工程尺度下微震信号及P波初至自动识别AB算法

doi:10.13722/j.cnki.jrme.2016.0178

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Abstract To improve the recognition rate of microseismic signal with low SNR and the pickup accuracy of P wave in the engineering noise environment，Allen algorithm which can pick up microseismic signal automatically and quickly and Bear algorithm which is good at picking up the microseismic signal with low SNR at the beginning of the P wave were combined to form an AB algorithm with the introduction of Bear weighted factor and characteristic function on the basis of Allen algorithm. The AB algorithm can identify the microseismic signals accurately and accurately pick up the changed P wave automatically. The weighting factor K，characteristic function CF and value of AB algorithm have higher sensitivity to the changes of frequency and amplitude than Allen algorithm. The AB algorithm is more susceptive to the change of amplitude than frequency. The pickup rate of the seismic signal and the pickup accuracy of the automatic P wave in the AB algorithm are better than the Allen algorithm at the project scales. The analysis of the microseismic signal from the deep underground laboratory at Jinping shows that the positioning results of the microseismic sources exhibit higher reliability and stability based on the AB algorithm for the weak signal. The AB algorithm is confirmed to be effective，simple and suitable for the real time monitoring of microseismic signal and the pickup of first arrival of P wave.

Key words： rock mechanics microseism P-wave pickup signal recognition AB algorithm

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	Articles by authors
	LI Xian1
	WANG Wenjie1
	CHEN Bingrui2

Cite this article:

LI Xian1,WANG Wenjie1,CHEN Bingrui2. AB algorithm suitable for identifying the microseismic signal and#br# first arrival of P-wave automatically at the project scale[J]. , 2017, 36(3): 681-689.

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http://www.rockmech.org/EN/10.13722/j.cnki.jrme.2016.0178 OR http://www.rockmech.org/EN/Y2017/V36/I3/681

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