Based On Acoustic Emission Of Coal And Gas Outburst Prediction

In recent years, China’s coal mine accidents occur frequently.Including coal and gasOutburst phenomenon,to the coal mine safety production,especially the staff of theunderground life and property caused by an extremely serious threat.This gives thedevelopment of China’s coal industry has sounded the alarm.Coal and gas outburst is thegas containing coal mine rock was crushed to the state from coal mining space rockssharp(a few seconds to several minutes to complete)along with a lot of movement andemitted a strong gas outburst,although unexpected,but the former are precursors of thehighlights show,which is the precursor of electro magnetic radiation.As the scousticemission signal contains a lot of noise,and noise reduction technology can not currentlymake a good prediction based on gradient type lifting wavelet packet threshold of noisereduction method,and through a large number of numerical calculations and computersimulations demonstrate the feasibility of the idea.Proposed based on wavelet neural network ant colony optimization of coal and gasoutburst prediction model,systematic study of the acoustic emission of coal and gasoutburst prediction of neural network theory,the acoustic emission adaptive neuralnetwork model is applied to coal and gas outburst prediction.To achieve a coal and gasoutburst prediction of the dynamic trend of acoustic emission.Finally,the article brieflydescribes the monitoring symtem design implementation.