Experimental investigations on induction machine condition monitoring and fault diagnosis using digital signal processing techniques

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 the monitoring system are treated with different processing techniques with suitably modified algorithms to extract detailed information for machine health diagnosis. In this study, on-line analysis of the acquired signals has been performed using c(+ +), while MATLAB has been used to perform the off-line analysis. (C) 2002 Elsevier Science B.V. All rights reserved.