Gas detection method based on KPCA (Kernel Principal Component Analysis)

Abstract

The invention discloses a gas concentration detection method, which is characterized by adopting a KPCA (Kernel Principal Component Analysis) algorithm for identifying a large number, firstly building two mixed kernel functions, utilizing a vector method for building a kernel matrix, and utilizing kernel principle component analysis for calculating characteristic vectors of the kernel matrix, wherein the algorithm has higher recognition rate and higher arithmetic speed. The algorithm converts a KPCA process on a training set into a PCA process on a data set of coordinates of all kernel training samples under a group of basis through a group of standard orthogonal basis of a subspace expanded by the training samples in a characteristic space, meanwhile, carries out characteristic extraction on the training samples so as to effectively capture nonlinear characteristics of training data, and is widely interested and applied in mode recognition and regression analysis. During a solving process of KPCA, an M*M kernel matrix (M represents the number of the training samples) needs to be subjected to eigenvalue decomposition, so that when sample characteristics are extracted, only a sample and a kernel function for forming the group of Kidd samples need to be calculated, and an experimental result verifies that the algorithm is effective.

Description

technical field [0001] The invention relates to a detection method, in particular to a KPCA-based 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] 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. At present, some coal mines in my country have installed gas detection and alarm systems. The current ...

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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