Most roller bearing fault vibration signals are always multi-component amplitude-modulated and frequency-modulated (AM-FM) signals

however

the selection of central frequency of band-pass filter needs to be determined with experience in conventional envelope analysis method

which would bring demodulation error.To target this problem

a roller bearing fault diagnosis approach based on LMD (local mean decomposition) and envelope spectrum characteristics was proposed.Firstly

by using LMD method

the vibration signal of roller bearing can be decomposed into a set of product functions (PF) whose instantaneous frequencies owned physical sense and each of which was a product of an envelope signal and a purely frequency modulated signal.Secondly

spectrum analysis can be used directly to envelope signal and then the envelope spectrum can be obtained.Finally

the amplitudes ratios in different characteristic frequencies of envelope spectrum were defined as the envelope spectrum characteristics

which served as input parameters of support sector machine classifier to classify working condition and fault patterns of roller bearings.The analysis results demonstrate the effectiveness of the proposed method.