Application of Local Mean Mode Decomposition in Bearing Fault Diagnosis

摘要

The LMMD method is faster and more efficient than EMD; we proposed a new criterion for the sifting process to stop, it is better for the signal to decompose. We calculated the AIF and ER of the IMFs, which can describe the feature of the signal properly. What's more, The PPNN is fast, sample and precise. We analyzed the rolling bearing signal, and proved this method is high efficiently for processing the bearing signal, which can be used in the fault diagnosis.