Bearing Fault Diagnosis Based on Optimal Time-Frequency Representation Method

Wigner-Ville Distribution (WVD) is probably the most used non-linear time-frequency distribution for signal processing in fault diagnosis, due to the advantages of excellent resolution and localization in time-frequency domain. However, the presence of cross terms when they are applied to multicomponent signals can give misleading interpretations. A methodology based on Local Mean Decomposition (LMD) and WVD is proposed to get more reliable bearing fault diagnosis based on vibration signals. Kullback-Leibler Divergence (KLD) guides the selection of the optimal frequency band with the most relevant information about the fault. Early results based on experimental data show successful diagnosis.