theoretical spectral peak and the actual spectral peak in the same formula are the corresponding spectral peaks in the theoretical spectral data and the current spectral data, and the theoretical spectral peak group and the actual spectral peak group are also corresponding spectral peak groups.

[0087] Optionally, determine the average intensity ratio according to the intensity ratio of the actual spectral peaks corresponding to each theoretical spectral peak;

[0088] If the average intensity ratio does not meet the preset threshold, re-acquire the current spectral data of the target substance.

[0089] Specifically, the intensity ratio can characterize the deviation degree between the theoretical spectral peak and the corresponding actual spectral peak, and the average intensity ratio can characterize the average deviation degree. If the average intensity ratio does not meet the preset threshold, it indicates that there may be problems in the current data acquisition process, or the current environment is harsh, seriously affecting the acquisition of spectral data. Therefore, it is necessary to re-acquire the current spectral data of the target substance.

[0090] Step 250: Receive the spectral data for coal quality, and calibrate the spectral data for coal quality according to the deviation coefficient.

[0091] Specifically, the spectral peak of coal quality can be determined based on the spectral data of coal quality, and then the intensity and wavelength of the spectral peak of coal quality can be determined.

[0092] Wavelength after calibration of spectral data for coal quality = Wavelength of spectral peak of coal quality + Wavelength direction transformation coefficient × (Wavelength of spectral peak of coal quality - Wavelength of spectral peak with the highest intensity in the current target data) - Wavelength direction transformation intercept

[0093] Intensity after calibration of spectral data for coal quality = Intensity of spectral peak of coal quality × Intensity direction transformation coefficient.

[0094] Among them, the wavelength direction transformation intercept, the wavelength direction transformation coefficient, and the intensity direction transformation coefficient can be determined according to the formula in step 240.

[0095] Step 260: Determine the coal quality components based on the calibrated spectral data for coal quality.

[0096] The embodiment of the present invention provides a coal quality detection method based on target calibration. This method can determine the deviation coefficient through the intensity and wavelength of the spectral reference lines in the theoretical spectral data and the intensity and wavelength of the spectral peaks in the current spectral data, and then use the deviation coefficient to calibrate the spectral data for coal quality. This way can improve the accuracy of the spectral data for coal quality, and further improve the accuracy of coal quality component detection.

[0097] Embodiment III

[0098] Figure 3 It is a schematic structural diagram of a coal quality detection device provided by Embodiment III of the present invention. As Figure 3 shown, the device includes:

[0099] A deviation coefficient determination module 310, configured to receive the current spectral data for the target substance, and determine the deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance. Among them, the theoretical spectral data includes multiple spectral reference lines, and the spectral reference lines are used to characterize the physical parameters of the spectral peak and provide a reference benchmark for the determination of the deviation coefficient;

[0100] A calibration module 320, configured to receive spectral data of coal quality and calibrate the spectral data of the coal quality according to the deviation coefficient;

[0101] A component determination module 330, configured to determine the coal quality components according to the calibrated spectral data of the coal quality.

[0102] The beneficial effect of the coal quality detection device based on target calibration provided by the embodiments of the present invention is that since the detection environment will affect the detection result, therefore, by determining the theoretical spectral data and the current spectral data of the target substance, the deviation coefficient characterizing the environmental impact can be determined, and then the spectral data of the coal quality can be calibrated with the deviation coefficient, which can improve the accuracy of the spectral data of the coal quality, and further improve the accuracy of the coal quality component detection. The technical solution provided by the device of the present invention can improve the accuracy of the coal quality component detection and solve the problem of time-consuming and laborious manual detection.

[0103] Optionally, the coal quality detection device based on target calibration further includes: a spectral reference line determination module, configured to obtain the theoretical spectral data of the target substance in a preset environment, determine a set number of theoretical spectral peaks according to the physical parameters of the spectral peaks in the theoretical spectral data, and determine the spectral reference line according to the theoretical spectral peaks.

[0104] Further, the spectral reference line determination module specifically includes:

[0105] An acquisition unit, configured to acquire the theoretical spectral diagram of the target substance in a preset environment, where the number of spectral peaks in different optical bands of the theoretical spectral diagram exceeds a set number threshold;

[0106] A determination unit, configured to determine a set number of theoretical spectral peaks according to the intensity of the spectral peaks in any optical band of the theoretical spectral diagram;

[0107] A spectral reference line determination unit, configured to determine the spectral reference line according to the intensity and wavelength of the theoretical spectral peaks.

[0108] Optionally, the deviation coefficient determination module 310 includes:

[0109] A wavelength region determination unit, configured to determine the wavelength region of the spectral peaks in the current spectral data;

[0110] A target region determination unit, configured to determine the wavelength region of the theoretical spectral data as the target region, where the number of spectral peaks in the target region is the same as the number of spectral peaks in the wavelength region;

[0111] A deviation coefficient determination unit, configured to determine the deviation coefficient between the theoretical spectral data and the current spectral data according to the intensity and wavelength of the spectral reference line in the target region and the intensity and wavelength of the spectral peaks in the wavelength region.

[0112] The deviation coefficient determination unit includes:

[0113] A first determination subunit, configured to determine a spectral peak within a wavelength region as an actual spectral peak, and determine the wavelength and intensity of the actual spectral peak;

[0114] A second determination subunit, configured to determine the intensity and wavelength of a corresponding theoretical spectral peak according to the intensity and wavelength of a spectral reference line;

[0115] A theoretical spectral peak group subunit, configured to generate at least one theoretical spectral peak group including two different theoretical spectral peaks according to the theoretical spectral peaks;

[0116] An actual spectral peak group subunit, configured to generate at least one actual spectral peak group including two different actual spectral peaks according to the actual spectral peaks;

[0117] A group correspondence determination subunit, configured to determine the group correspondence between the theoretical spectral peak group and the actual spectral peak group based on the correspondence between the theoretical spectral peak and the actual spectral peak;

[0118] A deviation coefficient determination subunit, configured to determine the deviation coefficient between the theoretical spectral data and the current spectral data according to the wavelength and intensity of the theoretical spectral peak, the wavelength and intensity of the actual spectral peak, the theoretical wavelength difference of the theoretical spectral peak group, the actual wavelength difference of the actual spectral peak group, and the group correspondence.

[0119] Optionally, the deviation coefficient determination unit further includes:

[0120] An inspection unit, configured to determine an average intensity ratio according to the intensity ratio of the actual spectral peaks corresponding to each theoretical spectral peak; if the average intensity ratio does not meet a preset threshold, re-acquire the current spectral data of the target substance.

[0121] Optionally, the calibration module 320 includes:

[0122] A spectral peak determination unit, configured to determine the spectral peaks of coal quality components according to the spectral data of coal quality;

[0123] A wavelength calibration unit, configured to calibrate the wavelength of the spectral peaks of the coal quality components according to the wavelength deviation coefficient;

[0124] An intensity calibration unit, configured to calibrate the intensity of the spectral peaks of the coal quality components according to the intensity deviation coefficient.

[0125] Optionally, the component determination module 330 includes:

[0126] An acquisition unit, configured to acquire a base model, where the base model includes wavelength data and intensity data of each coal quality component that may exist in the coal quality;

[0127] A detection unit, configured to determine, based on a base model and according to the wavelength and intensity of a calibrated spectral peak, the coal quality components actually present in the coal quality characterized by spectral data.

[0128] The coal quality detection device based on target calibration provided by the embodiments of the present invention can execute the coal quality detection method based on target calibration provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0129] Embodiment 4

[0130] Figure 4 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, personal digital processors, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0131] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0132] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0133] The processor 11 may be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the coal quality detection method based on target calibration.

[0134] In some embodiments, the coal quality detection method based on target calibration can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the coal quality detection method based on target calibration described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the coal quality detection method based on target calibration by any other suitable means (e.g., by means of firmware).

[0135] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0136] The computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0137] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0138] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0139] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0140] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0141] It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and no limitations are imposed herein.

[0142] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A coal quality detection method based on target calibration, characterized in that: include: Receiving current spectral data for a target substance, and determining a deviation coefficient of the theoretical spectral data and the current spectral data according to theoretical spectral data of the target substance and the current spectral data, wherein the theoretical spectral data includes a plurality of spectral reference lines, and the spectral reference lines are used to characterize physical parameters of spectral peaks and provide a reference benchmark for determining the deviation coefficient; receiving spectral data for coal quality, and calibrating the spectral data for the coal quality according to the deviation coefficient; Determine the coal composition based on the calibrated coal spectrum data; The method for determining the spectrum reference line of the theoretical spectrum data includes: Acquire theoretical spectrum data of the target substance under a preset environment, determine a set number of theoretical spectrum peaks according to physical parameters of the spectrum peaks in the theoretical spectrum data, and determine spectrum reference lines according to the theoretical spectrum peaks; The step of determining the deviation coefficient of the theoretical spectral data and the current spectral data according to the theoretical spectral data and the current spectral data of the target substance comprises: Determine the wavelength region of the spectrum peak in the current spectrum data; Determining a wavelength region of the theoretical spectrum data as a target region, wherein the number of spectrum peaks in the target region is the same as the number of spectrum peaks in the wavelength region; The deviation coefficient of the theoretical spectral data and the current spectral data is determined according to the intensity and wavelength of the spectral reference line of the target area and the intensity and wavelength of the spectral peak in the wavelength area.

2. The method according to claim 1, characterized in that The step of acquiring theoretical spectral data of a target substance under a preset environment, determining a set number of theoretical spectral peaks according to physical parameters of the spectral peaks in the theoretical spectral data, and determining spectral reference lines according to the theoretical spectral peaks includes: Acquiring a theoretical spectrum of the target substance under a preset environment, wherein the number of spectrum peaks in different light bands of the theoretical spectrum exceeds a set number threshold; For any light band in the theoretical spectrum diagram, determining a set number of theoretical spectrum peaks according to the intensity of the spectrum peaks of the light band; The spectrum reference line is determined according to the intensity and wavelength of the theoretical spectrum peak.

3. The method according to claim 1, characterized in that Determining the deviation coefficient of the theoretical spectrum data and the current spectrum data according to the intensity and wavelength of the spectrum reference line of the target area and the intensity and wavelength of the spectrum peak in the wavelength area includes: Determine a spectral peak in the wavelength region as an actual spectral peak, and determine the wavelength and intensity of the actual spectral peak; Determine the intensity and wavelength of the corresponding theoretical spectrum peak according to the intensity and wavelength of the spectrum reference line; generating at least one theoretical spectrum peak group including two different theoretical spectrum peaks according to the theoretical spectrum peaks; generating at least one actual spectrum peak group including two different actual spectrum peaks according to the actual spectrum peaks; Based on the correspondence between the theoretical spectrum peaks and the actual spectrum peaks, determining a group correspondence between the theoretical spectrum peak group and the actual spectrum peak group; The deviation coefficient of the theoretical spectral data and the current spectral data is determined based on the wavelength and intensity of the theoretical spectral peak, the wavelength and intensity of the actual spectral peak, the theoretical wavelength difference of the theoretical spectral peak group, the actual wavelength difference of the actual spectral peak group and the group correspondence.

4. The method according to claim 3, characterized in that Also includes: Determine the average intensity ratio according to the intensity ratio of the actual spectrum peaks corresponding to each theoretical spectrum peak; If the average intensity ratio does not meet the preset threshold, the current spectrum data of the target material is reacquired.

5. The method according to claim 1, characterized in that: The deviation coefficient includes a wavelength deviation coefficient and an intensity deviation coefficient. The receiving spectral data for coal quality and calibrating the spectral data for coal quality according to the deviation coefficient include: Determine the spectral peaks of coal components based on the spectral data of coal quality; Calibrate the wavelength of the spectral peak of the coal quality component according to the wavelength deviation coefficient; The intensity of the spectral peak of the coal quality component is calibrated according to the intensity deviation coefficient.

6. The method according to claim 5, characterized in that The method of determining the coal quality composition according to the calibrated coal quality spectral data comprises: Acquire a base model, wherein the base model includes wavelength data and intensity data of each coal component that may exist in the coal; Based on the basis model, the actual coal components in the coal quality represented by the spectral data are determined according to the wavelength and intensity of the calibrated spectral peak.

7. A coal quality detection device based on target calibration, characterized in that: include: A deviation coefficient determination module, used for receiving current spectral data for a target substance, and determining a deviation coefficient between the theoretical spectral data and the current spectral data according to the theoretical spectral data of the target substance and the current spectral data, wherein the theoretical spectral data includes a plurality of spectral reference lines, and the spectral reference lines are used for characterizing the physical parameters of the spectral peaks and providing a reference benchmark for determining the deviation coefficient; A calibration module, used for receiving spectral data of coal quality and calibrating the spectral data of coal quality according to the deviation coefficient; A component determination module, used for determining the coal quality components according to the calibrated spectral data of the coal quality; The device further comprises: a spectrum reference line determination module, which is used to obtain theoretical spectrum data of the target substance under a preset environment, determine a set number of theoretical spectrum peaks according to physical parameters of the spectrum peaks in the theoretical spectrum data, and determine a spectrum reference line according to the theoretical spectrum peaks; The deviation coefficient determination module comprises: A wavelength region determination unit, used to determine the wavelength region of the spectrum peak in the current spectrum data; a target region determining unit, configured to determine a wavelength region of the theoretical spectrum data as a target region, wherein the number of spectrum peaks in the target region is the same as the number of spectrum peaks in the wavelength region; The deviation coefficient determination unit is used to determine the deviation coefficients of theoretical spectrum data and current spectrum data according to the intensity and wavelength of the spectrum reference line of the target area and the intensity and wavelength of the spectrum peak in the wavelength area.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the coal quality detection method based on target calibration described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the coal quality detection method based on target calibration as described in any one of claims 1 to 6 when executed.

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