Abstract
Rockburst is one of the critical safety concerns for underground engineering. The acoustic emission (AE) activity that occurs during rockburst is one of its notable characteristics. Because rockburst is induced by complexity factors, the prediction of rockburst has been investigated widely, yet few methods have been applied in depth. In this study, dynamic process of rockburst was investigated, and the information entropy of the dominant frequency was determined to be an indicator of rockburst. A series of true triaxial tests were conducted, and AE signals associated with the evolution of rock failure were collected. The AE data were treated with the fast Fourier transform to acquire the dominant frequency. Then, the information entropy of the dominant frequency was obtained, and a significant drop of the entropy value right after it reached the peak was observed. Finally, based on the comprehensive analysis of AE energy, dominant-frequency entropy, and other precursory information of rock failure, a multiparameter synergetic method of predicting rockburst is proposed. This research has important theoretical significance for improving the prediction accuracy of rockburst.
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Abbreviations
- X(j):
-
Input sequence
- N :
-
Frequency points
- W N :
-
Twiddle factor
- k :
-
A constant and k ≥ 0
- H :
-
Information entropy
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Acknowledgements
The authors would like to acknowledge the financial support from the National Natural Science Foundation of China (Grant No. 52074294, 51574246), National Key Research and Development Program of China (Grant No. 2017YFC0804201), and Fundamental Research Funds for the Central Universities (Grant No. 2011QZ01).
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Wang, C., Cao, C., Liu, Y. et al. Experimental investigation on synergetic prediction of rockburst using the dominant-frequency entropy of acoustic emission. Nat Hazards 108, 3253–3270 (2021). https://doi.org/10.1007/s11069-021-04822-6
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DOI: https://doi.org/10.1007/s11069-021-04822-6