With the increase of mining depth and intensity of mining face,the risk of microseismic events and disasters in underground coal mines continues to increase.Combined with the microseismic moni-toring data of the tunneling roadway in Zhangcun Coal Mine,the b-value optimization analysis and informa-tion recognition classification of the microseismic events in the area in front of the tunneling face are carried out.A variational root-square algorithm based on the least square method is proposed.A variational root-square algorithm based on the least square method is proposed.The b-value and source of the fault area are analyzed from the three angles of'time,space and strength',and the accuracy of the b-value is optimized.The research improves the reliability of microseismic monitoring and early warning and better guides mine safety production.
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