Vibration signal analysis using wavelet transform for isolation and identification of electrical faults in induction machine

Abstract Condition monitoring is used for increasing machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring scheme is capable of providing warning and predicting the faults at early stages. The monitoring system obtains information about the machine in the form of primary data and through the use of modern signal processing techniques; it is possible to give vital information to equipment operator before it catastrophically fails. The suitability of a signal processing technique to be used depends upon the nature of the signal and the required accuracy of the obtained information. Therefore, in this paper, signals obtained from monitoring system have been processed using wavelet transform (WT) with suitably modified algorithms to extract detailed information for induction machine fault diagnosis. The results of this investigation depict that the application of WT for processing and analysis of the vibration signal to different frequency regions in time domain improves the extraction of the information that can enhance the ability of the system for diagnosis.