Feature extraction, recognition, and classification of acoustic emission waveform signal of coal rock sample under uniaxial compression
文献类型：期刊论文
| 作者 | Ding, Z. W.; Li, X. F.; Huang, X.; Wang, M. B.; Tang, Q. B.; Jia, J. D. |
| 刊名 | INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
 |
| 出版日期 | 2022-12-01 |
| 卷号 | 160 |
| ISSN号 | 1365-1609 |
| 关键词 | Material identification Acoustic emission Signal feature extraction Mel frequency cepstrum coefficient Deep learning |
| 英文摘要 | In this study, based on Mel frequency cepstrum coefficient (MFCC) method, the AE signal characteristics of coal and rock samples were extracted, and the stress state criterion based on signal features was constructed. By integrating back propagation (BP) neural network for deep learning of signal characteristics, the recognition, classification, and prediction of coal and rock materials were realized. The results show that the MFCC could characterize the variation law of the original signal, with the sharp fluctuation of the amplitudes of both the AE signal and MFCC when the rock stress was near the peak value. Considering the ratio of sample stress to peak stress as the stress state, the correlation between MFCC and stress state was analyzed. The BP neural network exhibited a high accuracy rate for the signal characteristics represented by MFCC, achieving an accuracy of more than 95% with a fast recognition speed. Notably, the evaluation results of neural network model were stable and reliable. Therefore, MFCC can be used to extract the AE waveform signal characteristics and evaluate the stability of stress state for coal and rock materials. The recognition, classification, and prediction of high-precision results of the two types of waveform characteristics of coal and rock can be achieved through BP neural network. |
| 学科主题 | Engineering ; Mining & Mineral Processing |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000894821900002 |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/34911]  |
| 专题 | 中科院武汉岩土力学所 |
| 作者单位 | 1.Xi'an University of Science & Technology; 2.Chinese Academy of Sciences; Wuhan Institute of Rock & Soil Mechanics, CAS |
| 推荐引用方式 GB/T 7714 | Ding, Z. W.,Li, X. F.,Huang, X.,et al. Feature extraction, recognition, and classification of acoustic emission waveform signal of coal rock sample under uniaxial compression[J]. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES,2022,160. |
| APA | Ding, Z. W.,Li, X. F.,Huang, X.,Wang, M. B.,Tang, Q. B.,&Jia, J. D..(2022).Feature extraction, recognition, and classification of acoustic emission waveform signal of coal rock sample under uniaxial compression.INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES,160. |
| MLA | Ding, Z. W.,et al."Feature extraction, recognition, and classification of acoustic emission waveform signal of coal rock sample under uniaxial compression".INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES 160(2022). |
入库方式： OAI收割
来源：武汉岩土力学研究所
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