On Line Fault Identification of Induction Motor using Fuzzy System

It is well known that Induction motors are used worldwide as the “workhorse” in industrial applications. Although, these electromechanical devices are highly reliable, they are susceptible to many types of faults. Such fault can become catastrophic and cause production shutdowns, personal injuries and waste of raw material. However, induction motor faults can be detected in an initial stage in order to prevent the complete failure of an induction motor and unexpected production costs. The motive of this project is to analyse the fault in induction motor through sound and electrical signature produced during the specific fault existing in the induction motor and then to analyse it through various technique. In this paper, a method for mechanical and electrical fault diagnosis in induction motor through sound and electrical signature analysis has been proposed. The work reported in this project uses noninvasively method for sound signature for diagnosing different mechanical faults. For the electrical fault diagnosis the current signature of 3-phase induction motor has been recorded. The recorded sound signature and current signature of the faulty induction motor and a healthy induction motor during different faults have been analysed using Fourier transform. The magnitude and frequency of FFT of these signatures have been used for identification of different faults using fuzzy system. Keywords—Induction motor, fuzzy logic