基于复小波块阈值的降噪方法及其在机械故障诊断中的应用  

DENOISING METHOD OF BLOCK THRESHOLDING BASED ON DT-CWT AND ITS APPLICATION IN MECHANICAL FAULT DIAGNOSIS

作　　者：陈志新[1] 徐金梧[1] 杨德斌[1] 

机构地区：[1]北京科技大学机械工程学院,北京100083

出　　处：《机械工程学报》2007年第6期200-204,共5页Journal of Mechanical Engineering

基　　金：北京市自然科学基金资助项目(3062012)。

摘　　要：提出一种基于对偶树复小波块阈值的信号降噪方法,并将其成功应用于机械故障诊断中。机械设备的振动信号都或多或少地含有噪声,导致弱故障信息的提取一直是故障诊断的难点和热点。提出的降噪方法充分利用对偶树复小波变换的平移不变性和块阈值法的更优估计特性,可以获得比常规的小波降噪方法以及基于常规离散正交小波变换的NeighBlock降噪法更高的信噪比,不仅能有效抑制高斯白噪声,还能够去除冲击信号中的脉冲噪声。对实际信号的研究表明:这种降噪方法可以提取齿轮箱早期故障信息和强噪声背景情况下的隐含故障信息,特别对提取弱冲击故障信号非常有效。A denoising method of block thresholding based on DT-CWT （Dual-tree complex wavelet transform） is proposed, aiming at the difficulty of extracting weak failure information in machinery vibration signals. The presented method can obtain higher signal-to-noise ratio （SNR） than NeighBlock and other common methods based on orthonormal discrete wavelet transform, because of improving asymptotic optimality of block thresholding estimator and shift invariance of DT-CWT. It can not only suppress white Gaussian noise, but also remove spike pulse noise in impulsive signal effectively. Experiments indicate that the method can extract incipient fault feature in gearbox vibration signals and cryptic information submerged in a heavy noise, and has an excellent effect on extracting weak periodical impulse components to diagnose fault.

关 键 词：对偶树复小波变换 降噪 块阈值 故障诊断 

分 类 号：TH165.3[机械工程—机械制造及自动化] TN911.7[电子电信—通信与信息系统]