Inter-turn short circuit detection based on modulation signal bispectrum analysis of motor current signals

Motor current signature analysis (MCSA) is a common practice in industry for finding motor faults. However, because of small modulations caused by faults and high noise contamination, it is difficult to quantify the modulation in measured signals which is dominated by the supply frequency, higher order harmonics and noise. In this paper a modulation signal bispectrum (MSB) is investigated to detect stator winding faults. This type of fault can cause high winding temperatures which may effect on current signal so motor temperature will be considered in this paper. The results show that MSB has the capability to accurately estimate modulation degrees and suppress the random and non-modulation components. The test results show that MSB has a better performance in differentiating spectrum amplitudes due to stator faults, and hence produces better diagnosis performance, compared with that of conventional power spectrum analysis.