Title: An online broken bar fault detection method and its application to squirrel-cage asynchronous motors

Authors: Xing-wen Tan; Lei Zhang; Shu-qiang Liu; Xuewu Dai

Addresses: School of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China ' College of Electrical Engineering, Chongqing University, Chongqing, 400100, China ' College of Electrical Engineering, Chongqing University, Chongqing, 400100, China ' School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China

Abstract: In this paper, an improved online stator current analysis method is proposed for detecting the rotor broken bar fault of three-phase squirrel-cage asynchronous motors. With the rapid development of the advanced digital filtering technique (such as ZOOM-FFT) and the rotor slot harmonics (RSH) techniques for slip measurement, it is possible to accurately estimate a motor's slip rate from the precise measurements of the harmonic components of a rotor and the power supply frequency. This enables us to find the characteristic spectrum of a bar-broken rotor from the stator current spectrum. We proposed an online algorithm to detect the motor broken bar fault by localising and checking the existence of the fault-related characteristic spectrum. The proposed method overcomes the drawback of traditional current spectral analysis approaches. In particular, this paper addresses the problem that the side lobe spectral components are covered by the fundamental frequency and noises. This method has been validated in our experiment with a 30 kW three-phase induction motor. The experiment results show that the proposed method is able to detect small broken rotor bar fault with good application perspective.

Keywords: three-phase squirrel cage asynchronous motors; rotor broken bars; fault detection; online monitoring; ZOOM-FFT; stator current analysis; digital filtering; rotor slot harmonics; RSH; slip measurement; slip rate; side lobe spectral components.

DOI: 10.1504/IJMIC.2013.054041

International Journal of Modelling, Identification and Control, 2013 Vol.19 No.1, pp.89 - 97

Published online: 27 Sep 2014 *

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