Diagnosis of subharmonic faults of large rotating machinery based on EMD

Abstract

The vibration signals always carry the abundant dynamic information of a machine and are very useful for the feature extraction and fault diagnosis. In practice, most subharmonic signals have a close relationship to time variables and can manifest large amplitude fluctuation, transient vibration, or modulation signals in time domain. In view of this, this paper describes an effective method to search the features of subharmonic faults of large rotating machinery based on empirical mode decomposition (EMD). Case study on some actual vibration signals of machine parts shows that EMD is an adaptive and unsupervised method in feature extraction and it provides an attractive alternative to the traditional diagnostic methods.