|
Abstract: 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 trans-form, 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 gear-box vibration signals and cryptic information submerged in a heavy noise, and has an excellent effect on extracting weak periodical impulse components to diagnose fault.
Key words: Dual-tree complex wavelet transform Denoising
Block thresholding Fault diagnosis
CLC No: TH165.3 TN911.7 TP206.3
北京市自然科学基金资助项目(3062012). Received 20060718, received in revised form 20070309
|