FAULT FEATURE EXTRACTION METHOD FOR ROLLER BEARINGS BASED ON LCD AND LOCAL HILBERT MARGINAL ENERGY SPECTRUM

Abstract

Based on the definition of local Hilbert marginal energy spectrum,a fault feature extraction method for roller bearings is further proposed based on LCD and local Hilbert marginal energy spectrum. By using LCD,an original rolling bearing vibration signal could be adaptively decomposed into a number of intrinsic scale components（ ISC）,and then the time-frequency distribution（ TFD） could be obtained by applying Hilbert demodulation to all the components. According to the distribution of the signal energy revealed by the TFD,a local Hilbert marginal energy spectrum could be acquired once the lower and upper limit frequency for the corresponding frequency band are determined. Then the signal energy over this frequency band could be computed subsequently and regarded as the fault feature parameter. The analysis results from rolling bearing vibration signals show that the proposed approach can effectively extract the fault feature information.