The application of wavelets for the detection of inter-turn faults in induction machines

The most popular methods of induction machine condition monitoring utilize the steady-state spectral components of the stator quantities. These stator spectral components can include voltage, current and power and are used to detect turn faults, broken rotor bars, bearing failures and air gap eccentricities. Presently, many techniques that are based on steady-state analysis are being applied to induction machines. However, induction motors are not always operating under complete steady state conditions, therefore prompting the development of non-stationary techniques for fault detection. In this paper, it will be shown how the steady-state fault detection technique, Extended park's vector approach (EPVA), can be improved to detect inter-turn faults during transients by incorporating the discrete wavelet transform (DWT) to the detection scheme. The new technique shows that stator turn faults can be unambiguously detected under transient conditions.