Electrical Fault Detection and Diagnosis of Induction Motor using Fuzzy Logic *V. P. Mini, **S. Ushakumari, Department of Electrical Engineering, College of Engineering Trivandrum, Kerala, 695 016, INDIA * vpminicet@yahoo.in, ** ushalal2002@yahoo.com Abstract Induction motors are critical components in many industrial processes and online monitoring of the parameters of these high capacity induction motors is becoming increasingly important. The motor experiences different type of faults, like electrical faults, mechanical faults etc. Objective of the paper is to study the effects of various types of electrical faults such as stator winding faults and external faults. It is also proposed to formulate fuzzy inference algorithms for detecting various faults and analyzing their severity. The mathematical model of three phase induction motor, under healthy condition is taken as the reference for fault detection and analysis. The asymmetrical induction motor model is used for inter-turn short circuit fault detection. For the earth fault and external fault detection, the symmetrical induction motor model is used. In this work, fuzzy logic inference algorithms are used to formulate decisions about the motor condition with high degree of accuracy. Key words Induction Motor, Electrical fault, Modeling, Fuzzy logic, Fault detection and diagnosis. 1. Introduction Three phase induction motor is popular in industries due to the simple construction, high reliability, low cost etc. Because of costly repair, external process down time, health and safety problem are the areas focusing attention for fault detection and predictive maintenance strategies for an industrial plant. For the past 25 years, substantial amounts of research have been carried out for the formulation of new condition monitoring techniques for induction motor drives. Some fault analysis methods for single phase and three phase induction motors are given by M. Chow et al. (1991) and F. Filippetti et al. (1993). The induction motor faults are categorised into three viz. internal, external and environmental related faults. Electrical and mechanical faults are the two