Dense medium suspension liquid coal slurry content determination method by using principal component analysis and support vector machine

Abstract

The invention relates to a dense medium suspension liquid coal slurry content determination method by using principal component analysis and a support vector machine, which belongs to coal slurry content industrial detection methods. The method is characterized in that a plurality of principal components are constructed by utilizing the principal component analysis method, so as to facilitate the dimensionality reduction treatment of high-dimensional pressure difference data in the static settling process of dense medium suspension liquid, and a training sample is formed after extracting the principal components; an epsilon type support vector regression machine is further used for establishing a coal slurry content measurement module, and the basic genetic algorithm is used for realizing the selection of optimal parameters of the support vector machine during the modeling process. The error of the coal slurry content measured by the method is +/-4%.

Description

technical field [0001] The invention belongs to the technical field of industrial automatic detection, and relates to a method for measuring the content of dense medium suspension coal slime using principal component analysis and support vector machines. Background technique [0002] Dense medium coal preparation is a coal preparation method that uses a liquid with a density between coal and gangue as a separation medium. Clean coal with a density lower than the medium floats, and gangue (or medium coal) with a density higher than the medium sinks, and then Products classified into different categories are collected separately. At present, the dense medium suspension prepared by magnetic powder and water is generally used as the separation medium for coal preparation at home and abroad. [0003] In the process of dense medium coal preparation, density and viscosity are two key parameters of dense medium suspension. In the industrial field, the density is generally controll...

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Problems solved by technology

[0016] The technical effect of the present invention is that the method provides a feature extraction method based on principal component analysis, which realizes the dimensionality reduction of the pressure difference data; adopts the basic genetic algorithm to realize the selection of the optimal parameters of the support vector machine, and solves the problem of support Difficult selection of parameters in the application of vector machines; established a slime content measurement model based on ε-SVR (ε-type support vector regression machine, where ε is the regression accuracy parameter), so that the dense medium suspension can be measured by the differential pressure measurement device Therefore, this method provides a reliable foundation and basis for "integrated measurement of density and slime content through a differential pressure measuring device"

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