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. [Final Year Project] (Unpublished)

[thumbnail of Dissertation _NGUYEN CHI CUONG(15770).pdf]
Preview
PDF
Dissertation _NGUYEN CHI CUONG(15770).pdf

Download (1MB) | Preview

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
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE: Engineering > Electrical and Electronic
Depositing User: Mr 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

Actions (login required)

View Item
View Item