摘要
针对岩石声发射(AE)信号的低信噪比、随机性强、非平稳性等特点,提出了一种基于总体经验模态(EEMD)及单通道盲源分离(SCBSS)的AE信号滤波方法。将含有背景噪声的AE信号进行EEMD分解,得到一系列按频率从高到低排列的本征模函数(IMF);提取高频背景噪声信号与观测信号构建虚拟多通道观测信号;利用快速不动点优化算法(FastICA)对构建的虚拟多通道观测信号进行盲源分离(BSS),进而得到滤波后的AE信号。通过构造含噪声AE信号进行数值仿真实验及实测数据分析,将基于EEMD及SCBSS滤波方法与小波阈值滤波方法进行比较。实验结果表明:小波阈值滤波方法会导致滤波后的AE信号频域信息失真,影响滤波后的AE信号上升时间,能量等参数识别;该方法可以对含噪声AE信号进行有效地滤波处理,能够较好地滤除AE信号中的非平稳随机噪声,并且能够保护滤波后的AE信号频域信息。
Aiming at characteristics of rock acoustic emission(AE)signal,such as,low signal-to-noise ratio,strong randomness and non-stationarity,etc.,a filtering method of AE signals based on ensemble empirical mode decomposition(EEMD)and single channel blind source separation(SCBSS)was proposed.Firstly,an AE signal with background noise was decomposed with EEMD to obtain a series of intrinsic mode functions(IMFs)arranged from higher frequency to lower one.Secondly,high frequency background noise signal and observation signal were extracted to construct virtual multi-channel observation signals.Finally,the fast-independent component analysis(Fast ICA)algorithm was used to do blind source separation(BSS)of the constructed virtual multi-channel observation signal,and then obtain the denoised AE signal.Through constructing AE signal with noise to do numerical simulation tests and analyzing the actually measured data,the filtering method based on EEMD and SCBSS was compared with the wavelet threshold filtering method.The test results showed that the wavelet threshold filtering method can cause the distortion of frequency domain information of denoised rock AE signal,and affect the identification of parameters of rising time and energy for rock denoised AE signal;the proposed method can effectively denoise rock AE signals,suppress non-stationary random noise in AE signals,and protect frequency domain information of rock denoised AE signals.
作者
赵奎
杨道学
曾鹏
王晓军
钟文
龚囱
闫雷
ZHAO Kui;YANG Daoxue;ZENG Peng;WANG Xiaojun;ZHONG Wen;GONG Cong;YAN Lei(School of Resources and Environmental Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China;Jiangxi Provincial Key Lab of Mining Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2021年第5期179-185,210,共8页
Journal of Vibration and Shock
基金
国家重点研发计划资助项目(2017YFC0804601)
国家自然科学基金资助项目(51664018)
江西理工大学优秀博士论文培育项目(3105500025)。
关键词
岩石声发射信号
去噪
总体经验模态
单通道盲源分离
rock acoustic emission(AE)signals
denoising
ensemble empirical mode decomposition(EEMD)
single channel blind source separation(SCBSS)
