Bearings Fault Diagnosis Using Vibrational Signal Analysis by EMD Method

摘要

Studying vibrational signals is one reliable method for monitoring the situation of rotary machinery. There are various methods for converting vibrational signals into usable information for fault diagnosis, one of which is the empirical mode decomposition method (EMD). This article is about diagnosing bearing faults using the EMD method, employing nondestructive test. Vibration signals are acquired by a bearing test machine. The discrete wavelet bases are used to translate vibration signals of a roller bearing into time-scale representation. Then, an envelope signal can be obtained by envelope spectrum analysis of wavelet coefficients of high scales. Local Hilbert marginal spectrum can be obtained by applying thr EMD method to the envelope signal from which the faults in a roller bearing can be diagnosed and fault patterns can be identified. The results have shown bearing faults frequencies are easily observable. There is a variant of the EMD method called the ensemble EMD (EEMD), which overcomes the mode mixing problem which may occur when the signal to be decomposed is intermittent. The EEMD method is also applied to the acquired signals, and the two methods were compared. While the outcomes of both methods do not differ much, one important merit of the EMD is that it has much less computational processing time than EEMD.