Recognition of frequency information in acoustic emission monitoring of rock fracture
LIU Xiang-xin1,2, ZHANG Yan-bo1, LIANG Zhen-zhao2, LIU Shan-jun3
1. School of Mining Engineering, North China University of Science and Technology, Tangshan 063009, China; 2. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China; 3. Institute for Geo-informatics and Digital Mine Research, Northeastern University, Shenyang 110818, China
Abstract：The mathematical methods of FFT and wavelet transform are used to deal with the acoustic emission (AE) frequency information of rock fracture firstly. Combined with the spectral distribution of AE signal, the main response spectrum of this lithology in specific form of fracture is selected. The AE precursor advantage spectrum and its calculation method, the most suitable short-term and optimal impending prediction parameters should be optimized, which gives a new way to monitor the disasters of rock mass engineering. In order to prove the validity of this method, the circular tunnel model is used in horizontal unloading tests in laboratory. The results show that the model edge wall around the tunnel is fractured at the moment of horizontal unloading. The energy achieves 73% between 31.25 and 62 kHz, which reflects the properties of rock materials. When it is near the breakdown (TP=2425 s), the changing coefficient of becomes from 0.5 to 15, and it has characteristics of typical disaster response. (7.8125 ~ 15.625 kHz) is the precursor advantage spectrum, and can be used as the macro rupture of short-term and impending prediction parameters combined with the sudden emergence in (90 ~ 105 kHz) and (13 ~ 20kHz) of AE main-frequency. The proposed method may provide new characteristic parameters for disasters monitoring and early warning in rock mass engineering.
刘祥鑫, 张艳博, 梁正召, 刘善军. 岩石破裂失稳声发射监测频段信息识别研究[J]. 岩土工程学报, 2017, 39(6): 1096-1105.
LIU Xiang-xin, ZHANG Yan-bo, LIANG Zhen-zhao, LIU Shan-jun. Recognition of frequency information in acoustic emission monitoring of rock fracture. Chinese J. Geot. Eng., 2017, 39(6): 1096-1105.
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