On-line detection of stator and rotor faults occurring in induction machine diagnosis by parameters estimation

The authors propose a diagnosis method for on-line interturns short-circuit windings and broken bars detection by parameters estimation. For predictive detection, Kalman filtering algorithm has been adapted to take into account the on-line parameters deviations in faulty case. Experimental rig is used to validate the on-line identification of stator default. Within the framework of the rotor defects diagnosis, it is difficult to conduct experimental tests to validate the on-line identification of such default. For this reason, one propose an on-line technique to detect rotor broken bars. This technique was validated by using a finite element software (Flux2D). Estimation results show a good agreement and demonstrate the possibility of on-line stator and rotor faults detection.