Coal quality analysis method based on LIBS technology

Abstract

The application provides a coal quality analysis method based on LIBS technology, which comprises the following steps: a laser output by a laser is split into a first light beam and a second light beam; the first light beam is incident on coal powder, a photodetector array receives a scattered light signal and sends the signal to an analysis unit, and the analysis unit outputs a particle size distribution of the coal powder; the second light beam is incident on the coal powder to generate a plasma signal, and the signal is sent to a spectrometer to obtain a spectrum of the coal powder; and the analysis unit processes the spectrum and the particle size distribution by using an analysis model to obtain parameters of the coal powder, wherein the parameters include a calorific value. The application has the advantages of accurate analysis.

Description

Technical Field

[0001] This invention relates to LIBS technology, and particularly to a coal quality analysis method based on LIBS technology. Background Technology

[0002] Currently, in thermal power plants, the testing of indicators such as calorific value in coal used for power generation mostly involves on-site sampling followed by chemical analysis in a laboratory. This method is time-consuming in the sampling and testing process, which is not conducive to online monitoring of coal combustion. Among online coal quality analysis instruments, the neutron activation method has high measurement accuracy, but its high cost, difficult maintenance, and radiation exposure limit its development.

[0003] Laser-induced breakdown spectroscopy (LIBS) is an emerging rapid analytical technique whose advantages, such as no sample preparation required, fast analysis, and remote sensing capabilities, have led to its rapid development in online analysis technologies. Real-time detection of elements in coal using LIBS allows for rapid calculation of indicators such as calorific value, providing real-time guidance for online combustion in power plants. Besides analyzing indicators like calorific value, the particle size of burning coal is also a crucial factor affecting its complete combustion. Existing instruments for measuring coal particle size include laser particle size analyzers, but most are offline instruments. Real-time detection and analysis of coal particle size also helps power plants guide the ratio of coal to oxygen and water supply. Some online particle size analyses primarily employ image processing methods, but real-time operating conditions significantly impact image processing of coal combustion. Furthermore, considering that the particle size of the analyte is also a significant factor affecting the intensity and stability of the LIBS signal, this analysis is crucial for accurate and reliable analysis.

[0004] Therefore, it is necessary to develop a new type of coal quality analyzer that can not only detect the particle size of coal in real time, but also measure combustion indicators such as calorific value, so that power plants can grasp the real-time coal combustion situation and make real-time online adjustments to the combustion situation. Summary of the Invention

[0005] To address the shortcomings of the existing technical solutions, this invention provides a coal quality analysis method based on LIBS technology.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A coal quality analysis method based on LIBS technology, wherein the LIBS-based coal quality analysis method is as follows:

[0008] The laser output from the laser is split into a first beam and a second beam.

[0009] The first beam is incident on the coal powder, the photodetector array receives the scattered light signal and sends it to the analysis unit, and the analysis unit outputs the particle size distribution of the coal powder;

[0010] The second beam is incident on the pulverized coal, generating a plasma signal. This signal is sent to a spectrometer to obtain the spectral map of the pulverized coal. The analysis unit uses an analysis model to process the spectral map and particle size distribution to obtain the parameters of the pulverized coal, including the calorific value.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0012] 1. By simultaneously measuring the scattered light and laser-induced spectrum of pulverized coal, information on the particle size distribution and calorific value of pulverized coal can be obtained;

[0013] 2. The measured coal powder particle size distribution information has a certain impact on the laser-induced breakdown spectrum. Using this information as a correction term for modeling information such as calorific value results in more accurate and stable results.

[0014] 3. Coal samples of different particle sizes can be classified by particle size distribution information. This classification can be performed before quantitative analysis of information such as calorific value, making the measurement results more accurate. Attached Figure Description

[0015] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention. In the drawings:

[0016] Figure 1 This is a schematic flowchart of a coal quality analysis method based on LIBS technology according to an embodiment of the present invention. Detailed Implementation

[0017] Figure 1 The following description illustrates optional embodiments of the invention to teach those skilled in the art how to implement and reproduce the invention. Some conventional aspects have been simplified or omitted to explain the technical solutions of the invention. Those skilled in the art should understand that variations or substitutions derived from these embodiments will be within the scope of the invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the invention. Therefore, the invention is not limited to the following optional embodiments, but is defined only by the claims and their equivalents.

[0018] Example 1:

[0019] Figure 1 A flowchart illustrating the coal quality analysis method based on LIBS technology according to an embodiment of the present invention is shown, such as... Figure 1 As shown, the coal quality analysis method based on LIBS technology is as follows:

[0020] The laser output from the laser is split into a first beam and a second beam.

[0021] The first beam is incident on the coal powder, the photodetector array receives the scattered light signal and sends it to the analysis unit, and the analysis unit outputs the particle size distribution of the coal powder;

[0022] The second beam is incident on the pulverized coal, generating a plasma signal. This signal is sent to a spectrometer to obtain the spectral map of the pulverized coal. The analysis unit uses an analysis model to process the spectral map and particle size distribution to obtain the parameters of the pulverized coal, including the calorific value.

[0023] To obtain an accurate coal powder particle size distribution, the first beam is further expanded and then incident on the coal powder.

[0024] To obtain an accurate coal powder particle size distribution, the particle size distribution is further obtained as follows:

[0025] The particle size distribution of coal powder is obtained by using the correspondence between the particle size and the location of the maximum intensity of the scattered light output by the photodetector array.

[0026] To obtain accurate indicators such as the calorific value of pulverized coal, the analytical model is further established as follows:

[0027] Classify coal samples;

[0028] The spectrum of the coal sample is obtained, and the spectral lines of C, H and inorganic ash-forming elements in the coal sample are collected. These spectral lines are used as input variables of the model to establish a model between the spectral lines and the calorific value, and the coefficient matrix and error term of the model are obtained.

[0029] The coal sample particle size is used as a separate feature to calibrate the measurement error generated by the model, and a functional relationship is established between the modeling error of the coal sample and the size of the corresponding coal powder particles.

[0030] To establish an accurate analytical model, the classification method is further as follows:

[0031] Coal samples of different sizes were measured to obtain different coal sample particle size data. Particle size histograms were plotted and classified according to the partial probability of particle size.

[0032] Example 2:

[0033] An application example of the coal quality analysis method based on LIBS technology according to Embodiment 1 of the present invention.

[0034] In this application example, such as Figure 1 As shown, the coal quality analysis method based on LIBS technology is as follows:

[0035] Establish an analytical model.

[0036] After the laser output from the laser is split, it forms a first reflected beam and a second transmitted beam. The intensity of the first beam accounts for 1% and the intensity of the second beam accounts for 99%.

[0037] The first beam is incident on the coal powder, and the photodetector array receives the scattered light signal. A functional relationship is established between the particle size and the position of the strongest light intensity received by the photodetector array. The particle size of the coal powder is used as the abscissa, and the position of the strongest light intensity of the scattered light detected by the photodetector is used as the ordinate to establish a calibration curve for particle size analysis and store it.

[0038] Coal samples of different sizes were measured to obtain different coal sample particle size data. Particle size histograms were plotted and classified according to the partial probability of particle size.

[0039] The spectrum of the coal sample is obtained, and the spectral lines of C, H and inorganic ash-forming elements (Si, Fe, Al, Ca and Mg) in the coal sample are collected. These spectral lines are used as input variables of the model to establish a model between the spectral lines and the calorific value, and the coefficient matrix and error term of the model are obtained.

[0040] The coal sample particle size is used as a separate feature to calibrate the measurement error generated by the model, and a linear function relationship is established between the modeling error of the coal sample and the size of the corresponding coal powder particles.

[0041] Formal analysis;

[0042] After the laser output from the laser is split, it forms a first reflected beam and a second transmitted beam. The intensity of the first beam accounts for 1% and the intensity of the second beam accounts for 99%.

[0043] After the first beam is expanded, it is incident on the coal powder located upstream. The photodetector array receives the scattered light signal and sends it to the analysis unit. The analysis unit uses the calibration curve to output the particle size distribution of the coal powder.

[0044] The second beam is focused onto the downstream coal powder, generating a plasma signal. This signal is sent to a spectrometer to obtain the spectrum of the coal powder. The analysis unit processes the spectrum using an analysis model to obtain the parameters of the coal powder, including the calorific value.

[0045] Substituting the calorific value into the linear function relationship, we obtain the corrected parameters such as the calorific value of pulverized coal.

Claims

1. A coal quality analysis method based on LIBS technology, characterized in that, The coal quality analysis method based on LIBS technology is as follows: The laser output from the laser is split into a first beam and a second beam. The first beam is incident on the coal powder, the photodetector array receives the scattered light signal and sends it to the analysis unit, and the analysis unit outputs the particle size distribution of the coal powder; The second beam is incident on the coal powder, generating a plasma signal. This signal is sent to a spectrometer to obtain the spectral map of the coal powder. The analysis unit uses an analysis model to process the spectral map and particle size distribution to obtain the parameters of the coal powder, including the calorific value. The particle size distribution is obtained as follows: The particle size distribution of coal powder is obtained by using the correspondence between particle size and the location of the maximum intensity of scattered light output by the photodetector array. The analytical model is established as follows: Classify coal samples; The spectrum of the coal sample is obtained, and the spectral lines of C, H and inorganic ash-forming elements in the coal sample are collected. These spectral lines are used as input variables of the model to establish a model between the spectral lines and the calorific value, and the coefficient matrix and error term of the model are obtained. The coal sample particle size is used as a separate feature to calibrate the measurement error generated by the model, and a functional relationship is established between the modeling error of the coal sample and the size of the corresponding coal powder particles.

2. The coal quality analysis method based on LIBS technology according to claim 1, characterized in that, The first beam is expanded and then incident on the coal powder.

3. The coal quality analysis method based on LIBS technology according to claim 1, characterized in that, The inorganic ash-forming elements are Si, Fe, Al, Ca, or Mg.

4. The coal quality analysis method based on LIBS technology according to claim 1, characterized in that, The classification method is as follows: Coal samples of different sizes were measured to obtain different coal sample particle size data. Particle size histograms were plotted and classified according to the partial probability of particle size.

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