Fast Inversion for Advanced Detection Using Electronic Resistivity in Coal Mineral Well Based Genetic Algorithm and Finite Element Method
The geology fault and subsided column in coal mineral are one of geological problems of impact on normal mining coal and safe production. In order to predict so accurately the shape, scope and water yield property of the fault an subsided column as to reduce coal mine disasters, based on the basic principles of electronic investigation method, dealing with data observed with inversion method, the situation of extension of the fault and subsided column in mining face is explored. In the paper, the weak signals of the geology fault and subsided column are recognized by back propagation neural network(BPNN). The shape of structure of the fault and subsided column is got by finite element method (FEM) and the least-square algorithm (LSA) improved by genetic algorithm (GA). The process is simulated with computer. The exploration and simulated results are consistent with drilling results. This shows that it is effective to apply the method proposed in the paper to detecting and predicting the geology fault and subsided column in coal mine.
Fault signals genetic algorithms finite element method Coal mineral well global optimization value
YU Sheng chen GUO Hui YU Gui xian LIU Bao jin CHE Jing jing SHAO Tie jun
Computer Science Department of North China Institute of Science & Technology,Beijing,China Beijing Zhao Fang Investment Trust Co.Ltd.Beijing Shanxi Luan Good-Environment Energy Co.Ltd,Shanxi Chanzhi,China,234000
国际会议
太原
英文
335-338
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）