Hybrid Method for Prediction of Coal and Gas Outburst Based on Data Fusion and Soft Sensor

摘要：

Based on introduction of the background and the limitations of present methods for coal and gas outburst,A hybrid method for prediction of coal and gas outburst based on soft sensor and data fusion combining many associated dynamic and static influence factors is proposed. In the method, the data fusion method based on arithmetic mean and batch estimation is used to process the dynamic influence factors data obtained by multiple sensors. And the soft sensor model based on fuzzy BP ANN predicts the dangerous status of coal and gas outburst according to the static factors data and the processed dynamic factors data. The application results show that the proposed method has high accuracy,and it is a practical method to dynamically and accurately predict coal and gas outburst.

关键词： coal and gas outburst soft sensor data fusion fuzzy BP ANN

作者: Xin Yan Naiwei Tu Hua Fu

作者单位: Faculty of Electrical and Engineering Control,Liaoning Technical University,Huludao 125105,China Research Center of Automation,Northeastern University,Shenyang 110004,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 2074-2078

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）