A new detection method for broken rotor bar fault in induction motors based on WSF and BBPSO

Abstract

A new method for detecting broken rotor bar fault (BRB) in induction motors is proposed which is based on the combination of weighted subspace fitting (WSF) and bare-bones particle swarm optimization (BBPSO). In the circumstance of low signal-to-noise ratio and small snapshots data, WSF owns an excellent estimation performance, with a heavy computation. In order to improve the rapidity of WSF, BBPSO has been proposed to quickly search solutions of WSF. Performance of this new detection method is texted with the stator current signal of an induction motor with rotor fault, providing that the WSF-BBPSO-based method to detect rotor fault in induction motor is effective even with short-time sample and in low SNR environment, meanwhile compared with FFT and ESPRIT-SAA method to prove its superiority and feasibility.