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Lingjie Meng,Jiawei Xiang,Yongteng Zhong,Wenlei Song 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.8
Defective rolling bearing response is often characterized by the presence of periodic impulses. However, the in-situ sampled vibrationsignal is ordinarily mixed with ambient noises and easy to be interfered even submerged. The hybrid approach combining the secondgeneration wavelet denoising with morphological filter is presented. The raw signal is purified using the second generation wavelet. Thedifference between the closing and opening operator is employed as the morphology filter to extract the periodicity impulsive featuresfrom the purified signal and the defect information is easily to be extracted from the corresponding frequency spectrum. The proposedapproach is evaluated by simulations and vibration signals from defective bearings with inner race fault, outer race fault, rolling elementfault and compound faults, respectively. Results show that the ambient noises can be fully restrained and the defect information of theabove defective bearings is well extracted, which demonstrates that the approach is feasible and effective for the fault detection of rollingbearing.