Abstract S-wave phase picking is a fundamental and important part in microseismic monitoring technology. The efficiency of S-wave picking affects the analysis of microseismic source location,seismic source mechanism,seismic activity prediction and rock stress redistribution directly. Currently,the automatic S-wave identification in microseismic monitoring system is not precise enough,time-consuming and lowly efficient and the manual identification need be carried out again. By analyzing three time-domain characteristic functions of the microseismic signals in mines,including the average cross zero ratio,the average amplitude and the short time energy over short time,four S-wave identification indicators were obtained. Then,an algorithm with four indicators of three functions for S-wave identification was established. The empirical thresholds to detect S-phase were obtained according to the actual microseismic events. And a code was written on the basis of the empirical thresholds for automatic analysis of examples. Comparisons of the results from the automatic and manual identification showed that the accuracy rate of automatic identification reached within 88% and 74% within 25 ms and 12.5 ms respectively . The recognition effect was the best for the short time energy,followed by the short time average cross zero ratio and the short time average amplitude.
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