Nonlinear identification method for mine water inrush source

Abstract

The invention relates to a nonlinear identification method for a mine water inrush source. The method comprises the following steps of (1) collecting spectrum data; (2) preprocessing the collected original spectrum data by utilizing a Savitzky-Golay (SG) smoothing technology; (3) performing data dimension reduction by utilizing a nonlinear kernel principal component analysis method, and performing nonlinear feature extraction; (4) establishing independent test set and training set by collected water samples; and (5) establishing an ELM by utilizing the training set, and then performing classification result testing through the test set. According to the method, the feature extraction is performed in a nonlinear way, so that the time and space complexity is lowered and the sample identification performance is provided; the kernel principal component analysis optimizes learning parameters of the ELM; an ELM classification model has the characteristics of few training parameters, high learning speed and the like; the KPCA and the ELM are combined for nonlinear identification of the mine water inrush source; and the method is very suitable for online water inrush source monitoring.

Description

technical field [0001] The invention is a nonlinear identification method for mine water inrush sources, and in particular relates to a nonlinear method for identifying mine water inrush sources based on KPCA-EML laser-induced fluorescence spectroscopy (LIF). Background technique [0002] Coal mine water inrush has caused serious harm to coal mine production, and it is necessary to quickly and accurately identify the source of water inrush when preventing and controlling water inrush. The main types of mine water inrush water sources are: Austrian ash water, old kiln water, alluvium water, sandstone water, and limestone water. At present, conventional methods for identifying water inrush sources in coal mines are mostly based on water chemistry, but the identification time is long and the efficiency is relatively low, and it is difficult to adapt to real-time monitoring of water inrush in coal mines. The laser-induced fluorescence spectroscopy (LIF) technology is used to ob...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is mainly to provide a non-linear identification method for mine water inrush sources. In order to solve the problem of feature extraction of nonlinear data and the problem of accurate and fast learning classification, a mine water inrush based on KPCA-EML laser-induced fluorescence spectroscopy technology is proposed. Nonlinear Discrimination Method of Water Source

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