Development of a detection and classification method for induction motor faults using Motor Current Signature Analysis and Feedforward Neural Network / Felicity Bulan Leo Uchat
In this thesis, a predictive maintenance method for the development of adetection and classification method for comprehensive fault conditions in induction motors (IM) is proposed. Induction motors are taken into account because they are commonly utilized in industrial and commercial plants worldwid...
Saved in:
Main Author: | Leo Uchat, Felicity Bulan |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | https://ir.uitm.edu.my/id/eprint/14493/1/TD_FELICITY%20BULAN%20LEO%20UCHAT%20EE%2016_5.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Digital neuron integrated circuit design for Feedforward Neural Network using Silterra 0.13 micrometer technology / Mohamad Faiz Omar Mahmud
by: Mahmud, Mohamad Faiz Omar
Published: (2012) -
Dynamic unsupervised feedforward neural network clustering /
by: Asadi, Roya
Published: (2016) -
Economic dispatch prediction for power generation using artificial neural networks / Ahmad Radzi Sabtu
by: Sabtu, Ahmad Radzi
Published: (2012) -
Artificial neural network sediment transport model for Sungai Bernam / Muhammad Syahreen Sa'adon
by: Sa'adon, Muhammad Syahreen
Published: (2008) -
Character recognition of Malaysian license tender plate number using neural network / Izzwan Ishak
by: Ishak, Izzwan
Published: (2007)