Fault Detection and Prediction in Induction Motors
Date
2022
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Ashesi University
Abstract
Induction motors are expensive and the backbone of every industry. There would be no production when induction motors break down. It is also costly to repair them after a sudden shutdown. Industries are gradually adapting to predictive maintenance to prevent unnecessary shutdowns and reduce the cost of maintenance. The objective of this paper is to even make the predictive maintenance of inter-turn short circuit fault in induction motors more reliable by adding fault detection and deploying the entire system in an alarm and display system. In this project, secondary current data from a three-phase induction
motor has been used because of the current's capabilities of detecting a higher percentage of electrical faults. This is achieved using predictive maintenance toolbox in MATLAB.
Description
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2022cc
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Capstone Project
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Citation
Afriyie, D. (2022). Fault Detection and Prediction in Induction Motors. Ashesi University.