期刊
MEASUREMENT
卷 44, 期 9, 页码 1582-1591出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2011.06.011
关键词
Bearing fault diagnosis; Antisymmetric real Laplace wavelet; Envelope spectrum; Fault signal model; Wavelet filter; Differential evolution; Impulsive features; Vibration signal analysis
资金
- National Natural Science Foundation of China [50635010]
The presence of periodical impulses in vibration signals usually indicates the occurrence of rolling element bearing faults. Unfortunately, detecting the impulses of incipient faults is a difficult job because they are rather weak and often interfered by heavy noise and higher-level macro-structural vibrations. Therefore, a proper signal processing method is necessary. We proposed a differential evolution (DE) optimization and antisymmetric real Laplace wavelet (ARLW) filter-based method to extract the impulsive features buried in noisy vibration signals. The wavelet used in paper is developed from the fault characteristic signal model based on the idea of sparse representation in time-frequency domain. We first filter the original vibration signal using DE-optimized ARLW filter to eliminate the interferential vibrations and suppress random noise, then, demodulate the filtered signal and calculate its envelope spectrum. The analysis results of the simulation signals and real fault bearing vibration signals showed that the proposed method can effectively extract weak fault features. (C) 2011 Elsevier Ltd. All rights reserved.
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