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Microseismic Monitoring Data Fusion Algorithm and Coal and Gas Outbursts Prediction

Microseismic Monitoring Data Fusion Algorithm and Coal and Gas Outbursts Prediction
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摘要 The prediction study on coal and gas outbursts is carried out by monitoring some indices which are sensitive to the initiation of coal and gas outbursts. The values and changing roles of the indices are the foundations of coal and gas outbursts prediction. But now, only the data of ere key monitoring station is used in the coal and gas outbursts prediction practice, and the other data are ignored. In order to overcome the human factor and make full use of the monitoring information, the technique of multi-sensor target tracking is proposed to deal with the microseismic informatiion. With the results of microseismic events, the activities of geological structure, fracure-depth of roof and floor, and the location of gas channel are obtained. These studies indicate that it is considerably possible to predict the coal and gas outbursts using microseismic monitoring with its inherent ability to remotely monitor the progressive failure caused by mining.
出处 《Journal of Measurement Science and Instrumentation》 CAS 2010年第4期315-316,共2页 测试科学与仪器(英文版)
基金 supported by National Basic Research Programof China(973Program,2010CB226805) Shandong Province Natural Science Fund(Z2008F01) Key Laboratory of Mine Disaster Prevention and Control of Education Ministry(MDPC0809,MDPC0811)
关键词 coal and gas outbursts microseismic monitoring data fusion 煤与瓦斯突出预测 微震监测 数据融合 算法 人为因素 监测信息 跟踪技术 多传感器
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