Microseism Monitoring System for Coal and Gas Outburst
The outburst forecast of coal and gas is a complex system engineering. On the basis of the analysis of microseism monitoring principle, a simplex positioning algorithm for microseism monitoring is designed; a mine microseism monitoring system is established to canalize mine microseism. Mechanism of the error producing and noise reduction measures is studied. We can analyze the data of the microseism monitoring to find coal or rock vibration caused by mining activities. Microseism monitoring system can capture real-time positioning information. It also can timely, accurately monitor and position these microseism events and the mining microseism event, which provide the pressure monitoring, the prediction of gas outstanding and the next step gas coal bed mining monitoring with reference experience.
Keywords: Coal and Gas Outburst, Microseism Monitoring, Simplex Type, Mining Dynamic Disaster Prediction
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ABOUT THE AUTHORS
Li Zhenbi
Mr. Zhenbi Li received the Bachelor's degree in science from the Shandong University, in 1981. He received the Master degree in mining machinery engineering from Huainan Institute of Industrial, in 1998. Currently, he is an associate professor at Anhui University of Science and Technology, China. His research interests include intelligent control and pattern recognition.
Zhao Baiting
Dr. Zhao Baiting received the MasterDegree in control theory and control engineering from the Qingdao University of Science & Technology, in 2005. He received the Ph.D. degree in control science and engineering from the Harbin Institute of Technology. Currently, he is a lectorate at Anhui University of Science & Technology, Electrical and Information Engineering College. His research interests include intelligent control and Fault diagnosis.
Li Zhenbi
Mr. Zhenbi Li received the Bachelor's degree in science from the Shandong University, in 1981. He received the Master degree in mining machinery engineering from Huainan Institute of Industrial, in 1998. Currently, he is an associate professor at Anhui University of Science and Technology, China. His research interests include intelligent control and pattern recognition.
Zhao Baiting
Dr. Zhao Baiting received the MasterDegree in control theory and control engineering from the Qingdao University of Science & Technology, in 2005. He received the Ph.D. degree in control science and engineering from the Harbin Institute of Technology. Currently, he is a lectorate at Anhui University of Science & Technology, Electrical and Information Engineering College. His research interests include intelligent control and Fault diagnosis.
