Recently, postdoctoral fellow (assistant research fellow) Zhenghu Zhang from the Centre for Rock Instability and Seismicity Research published a paper entitled "A new method for determining the crack classification criterion in acoustic emission parameter analysis" in the authoritative journal "International Journal of Rock Mechanics and Mining Sciences". This paper was identified as a key scientific article contributing to research excellence by Advances in Engineering (AIE), a well-known international science and technology organization, and a special report was made on the results of the paper. Both the first author and corresponding author are from Dalian University of Technology. Dr. Zhenghu Zhang is a postdoctoral fellow in the team of Professor Tang Chunan from the Centre for Rock Instability and Seismicity Research, Faculty of Infrastructure Engineering.
In this paper, Dr. Zhang proposed a method to determine the crack classification criterion in acoustic emission (AE) parameter analysis for rock-like materials. At a microscopic scale, the failure of brittle materials results from crack initiation, propagation and coalescence. AE technique has been widely used to investigate the formation and growth of cracks in brittle materials and predict the safety and performance of engineering structures. Acoustic emission can be classified into two methods: waveform-based analysis and parameter-based method/parameter analysis. Parameter analysis is commonly used owing to its convenience and efficiency. However, the crack classification criterion of the existing parameter analysis is based on the empirical relation between RA value and average frequency, which may not provide the desired accuracy In view of the need and existing shortcomings, this study proposed a method based on statistical analysis of dominant frequency characteristics of AE waveforms to determine the crack classification criteria in AE parameter analysis. This method combines the advantages of waveform and parametric analyses to greatly improve the accuracy and efficiency of AE crack classification, structure monitoring and damage analysis. The study found that the optimal ratio of the RA and A-FRQ values of brittle rocks is approximately 1:100 to 1:500. The findings in this study are of great significance for enhancing the understanding of mechanical behaviors and fracture mechanisms of rock in rock bursts, landslides and other engineering disasters.
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This research was funded by the National Natural Science Foundation of China and the National Key Research and Development Program.
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