Coal quality on-line detecting analytical method based on regression analysis

A regression analysis and analysis method technology, applied in material excitation analysis, fluorescence/phosphorescence, etc., can solve problems such as insufficient precision, large investment, and inability to achieve full element analysis.

CN101509872AActive Publication Date: 2009-08-19TSINGHUA UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2009-08-19

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Abstract

The invention discloses an online coal property detecting and analyzing method, which is based on regression analysis, utilizes a spectral line intensity group of calibration coal samples and builds the following two calibration curves of all elements through the least square method: C equals to aI plus e, and C equals to AI plus summation of *BC plus Dg(C) plus E. In the detection of samples of unknown coal flows to be detected, first-time computed mass concentration of each element is computed by characteristic spectral line intensity of laser-induced plasma of each element, and the mass concentration of an element to be detected is calculated according to the calibration curves; alternatively, calibration of carbon element is implemented for two times, second-time computed mass concentration of each element is calculated, and then the mass concentration of the element to be detected is calculated according to the calibration curves. The online coal property detecting and analyzing method utilizes all the information of LIBS spectrum, avoids errors caused by complex calibrating methods, reduces the influence of maternal effect, has quick calibrating speed and high precision, can realize online coal full-element analysis, and can provide the real-time data of coal elements for users.
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Description

technical field

[0001] The invention relates to an online detection and analysis method for coal. Specifically, the basic principle of the method is laser-induced plasma spectroscopy (LIBS), which is based on the least squares method in regression analysis for quantitative analysis of coal elements. Background technique

[0002] In coal mines, coal plants and power plants and other coal-consuming units, it is necessary to control the various components of the coal on the belt conveyor in time according to the needs, so as to adjust and control in a timely manner, which requires real-time online analysis of the coal on the conveyor belt. Most of the commonly used methods are offline analysis. This method has disadvantages such as poor sampling and sample preparation, slow analysis speed, and cumbersome procedures. It cannot provide timely feedback of coal information and cannot provide real-time online reference data for operators. It is difficult to meet the needs of indust...

Examples

Embodiment 1

[0076] A method for online detection and analysis of coal quality based on regression analysis, characterized in that

[0077] 1) First, a group of anthracite coal samples with known mass concentrations of each element are used for calibration. The mass concentrations of the main elements of the coal samples are sample 1 containing 92.27% of C, 1.14% of H, 4.72% of O, and 0.88% of N. S 0.54%; Sample 2 contains C 95.76%, H 1.16%, O 2.37%, N 0.88%, S 0.32%; Sample 3 contains C 94.90%, H 1.18%, O 2.55%, N 0.72%, S 0.65% ;Sample 4: C 91.59%, H 4.04%, O 2.59%, N 1.46%, S 0.32%, because the mass concentration of trace elements is very small, for the convenience of explanation, the influence of trace elements on the signals of the measured elements is not considered here , of course, trace elements can also be considered according to actual measurement needs. Put five kinds of coal samples on the coal conveyor belt in turn, and use the laser-induced plasma spectroscopy system instal...

Embodiment 2

[0099] 1) First, a group of anthracite coal samples with known mass concentrations of each element are used for calibration. The mass concentrations of the main elements of the coal samples are sample 1 containing 92.27% of C, 1.14% of H, 4.72% of O, and 0.88% of N. S 0.54%; Sample 2 contains C 95.76%, H 1.16%, O 2.37%, N 0.88%, S 0.32%; Sample 3 contains C 94.90%, H 1.18%, O 2.55%, N 0.72%, S 0.65% ;Sample 4: C 91.59%, H 4.04%, O 2.59%, N 1.46%, S 0.32%, because the mass concentration of trace elements is very small, for the convenience of explanation, the influence of trace elements on the signals of the measured elements is not considered here , of course, trace elements can also be considered according to actual measurement needs. Put five kinds of coal samples on the coal conveyor belt in turn, and use the laser-induced plasma spectroscopy system installed on the coal conveyor belt to detect the coal samples online, such as figure 1 As shown: the pulsed laser 1 is used a...