Fault Detection of Rator Bar in Motors Using Machine Learning

 




 

Ang, Hooi Chen (2019) Fault Detection of Rator Bar in Motors Using Machine Learning. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

[img] Text
Ang Hooi Chen.pdf
Restricted to Registered users only

Download (3MB)

Abstract

Fault detection of induction motors is emerging rapidly in the technology of electrical maintenance and it is gaining attention in the worldwide. Fault detection technology shown that the number of unexpected failure of induction motors can be avoid by keeping awareness before the failure happened. While fault detection can be done by monitoring the output signal from the induced motor, then by using Artificial intelligent (AI) to determine the presence of fault. Thus, this project will obtained present fault detection techniques and perform analysis and hoped to set up a fault detection techniques that can be more efficient, fast and can over the limitation of the old and traditional data based methods.

Item Type: Final Year Project
Subjects: Technology > Electrical engineering. Electronics engineering
Faculties: Faculty of Engineering > Bachelor of Engineering (Honours) Electrical and Electronics
Depositing User: Library Staff
Date Deposited: 31 Jan 2020 02:34
Last Modified: 31 Jan 2020 02:34
URI: https://eprints.tarc.edu.my/id/eprint/13036