Inter-turn short-circuit fault diagnosis using robust adaptive parameter estimation

This paper presents a robust adaptive parameter estimation procedure, applied to stator inter-turn short-circuit (ITSC) fault detection in induction motors (IM). Using a fault state space model, it is proposed the application of an adaptive parameter estimation methodology, used to identify a parameter related to the failure severity. A linear parameter varying (LPV) robust H∞ filtering technique, obtained by linear matrix inequalities (LMI), is applied to estimate the unavailable states, being the proposed method robust to external disturbances, and also adequate to online applications. The proposed framework is validated through simulations and experimental tests — conducted in a modified IM that allows the emulation of ITSC faults. Tests are performed under several operational conditions, including different levels of fault severity, load torque and voltage unbalance, demonstrating the validity of the ITSC fault detection approach.