Parametric Method based Inter-Turn Incipient Short Circuit Stator Fault Detection of Induction Motor

Abstract

Objectives: The parametric method is proposed to identify the inter-turn incipient short circuit fault of induction motor. Methods/Statistical Analysis: The Parametric methods are the high resolution methods, which are used to detect the frequencies with low signal to noise (SNR) ratio using smaller number of data samples. The subspace parametric methods use the Multi-signal Classification (MUSIC) algorithm to identify the inter-turn incipient fault and its severity. The pseudo spectrum from the MUSIC algorithm estimates the frequencies related to the faulty condition of the induction motor. Findings: The frequencies which are related inter-turn short circuit fault are obtained from the pseudo spectrum and are compared with the estimated frequencies and thus it proves the estimated frequencies. Application/Improvements: The proposed algorithm is used to estimate the harmonic components from the pseudo spectrum which helps to differentiate the healthy and faulty conditions of the motors. Also the severity of the fault is identified from the pseudo spectrum.