小波-EMD和随机共振级联微弱信号检测  

Wavelet-EMD and stochastic resonance cascade weak signal detection

作　　者：张刚[1] 李红威 

机构地区：[1]重庆邮电大学通信与信息工程学院

出　　处：《电子测量与仪器学报》2018年第1期57-65,共9页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(61771085,61371164,61275099);信号与信息处理重庆市市级重点实验室建设(CSTC2009CA2003);重庆市教育委员会科研(KJ1600427,KJ1600429)资助项目

摘　　要：针对低信噪比下微弱信号检测困难问题,提出了一种三级级联微弱信号联合检测系统;首先将含噪信号通过小波阈值降噪,然后将降噪后的信号进行经验模态分解(EMD),利用信噪比定位模态法选取信噪比较高模态分量,对选取的模态进行合成使其待测特征得到突出;最后将其送入欠阻尼三稳态系统,使用果蝇智能参数寻优算法将稳态系统达到最佳随机共振状态,便于检测结果精确可靠。经过单频小信号及混频大信号仿真分析和滚动轴承内外圈故障诊断表明,该系统能够使-30 dB左右微弱信号的信噪比至少增加20 dB,扩大了微弱信号的检测范围,提高了检测的有效性。In order to solve the problem of weak signal detection under low signal-to-noise ratio( SNR),a three-level cascaded weak signal united detection system is proposed. First,the noisy signal is denoised by the wavelet threshold; Then after noise reduction,the signal is decomposed by( empirical mode decomposition,EMD),and the modal components with higher SNR is chosen by using SNR location modal method. Then the selected modal is synthesized so that the measured features are highlighted; Finally,the signal is input into the underdamped tri-stable system. To obtain the optimal stochastic resonance,the intelligent parameter optimization algorithm of Drosophila is adopted,which is convenient and reliable. Simulations are carried on for detection of small signal with single frequency and mixed large-signal. Also the system are applied to the fault diagnosis on inner and outer rolling bearing. All of above indicate the system can raise the input SNR from-30 dB to at least 20 dB,thus expanding the detection range of the weak signal,and improving the detection effectiveness.

关 键 词：小波 经验模态分解 随机共振 欠阻尼三稳态 信噪比 

分 类 号：TN911.23[电子电信—通信与信息系统]