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An Adaptive Resonance Theory Neural Network (ART NN)-based fault diagnosis system: A Case Study of gas turbine system in Resak Development Platform

CUONG, NGUYEN CHI (2015) An Adaptive Resonance Theory Neural Network (ART NN)-based fault diagnosis system: A Case Study of gas turbine system in Resak Development Platform. IRC, Universiti Teknologi PETRONAS. (Unpublished)

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Abstract

The project introduces a case study of a real gas turbine system in Resak Development Platform. There are two main objectives of this project. The first objective is aimed to achieve an online fault diagnosis model using Adaptive Resonance Theorem (ART) as a considered option to avoid potential faults happen during plant system and process. The second objective is focused on a solution to improve the maintenance plan for the gas turbine system to be more economical yet still maintaining its safety level.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 27 Aug 2015 16:28
Last Modified: 25 Jan 2017 09:35
URI: http://utpedia.utp.edu.my/id/eprint/15559

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