Implementation of a motor diagnosis system for rotor failure using genetic algorithm and fuzzy classification

Abstract

In this paper, the diagnosis of induction motor rotor failure with fuzzy theory and genetic algorithm is presented. The proposed method can evaluate the status of an operating motor. According to the measurement of electrical data, this research establishes the relationship of rotor failures with spectrum features. Through the learning of genetic algorithm, membership parameters can be adjusted to optimal positions. The simulation that combines fuzzy theory and a genetic algorithm has preferable diagnostic results for the rotor failures. The designed processes will be applied as a reference for building the diagnostic methods of other motor failures.