A case study on the comparison of non-parametric spectrum methods for broken rotor bar fault detection

Abstract

Broken rotor bars in an induction motor create asymmetries and result in abnormal amplitude of the sidebands around the fundamental supply frequency and its harmonics. Applying a spectrum analysis technique on motor current and inspecting the spectrum amplitudes at the broken rotor bar specific frequencies for abnormality is a well-known procedure for broken rotor bar fault detection and diagnosis. Among the spectrum analysis techniques for broken rotor bar fault detection, the fast Fourier transform (FFT) is the most widely used technique. There are other spectrum techniques, which are based on the power spectral density estimates. In this paper we compare the three well-known spectrum analysis methods: FFT, periodogram and Welch's periodogram methods according to their performance on the broken rotor bar fault detection problem. The results indicate that Welch's periodogram method has better fault discrimination capability and is more robust compared to the other two methods. A statistical hypothesis test applied to the results of the three methods depicts the comparison results quantitatively.