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Coal-mine gas concentration measurement method

A concentration measurement, coal mine gas technology, applied in the field of detection, can solve the problems of enterprise loss, backward alarm system technology, influence and other problems, and achieve the effect of ensuring leakage prevention and alarm

Inactive Publication Date: 2016-11-09
丁旭秋
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  • Abstract
  • Description
  • Claims
  • Application Information

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.

Method used

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Embodiment Construction

[0051] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and understandable, the specific implementation modes of the present invention will be described in detail below in conjunction with the accompanying drawings, so that the above-mentioned and other purposes, features and advantages of the present invention will be clearer. Like reference numerals designate like parts throughout the drawings. The drawings have not been drawn to scale, emphasis instead being placed upon illustrating the gist of the invention.

[0052] see figure 1 , first introduce the gas concentration measurement system, including the transparent gas pump 3 and the flexible grating 9 that are installed in the mine and can be driven by light; The light is irradiated to the transparent air pump 3 and the flexible grating 9 through the optical cable, the light source generating unit interacts with the signal acquisition and processing unit, and the...

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Abstract

The invention discloses a coal-mine gas concentration measurement method. ''A great number'' is identified by adopting a KPCA (Kernel Principal Components Analysis) algorithm; two mixed kernel functions are constructed firstly; a kernel matrix is constructed by utilizing a vector method; and an eigenvector of the kernel matrix is calculated by utilizing KPCA. The algorithm has relatively high identification rate and relatively high calculation speed. According to the algorithm, a KPCA process on a training set is converted into a PCA process in which coordinates of all kernel training samples under a group of standard orthogonal bases are data sets through the group of the standard orthogonal bases of subspaces formed by the training samples in a characteristic space, and characteristics of the training samples are extracted, so that nonlinear characteristics of training data can be effectively captured; and therefore, the algorithm is widely interested and applied in mode identification and regressive analysis. In a solving process of the KPCA, an eigenvalue is required for decomposing an M*M kernel matrix (M represents the number of training samples), and only a kernel function between the samples and a group of formed Kidd samples needs to be calculated during sample characteristic extraction, and an experimental result verifies that the algorithm is valid.

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. In recent years, serious and extraordinarily serious safety accidents in my country's coal mines have occurred frequently, and the annual death toll has reached 6,000, which not only caused heavy losses to the life and property of the country and the people, but also caused a bad impact on the image of the Chinese government at home and abroad. [0003] It can be seen from the recent coal mine accidents in our country that gas ...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2163G06F18/2155
Inventor 丁旭秋
Owner 丁旭秋
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