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

摘要

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.