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Fault Diagnosis of Multiphase Drives Using Machine Learning

Events

Fault Diagnosis of Multiphase Drives Using Machine Learning

Time & Location:
Auditorium (G01011, KU Main Campus )
Thursday 13th June 2024 (01:30 pm – 02:00 pm)

 

Abstract

This seminar discusses the application of data-driven methods for fault diagnosis of multiphase drives, specifically the five-phase induction machine. Multiphase drives have numerous advantages over three-phase drive systems; one of them is the higher degrees of freedom or phase redundancy, making them more reliable as they require only three phases to produce a rotating magneto motive force. This seminar focuses on detecting and localizing the inverter side faults of the drive system which can be open-switch or open-phase faults. These diagnosis techniques are then used for derating the machine and reconfiguring the control for optimum operation. 

 

Biography

Hammad Hasan received his B.Sc. degree in Electrical Engineering from National University of Computer and Emerging Sciences, Islamabad, Pakistan. Currently, he is pursuing his MSc. Degree in Electrical Engineering at Khalifa University, Abu Dhabi, UAE, where he also serves as a Graduate Research and Teaching Assistant in the Department of Electrical Engineering and Computer Science. His research interests include control and fault diagnosis of drive systems.