| 英文摘要 | The safety in production of coal mine is an issue long plagued china’s coal industry. Related technology research for the monitoring and predicting of coal mine safety and the path of Urgent Danger are focus of techniques in the coal industry in recent years. However, due to the complex of major accidents which is induced by many factors in coal mine, that increases the difficulty of the major hazard detection, identification, forecasting and predicting. The systems of Monitoring and Predicting of fire, gas, coal mine roof and other major hazard are not united in the same geographical space regardless of database storage, or data processing platform, so they can not share the same space dynamically changing information such as roadway, resulting in difficulties in sharing data, serious silos of data and complex operation of system. They seriously hindered the progress of coal mine safety management of high-tech. In this paper, we designed the system of monitoring and predicting of coal mine safety based on the original subsystem, made it the ability to complete the integration of monitoring and information and build a fire, gas, warning indicator system to predict and analyze the roof warning and disposal processes. While, we analyzed in detail the reasons for major hazard of gas produced, distribution and disposal processes of warning. By studying and comparing the methods of gas warning prediction, including the general warning threshold gradient warning, the trend warning and regression analysis, and dynamic prediction model based on gray model GM(1.1), we can draw the conclusion that gray GM (1.1) Model is a better prediction of gas and establishing a dynamic forecasting model is better than the static prediction model. Combined with down hole sensor data, the use of predictive models can quickly react to changes in gas. Through the gray association analysis of the gas, three factors including the CO concentration factor, wind speed and pressure are associated with the gas safety. While we collect real-time sensor data, we judge the roadway safety coefficient by the method of fuzzy AHP of information fusion. Finally the system dynamically generates an optimal escape route when the accident occurred according to real-time warning or safety coefficient. So, it improves the chances of escape of underground personnel. The main application of this system is to monitor the coal mine safety Pre-Warning and to generate the emergency hedge path throu... |
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