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An effective method for laboratory acoustic emission detection and location using template matching

Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1642-1651页

作者： Xinglin Lei Tomohiro Ohuchi Manami Kitamura Xiaying Li Qi Li National Institute of Advanced Industrial Science and Technology(AIST) Tsukuba305-8567Japan Geodynamics Research Center Ehime UniversityMatsuyama790-8577Japan State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China University of Chinese Academy of Sciences Beijing100049China

In this paper, a template matching and location method, which has been rapidly adopted in microseismic research in recent years, is applied to laboratory acoustic emission(AE) monitoring. First, we used traditional methods to detect P-wave first motions and locate AE hypocenters in three dimensions. In addition, we selected events located with sufficient accuracy(normally corresponding AE events of relatively larger energy, showing clear P-wave first motion and a higher signal-to-noise ratio in most channels) as template events. Then, the template events were used to scan and match other poorly located events in triggered event records or weak events in continuous records. Through crosscorrelation of the multi-channel waveforms between the template and the event to be detected, the weak signal was detected and located using a grid-searching algorithm(with the grid centered at the template hypocenter). In order to examine the performance of the approach, we calibrated the proposed method using experimental data of different rocks and different types of experiments. The results show that the proposed method can significantly improve the detection capability and location accuracy, and can be applied to various laboratory and in situ experiments, which use multi-channel AE monitoring with waveforms recorded in either triggering or continuous mode.

关键词： Acoustic emission template matching and location Waveform cross-correlation Grid search

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