Diagnosis and Fault Detection of Rotor Bars in Squirrel Cage Induction Motors Using Combined Park’s Vector and Extended Park’s Vector Approaches

The induction motor (IM) is considered to be one of the most important types motors used in industries. A sudden failure this machine can lead unwanted downtime, with consequences costs, product quality, and safety. Over last decade, several methods techniques have been proposed diagnose detect faults machines. In paper, we present development a new algorithm based on combination both Park’s vector approach (PVA) extended (EPVA) for broken rotor bars (BRBs) fault detection identification. This detected using PVA by monitoring thickness orientation park’s pattern EPVA identifying specific spectral components related fault. For ability evaluation our suggested algorithm, simulations experiments are conducted presented. obtained results demonstrate that accurate effective extensively IM detections identifications.