Coal quality characteristic analysis method based on combination of dominant factors and partial least square method

A partial least squares method and partial least squares technology, applied in the direction of material excitation analysis, etc., can solve the problem that the partial least squares method does not consider physical laws and nonlinear effects, and achieve the effect of easy implementation and improved measurement accuracy

Active Publication Date: 2013-08-07
TSINGHUA UNIV
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Problems solved by technology

[0005] Aiming at the disadvantage that the partial least square method does not consider the physical law and nonlinear influence, the present invention provides a coal quality detection method based on the domina

Method used

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  • Coal quality characteristic analysis method based on combination of dominant factors and partial least square method
  • Coal quality characteristic analysis method based on combination of dominant factors and partial least square method
  • Coal quality characteristic analysis method based on combination of dominant factors and partial least square method

Examples

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Embodiment

[0072] Example: Coal quality characteristics analysis is performed on a group of coal samples in a power plant.

[0073] 1) In this example, 40 kinds of coal samples are used as calibration samples. The results obtained through traditional off-line analysis of the coal quality characteristics of the calibration samples are shown in Table 1: due to the large number of samples, the standard values ​​of some samples are omitted.

[0074] Table 1 Standard values ​​of coal quality characteristics

[0075]

[0076]

[0077] Put 40 kinds of coal samples on the coal conveyor belt one by one, 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 as the excitation light source, the laser emitted from the laser is focused by the focusing lens 2 and then acts on the surface of the coal sample 3, generating plasma at the focal point, and the plasma is cooled in ...

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Abstract

The invention discloses a coal quality characteristic analysis method based on combination of dominant factors and a partial least square method, and belongs to the technical field of atomic emission spectroscopy. According to the method, modeling is carried out based on a physical background of coal quality characteristics. The method comprises two steps of partial least square fitting processes. In the first partial least square fitting process, characteristic lines in a spectrum relative to coal quality characteristics are used as inputs, and a nonlinear dominant factor model is established for describing a physical relationship between coal quality characteristics and laser-induced breakdown spectroscopy. In the second partial least square fitting process, dominant factor residuals are corrected by using all spectral line intensity information of the spectrum. Compared with a traditional partial least square model, with the method provided by the invention, model calibration and prediction precisions are improved.

Description

technical field [0001] The invention relates to an on-line detection method for coal based on a dominant factor combined with a partial least square method using laser-induced plasma spectroscopy (LIBS). Background technique [0002] In coal mines, coal plants, power plants and other coal-consuming units, the coal quality detection methods commonly used are off-line sampling and laboratory analysis. This method has complex procedures, long time consumption, poor sampling representativeness, and it is difficult to feedback various components of coal in time. However, coal users need to control the coal composition on the belt conveyor in time to guide production and control. So the traditional off-line measurement is difficult to adapt to the needs of industrial production. If it is possible to analyze the composition of coal on the conveyor belt in real time and online, it will be of great significance to coal consumers. [0003] At present, the technologies used in onlin...

Claims

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Application Information

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IPC IPC(8): G01N21/63
Inventor 王哲袁廷璧李政
Owner TSINGHUA UNIV
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