Research On Warning Technology Of Coal And Gas Outburst Based On Methane Monitoring Data

Coal and gas outburst dynamic warning based on methane monitoring data to guard mines for safe production has important practical significance. Total 62 outburst events in Hebi coalfield were analyzed. Following the outburst features and controlling factors studied, the influence factor of gas emission on coal and gas outburst was introduced subsequently. It was recognized that the dynamic changes of gas emission was consistent with the outburst risk. Either rising or fluctuation of gas emission is the precursor information of outburst, and it is entirely feasible to predict the oburst risk through dynamic changes of gas emission. Using chaos time series theory,the phase space of gas concentration time series was reconstructed, time delayτwas calculated using the autocorrelation function, and the embedding dimension m was calculated by saturated correlation dimension method. The final weighted first-order Board domain method of gas concentration was used for reliably short-term forecasting and prediction. Finally, setting monitoring data of Hebi No.10 mine as an example, the gas concentration features of 3 outbursts were analyzed in detail. The index system by means of monitoring data predicting coal and gas outburst was put forward. The indexes used were the average gas emission Q , the increase gas emission rate△Q, the ratio of post-blasting gas emission B, and abnormal gas emission coefficient Kv. The values of above parameters were determined as 2.5m3/min, 0.5m3/min, 4 and 0.5 respectively. This provides a theoretical basis for early coal and gas outburst warning system developed in Hebi coalfield condition.