Study On The Safety Information Of Long Wall Coal Face

In order to curb the trend of frequent occurrence of coal spontaneous combustion and gas explosion, a research project named "Study on the Safety Information System of Long Wall Coal Face" offered by Chenjiashan Coal Mine has been conducted and the daily monitoring data of the 416 Long Wall Face in the mine has been tracked with a software platform composed of data collection, visualization, integrated analysis and decision making being proposed and developed. A new method of mathematical analysis of Support Vector Machine (SVM) is adopted on the basis of Safety Information System to predict coal spontaneous combustion in the gob, which leads to a comprehensive model of coal mine safety data information management as well as decision-making analysis, and has been applied to the management of safe production in coal mines.The practical impact and feasible way of data visualization for the 416 Long Wall Face is analyzed. The data structure to support large amount of data and frequent data exchange suitable for the safety management of coal mines has been put forward, which significantly facilitates the application of the safety information system.A prediction method of gob coal spontaneous combustion based on SVM analysis is studied. Data from the 8914 Long Wall Face of Xinzhou Coal Mine is taken as an example in which the risk of coal spontaneous combustion is identified and quantitatively determined through the usage of SVM method so as to show the feasibility of SVM method and to further explore functions of information management platform.The author has been trying to build a feasible structure of Computer-Aided Expert System for the decision-making of safety management in coal working faces supported by the general computer technology, artificial intelligence, and safety theory. It is hoped that the research achievements of the thesis will help promoting the appearance of a safer mining environment.