• Miss. Mohini G. Fuse
• Prof. Vishal M. Pimpalkar

This research paper focuses on the investigation of detecting broken rotor faults in AC induction motors through the analysis of both electrical and vibration signals. AC motors, commonly powered by three-phase converters or industrial power supplies, may experience failures in the rotor bars, manifesting in diverse signals such as voltages and currents across the three phases. Additionally, information from acceleration and velocity signals in radial, axial, and tangential directions provides valuable insights. The experimental setup comprises a three-phase induction motor linked to a direct-current machine serving as a generator to simulate load torque. This system is interconnected through a shaft incorporating a rotating torque meter.

Machine Learning, Fault detection, Induction motor.

"REVIEW ON MACHINE LEARNING ALGORITHM FOR THE FAULT DETECTION IN ELECTRICAL SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.f890-f899, May-2024, Available :http://www.jetir.org/papers/JETIR2405600.pdf

"REVIEW ON MACHINE LEARNING ALGORITHM FOR THE FAULT DETECTION IN ELECTRICAL SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppf890-f899, May-2024, Available at : http://www.jetir.org/papers/JETIR2405600.pdf