Defects detection using machine learning in condition monitoring

This final year project aims to make use of machine learning technique in condition monitoring for defects detection on the third rail. The machine learning model taken into consideration is the Support Vector Machine. The critical features were extracted from the data collected. This report analyse...

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Main Author:	Tan, Jian Jia
Other Authors:	See Kye Yak
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2020
Subjects:	Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	https://hdl.handle.net/10356/140159
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Institution:	Nanyang Technological University
Language:	English

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record_format	dspace
spelling	sg-ntu-dr.10356-1401592023-07-07T18:48:59Z Defects detection using machine learning in condition monitoring Tan, Jian Jia See Kye Yak School of Electrical and Electronic Engineering EKYSEE@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems This final year project aims to make use of machine learning technique in condition monitoring for defects detection on the third rail. The machine learning model taken into consideration is the Support Vector Machine. The critical features were extracted from the data collected. This report analyses how the defects detection of the third rail can be achieved by using the Support Vector Machine technique. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-27T03:12:38Z 2020-05-27T03:12:38Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140159 en A2163-191 application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	Engineering::Electrical and electronic engineering::Computer hardware, software and systems Tan, Jian Jia Defects detection using machine learning in condition monitoring
description	This final year project aims to make use of machine learning technique in condition monitoring for defects detection on the third rail. The machine learning model taken into consideration is the Support Vector Machine. The critical features were extracted from the data collected. This report analyses how the defects detection of the third rail can be achieved by using the Support Vector Machine technique.
author2	See Kye Yak
author_facet	See Kye Yak Tan, Jian Jia
format	Final Year Project
author	Tan, Jian Jia
author_sort	Tan, Jian Jia
title	Defects detection using machine learning in condition monitoring
title_short	Defects detection using machine learning in condition monitoring
title_full	Defects detection using machine learning in condition monitoring
title_fullStr	Defects detection using machine learning in condition monitoring
title_full_unstemmed	Defects detection using machine learning in condition monitoring
title_sort	defects detection using machine learning in condition monitoring
publisher	Nanyang Technological University
publishDate	2020
url	https://hdl.handle.net/10356/140159
_version_	1772826779303542784

Defects detection using machine learning in condition monitoring

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