Diagnosis of stator fault severity in induction motor based on discrete wavelet analysis

Abstract

This research puts forward a novel approach by proposing mathematical equations to estimate the fault intensity index in induction motor with stator inter-turn short circuit (ITSC) fault. Determination of the failure index is significant to create appropriate mitigation methods, as well as to define a safe working area for the motor to prevent the subsequent damage to the stator winding. Discrete Wavelet Transform (DWT) is employed to analyze the obtained raw currents in the time domain. From the detailed coefficients, the statistical parameter maximum norm has been computed under a variety of loading conditions, in addition to several fault severities. The originality of this work is to present an efficient and robust method based on new mathematical equations to detect the ITSC fault at an early level and to precisely specify the number of shorted turns in the defective phase. The methodology provides notable results, reduces computational time consumption, and simplifies the estimation process remarkably. In order to validate the efficacy of the proposed method, several experiments are conducted on the machine. The hardware experimental outcomes demonstrate the practicability and competency of the methodology, with a high level of correctness.