Microseismic Signal Spectra,Energy Characteristics,and Fractal Features Prior to Rock Burst: A Case Study from the Qianqiu Coal Mine,China |
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Authors: | Xuelong Li Enyuan Wang Junjun Feng Liang Chen Nan Li |
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Affiliation: | 1. Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology, Xuzhou, Jiangsu, China;2. School of Safety Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, China;3. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Xuzhou, Jiangsu, China |
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Abstract: | Microseismic (MS) technology has been widely adopted for monitoring coal and rock dynamic disasters. Insights into MS wave characteristics contribute to the accurate prediction of these disasters. In this study, MS wave characteristics were analysed from three aspects: the signal spectra, wavelet packet energy and fractal features. It is shown that prior to the rock burst, the MS wave main frequency decreased following a power law, the amplitude linearly increased, the wavelet packet energy tended to become concentrated on the low frequency bands, and the correlation dimension decreased. When the rock burst occurred, the MS wave main frequency, wavelet packet energy and correlation dimension declined to their lowest levels. Meanwhile, the amplitude rose to a maximum. Therefore, the MS wave characteristics in this study were found to effectively identify and extract precursor information of value for predicting rock dynamic disasters. |
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Keywords: | Rock Burst Microseismic Wave Spectrum Wavelet Packet Fractal Feature |
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