Ma Shaojie, Zhou Yan, Ma Depeng
Chongqing Vocational Institute of Engineering, Chongqing, 402260, China.
Shandong Agricultural University, Taian, 271018, China.
Sci Rep. 2024 Dec 30;14(1):31854. doi: 10.1038/s41598-024-83153-5.
Acoustic emission information can describe the damage degree of rock samples in the process of failure. However, as a discrete non-stationary signal, acoustic emission information is difficult to be effectively processed by conventional methods, while wavelet analysis is an effective method for non-stationary signal processing. Therefore, acoustic emission signal is deeply studied by using wavelet analysis method. In this paper, on the basis of noise reduction of acoustic emission signal, Matlab calculation program is used to decompose the acoustic emission signal of coal sample under the confining pressure test of triaxial unloading, and the singularity detection is carried out. The results show that the time when the Lipschitz index value first appears α negative can be used as the prediction time. However, the corresponding time when the Lipschitz index value is -0.15~-0.31 should be excluded; The absolute range of the difference between the final forecast time and the actual rupture time of coal samples is [5.2s, 17.1s], and the coal samples with the absolute value of time difference within [5.2s, 10.0s] account for 63.6% of the total.
声发射信息能够描述岩石试样在破坏过程中的损伤程度。然而，声发射信息作为一种离散的非平稳信号，难以用传统方法进行有效处理，而小波分析是处理非平稳信号的一种有效方法。因此，采用小波分析方法对声发射信号进行深入研究。本文在对声发射信号降噪的基础上，利用Matlab计算程序对三轴卸载围压试验下煤样的声发射信号进行分解，并进行奇异性检测。结果表明，Lipschitz指数值首次出现α为负的时刻可作为预测时间。但应排除Lipschitz指数值为-0.15~-0.31时对应的时间；煤样最终预测时间与实际破裂时间的绝对差值范围为[5.2s，17.1s]，时间差值绝对值在[5.2s，10.0s]内的煤样占总数的63.6%。
