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Research of Rolling Bearings Fault Diagnosis
CHEN Yong-hui;JIANG Xu;ZHANG Xue-liang;LI Hai-hong
2011, 31 (5):
133-136.
DOI: 10.3969/j.issn.1006-1355-2011.05.031
For the non-stationary and modulation features of rolling bearing’s fault signals, a method based on wavelet analysis is employed. The signals including fault information are decomposed and reconstructed by wavelet analysis method. Then, demodulation and fine spectral analysis of the signals are carried out by using Hilbert transform. The characteristic frequencies of the fault signals are extracted, and the fault patterns of the rolling bearings can be recognized. It is found that the wavelet analysis and Hilbert transform are effective in identifying the local defects of rolling bearings.
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