Data-Driven Robust Fault Detection and Isolation of Three-Phase Induction Motor

This paper deals with data-driven fault diagnosis of three-phase induction motor. The tools from subspace identification based data-driven scheme are utilized to design a framework of fault detection and isolation. The fault detection scheme is so designed that it caters for even small magnitude faults. In order to discriminate different faults, a fault isolation algorithm is proposed. Isolation thresholds are designed. The results show the effectiveness of the proposed schemes.