Denoising method of rock acoustic emission signal based on EEMD-SCBSS
ZHAO Kui1,2, YANG Daoxue1,2, ZENG Peng1,2, WANG Xiaojun1,2, ZHONG Wen1,2, GONG Cong1,2, YAN Lei1,2
1.School of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;
2.Jiangxi Provincial Key Lab of Mining Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
Abstract：In view of the characteristics of rock acoustic emission signals such as low signal-to-noise ratio, strong randomness and non-stationarity, a method of denoising rock acoustic emission signals based on ensemble empirical mode decomposition (EEMD) and single channel blind source separation (SCBSS) is proposed. Firstly, rock acoustic emission signals with background noise are decomposed by EEMD to obtain a series of intrinsic mode functions (IMF) arranged from high to low frequencies. Secondly, virtual multi-channel observation signals are constructed by extracting high-frequency background noise signals and observation signals. Finally, the fast-independent component analysis (FastICA) is used to separate the Virtual Multi-channel observation signals, and then the denoised rock acoustic emission signals are obtained. By constructing the numerical simulation experiment of acoustic emission signal with noise and analyzing the measured data, and comparing the denoising method based on EEMD and SCBSS with the wavelet threshold denoising method. The experimental results show that the wavelet threshold denoising method can lead to the distortion of frequency domain information of denoised rock acoustic emission signal, and affect the identification of parameters, such as rising time and energy of rock acoustic emission signal after denoising. The method proposed in this paper can effectively denoise rock acoustic emission signals with noise, suppress non-stationary random noise in acoustic emission signals, and protect the frequency domain information of rock acoustic emission signals after denoising.
赵奎1,2,杨道学1,2,曾鹏1,2,王晓军1,2,钟文1,2,龚囱1,2,闫雷1,2. 基于EEMD-SCBSS的岩石声发射信号去噪方法[J]. 振动与冲击, 2021, 40(5): 179-185.
ZHAO Kui1,2, YANG Daoxue1,2, ZENG Peng1,2, WANG Xiaojun1,2, ZHONG Wen1,2, GONG Cong1,2, YAN Lei1,2. Denoising method of rock acoustic emission signal based on EEMD-SCBSS. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(5): 179-185.
[1] KURITA K, FUJII N. Stress memory of crystalline rocks in acoustic emission[J]. Geophysical Research Letters, 1979, 6(1): 9-12.
[2] EBERHARDT E, STEAD D, STIMPSON B, et al. Identifying crack initiation and propagation thresholds in brittle rock[J]. Canadian Geotec- hnical Journal, 1998, 35(2): 222-233.
[3] 蔡美峰，何满潮，刘东燕. 岩石力学与工程[M].北京：科学出版社，2013.
CAI Meifeng, HE Manchao, LIU Dongyan. Rock Mechanics and engineering[M].Beijing: Science press, 2013.
[4] Meng Q B, Zhang M W, Han L J, et al. Acoustic emission characteristics of red sandstone specimens under uniaxial cyclic loading and unloading compression[J]. Rock Mechanics and Rock Engineering, 2018, 51(4): 969-988.
[5] Goodman R E. Subaudible noise during compression of rocks[J]. Geological Society of America Bulletin, 1963, 74(4): 487-490.
[6] 李庶林,周梦婧,高真平,等.增量循环加卸载下岩石峰值强度前声发射特性试验研究[J].岩石力学与工程学报,2019,38(04):724-735.
LI Shulin, ZHOU Mengjing, GAO Zhenping, et al. Experimental study on acoustic emission characteristics before the peak strength of rocks under incrementally cyclic loading-unloading methods[J]. Chinese Journal of Rock Mechanics and Engineering, 2019, 38(04): 724-735.
[7] 向高,刘建锋,李天一,等.基于声发射的盐岩变形破坏过程的分形与损伤特征研究[J].岩土力学,2018,39(08):2905-2912.
XIANG Gao, LIU Jianfeng, LI Tianyi et al. Study of fractal and damage characteristic in the deformation and failure process of salt rack based on acoustic emission[J]. Rock and Soil Mechanics, 2018, 39(08): 2905-2912.
[8] 赵奎,周永涛,曾鹏,等.三点弯曲作用下不同粒径组成的类岩石材料声发射特性试验研究[J].煤炭学报,2018,43(11):3107-3114.
ZHAO Kui, ZHOU Yongtao, ZENG Peng, et al. Experimental study on acoustic emission characteristics of rock-like materials with different particle sizes under three-point bend- ing[J]. Journal of China Coal Society, 2018, 43(11): 3107-3114．
[9] 李铁,李柯萱,皮希宇,等.弯载下砂岩声发射特征值时间效应[J].煤炭学报, 2018, 43(11): 3115-3121.
LI Tie, LI Kexuan, PI Xiyu, et al. Time- dependent behavior of acoustic emission feature parameters of sandstone under bending load[J]. Journal of China Coal Society, 2018, 43(11): 3115-3121.
[10] 陈栋,王恩元,李楠,等.石膏和砂岩试样损伤破裂及声发射时空演化规律研究[J].煤炭学报,2018,43(07):1902-1909.
CHEN Dong, WANG Enyuan, LI Nan, et al. Study on the fracture and the law of temporal- spatial evolution of acoustic emission of gypsum and sandstone specimens[J]. Journal of China Coal Society, 2018, 43(07): 1902-1909.
[11] 贾瑞生,赵同彬,孙红梅,等.基于经验模态分解及独立成分分析的微震信号降噪方法[J].地球物理学报,2015,58(03):1013-1023.
JIA Ruisheng, ZHAO Tongbin, SUN Hongmei, et al. Microseismic signal denoising method based on empirical mode decomposition and independent component analysis[J]. Chinese Journal of Geophysics, 2015, 58(03): 1013- 1023.
[12] 李成武,解北京,杨威,等.基于HHT法的煤冲击破坏SHPB测试信号去噪[J].煤炭学报,2012, 37(11):1796-1802.
LI Chengwu, JIE Beijing, YANG Wei, et al. Coal impact damage SHPB testing signal de-noising based on HHT method[J]. Journal of China Coal Society, 2012, 37(11): 1796-1802.
[13] 徐锋,刘云飞,宋军.基于中值滤波-SVD和EMD的声发射信号特征提取[J].仪器仪表学报,2011,32(12):2712-2719.
XU Feng, LIU Yunfei, SONG Jun. Feature extraction of acoustic emission signals based on median filter-singular value decomposition and empirical mode decomposition[J]. Chinese Journal of Scientific Instrument, 2011, 32(12): 2712-2719.
[14] Wu Z, Huang N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method[J]. Advances in adaptive data analysis, 2009, 1(01): 1-41.
[15] 戴聪聪,程铁栋,宗路,等.基于改进EEMD的红砂岩声发射信号的频谱特性研究[J].振动与冲击,2018,37(16):118-123.
DAI Congcong, CHENG Tiedong, ZONG Lu, et al. A study on spectrum characteristics of red sandstone acoustic emission signals based on improved EEMD[J]. Journal of Vibration and Shock, 2018, 37(16): 118-123.
[16] 凌同华，张胜，易志强，等. AE信号能量分布特征的EMD分析[J]．振动与冲击，2012，31(11): 26 －31．
LING Tonghua, ZHANG Sheng, YI Zhiqiang, et al. EMD analysis of energy distribution characteristics of rock acoustic emission signals[J]．Vibration and Shock，2012，31(11):26 －31．
[17] 黄艳波. 单通道盲源分离算法的研究[D].杭州：杭州电子科技大学,2017.
HUANG Yanbo. The Research of single-channel blind source separation algorithm[D]. Hangzhou: Hangzhou Dianzi University, 2017.
[18] 刘琚，孙建德，许宏吉. 盲信号处理理论与应
用[M].北京：科学出版社，2013.
LIU Ju, SUN Jiande, XU Hongji. Theory and application of blind signal processing[M]. Beijing: Science press, 2013.
[19] 何鹏举,刘刚易,折廷廷.单通道AE信号盲分离的飞机构件监测方法研究[J].仪器仪表学报,2018,39(08):34-42.
HE Pengju, LIU Gangyi, SHE Tingting. Research on monitoring of aircraft structural components based on blindseparation of single channel AE signal[J]. Chinese Journal of Scientific Instrument, 2018, 39(08): 34-42.
[20] 刘诚. 基于独立分量分析的地震信号多次波盲分离方法研究[D].成都：成都理工大学, 2008.
LIU Cheng. The method of multiple attenuation based on independent component analysis[D]. Chengdu: Chengdu University of Technology, 2008.
[21] 李成杰. 盲源信号分离算法研究及应用[D].成都：电子科技大学,2017.
LI Chengjie. Research on Algorithm and Application of Blind Source Signal Sepa- ration[D]. Chengdu: University of Electronic Science and Technology of China, 2017.
[22] 宫月,贾瑞生,卢新明,等.利用经验模态分解及小波变换压制微震信号中的随机噪声[J].煤炭学报,2018,43(11):3247-3256.
GONG Yue, JIA Ruisheng, LU Xinming, et al. To suppress the random noise in microseismic signal by using empirical mode decomposition and wavelet transform[J]. Journal of China Coal Society, 2018, 43(11): 3247-3256.
[23] Zheng J D, Cheng J S, Yang Y. Partly ensemble empirical mode decomposition: An improved noise-assisted method for eliminating mode mixing[J]. Signal Processing, 2014, 96: 362-374.
[24] Mitraković D, Grabec I, Sedmak S. Simulation of AE signals and signal analysis systems[J]. Ultrasonics, 1985, 23(5): 227-232.
