Revision of Bearing Fault Characteristic Spectrum Using LMD and Interpolation Correction Algorithm

Abstract

The fault spectral precision plays a significant role in the field of mechanical diagnosis. A bearing fault characteristic spectrum revised approach based on local mean decomposition (LMD) and interpolation correction theory is proposed. Bearing fault vibration signal belongs to multi-component modulated AM-FM signals, the LMD method can decompose this fault vibration signals into a number of different characteristic time scales product functions (PFs), then the spectrum analysis method is applied to the first PF1 component and the instantaneous frequencies and instantaneous amplitudes are obtained. However, in order to acquire accurate frequency and amplitude information and overcome the drawbacks such as energy leakage and fence effect, interpolation correction algorithm is introduced to the characteristic spectrum. The experimental results show that this method can effectively diagnose the bearing fault and accurately extract the characteristic spectrum information of bearing vibration signals and it has very high engineering application value.