Methodology for identifying the damage state of sandstone using Mel-frequency cepstral coefficient of acoustic emission

被引：0
|
作者：
He X. [1 ,2 ]
Yang F. [1 ]
Li Z. [1 ,2 ]
Li N. [1 ]
Song D. [1 ,2 ]
Wang H. [1 ,2 ]
Sobolev A. [3 ]
Rasskazov I. [3 ]
机构：
[1] School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing
[2] Key Laboratory of Ministry of Education for Efficient Mining and Safety of Metal Mine, University of Science and Technology Beijing, Beijing
[3] Mining Institute of the Far Eastern Branch, the Russian Academy of Sciences, Khabarovsk
来源：
Meitan Xuebao/Journal of the China Coal Society | 2024年 / 49卷 / 02期
关键词：
acoustic emission (AE); identification method; Mel-frequency cepstral coefficient (MFCC); sandstone damage state;
D O I：
10.13225/j.cnki.jccs.2023.0165
中图分类号：
学科分类号：
摘要：
Rock mass structure rupture is an important factor that seriously restricts the construction and safe operation of underground space engineering projects such as mines, subways and tunnels. Realizing the identification of rock mass fracture state is one of the hotspots and emphases of current research. In this study, some experiments of sandstone loading failure under different conditions were carried out, the acoustic emission Mel-frequency cepstral coefficient (MFCC) and its fluctuation difference during the whole loading process were extracted, the variation law of the coefficient and its fluctuation difference during the whole loading failure process was studied, and the correlation characteristics of coefficient No. 1 (According to the calculation of acoustic emission Mel-frequency cepstral coefficients, it can be seen that a set of acoustic emission Mel-frequency cepstral coefficient includes 12, and coefficient No. 1 refers to the first Mel-frequency cepstral coefficient) and its fluctuation difference with the fracture state of sandstone were analyzed. Based on this, a method to identify sandstone fracture state using the Mel-frequency cepstral of acoustic emission was proposed, and the identification criteria was constructed. The identification effect was finally verified. The results show that with loading increase, the coefficient No. 1 increases as a whole, and the coefficient value and its discreteness increase significantly in the failure stage and show significant regular fluctuations. The fluctuation difference of the coefficient has the characteristics of periodic variation. The size of the fluctuation difference and its fluctuation can characterize the fracture of sandstone. The overall increase and sudden increase of the fluctuation difference can reflect the macroscopic fracture of sandstone in the unstable deformation and post-peak failure stage, and the sudden increase level of the fluctuation difference can reflect the fracture degree of sandstone. The acoustic emission Mel-frequency cepstral coefficient and its fluctuation difference show good response characteristics to sandstone fracture, which is less affected by different loading conditions, thus they have applicability in reflecting sandstone fracture. The coefficient No.1 and its fluctuation difference have a good correlation with the fracture state of sandstone. The correlation can be divided into three stages as: in the micro-fracture stage of sandstone, the coefficient No.1 and its fluctuation difference are intensively distributed; in the unstable deformation stage just prior to the peak load, the distribution range increases sharply, the overall value increases and the high abnormal value appears; in the post-peak failure stage, the distribution range further increases, the overall value is higher, and more high abnormal values appear. The identification method and criteria of sandstone fracture state were constructed by using the 75% site value and outliers of coefficient No. 1 and the 75% site value and outliers of the fluctuation difference of coefficient No. 1. The effect of the identification criteria was tested by the confusion matrix of the three-classification model. The accuracy and precision of identification are 90.43% and 94.45%, respectively, which indicate the identification effect is good. The results can provide a reference for the identification of the fracture state of other types of coal and rocks, and for the monitoring and early warning of coal rock instability. © 2024 China Coal Society. All rights reserved.
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页码：753 / 766
页数：13
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