Research On Electromagnetic Emission Method Based On Coal And Gas Outburst Prediction

In recent years, China's coal mine safety accidents occur frequently. Which coal and gas outburst phenomenon to the underground coal mine safety production, and especially the staff of life and property caused an extremely serious threat, which gives the development of China's coal industry has sounded the alarm. Coal and gas outburst is a coal mine gas containing state of rock was crushed rock from coal mining space to the rapid (seconds to minutes to complete) motion and accompanied by a large number of gas exhaled a strong impetus to the process. Proved by long time prevention work and scientific research that coal and gas outburst takes place suddenly but has a lot of auguries including EME before outburst. Now, EME transmitting technology can't predict effectively because of a great deal of background noise and present noise processing technology, so the paper creatively proposed the method of noise processing based on wavelet packet transform and proved the feasibility of the method through a great deal of calculation and computer simulation. Based on basic principle of self-adapting neural network, the paper study the principle of EME self-adapting neural network forecasting coal and gas outburst in detail, and applied the method to forecast the danger of coal and gas outburst. It realized an EME dynamic trend prediction of the danger of coal and gas outburst. In the end, the paper designs the plan of the system simply.