Coal mine gas prediction method

Abstract

The invention discloses a coal mine gas prediction method. The KPCA algorithm is used for identifying a large number. Firstly, two hybrid kernel functions are constructed, a kernel matrix is constructed through a vector method, and a feature vector of the kernel matrix is calculated through kernel principal component analysis, wherein the algorithm is high in recognition rate and calculation speed; according to the algorithm, by means of a group of standard orthonormal bases of a subspace spanned by training samples in a feature space, the KPCA process on a training set is converted into the PCA process in which coordinates of all the kernel training samples under the group of bases are datasets, meanwhile, feature extraction is conducted on the training samples so that nonlinear features of training data can be effectively captured and widely paid attention to and applied in mode recognition and regression analysis. In the KPCA solving process, feature values need to decompose the M*M kernel matrix (M refers to the number of the training samples), when feature extraction is conducted on one sample, people only need to calculate the sample and the kernel functions between the samples forming the group of bases, and experiment results verify that the algorithm is effective.

Description

technical field [0001] The invention relates to a detection method, in particular to a coal mine gas detection method. Background technique [0002] With the rapid development of my country's economy, the demand for energy is increasing day by day. Since our country is a country rich in coal, poor in oil and little in gas, the mining of coal mines plays an extremely important role in the development of our country's economy. The rapid development of the economy naturally requires more coal mining. Coal mines are enterprises with frequent accidents. [0003] It can be seen from the recent coal mine accidents in our country that gas accidents occupy a large proportion, and gas is one of the important factors that endanger mine safety production. The detection of gas concentration is the main link of coal mine safety production. The accurate measurement and forecast of gas concentration (mainly methane) is directly related to the safety of underground personnel and equipment...

AI Technical Summary

Problems solved by technology

Due to the backward technology of the alarm system, false alarms are as high as 80 to 90%. Normal production is greatly affected by frequent false alarms, causing great losses to the enterprise.

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