Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique

Monitoring and inspecting the health condition and state of the pipelines are significant processes for an early detection of any leaking or damages for avoiding disasters. Although most Non Destructive Test (NDT) techniques are able to detect and locate damage during the maintenance intervals, inte...

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Main Author:	Elwalwal, Hatem Mostafa
Format:	Thesis
Language:	English English English
Published:	2018
Subjects:	TA401-492 Materials of engineering and construction Mechanics of materials
Online Access:	http://eprints.uthm.edu.my/188/1/24p%20HATEM%20MOSTAFA%20ELWALWAL.pdf http://eprints.uthm.edu.my/188/2/HATEM%20MOSTAFA%20ELWALWAL%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/188/3/HATEM%20MOSTAFA%20ELWALWAL%20WATERMARK.pdf
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id	my-uthm-ep.188
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spelling	my-uthm-ep.1882021-07-06T07:54:27Z Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique 2018-04 Elwalwal, Hatem Mostafa TA401-492 Materials of engineering and construction. Mechanics of materials Monitoring and inspecting the health condition and state of the pipelines are significant processes for an early detection of any leaking or damages for avoiding disasters. Although most Non Destructive Test (NDT) techniques are able to detect and locate damage during the maintenance intervals, interrupted services could result in high cost and lots of time consumed. In addition, most NDTs are utilized to detect and locate single damage such as axial crack, circular crack, or vertical crack only. Unfortunately, these NDTs are unable to detect or localize multi-type of damages, simultaneously. In this research, the proposed method utilizes the Structural Health Monitoring (SHM) based on guided wave techniques for monitoring steel pipeline continuously in detecting and locating multi-damages. These multi damages include the circumference, hole and slopping cracks. A physical experimental works as well as numerical simulation using ANSYS were conducted to achieve the research objectives. The experimental work was performed to validate the numerical simulation. An artificial neural network was used to classify the damages into ten classes for each type of damage including circumference, hole and sloping cracks. The obtained results showed that the numerical simulation was in agreement with the experimental work with relative error of less than 1.5%. In addition, the neural network demonstrated a feasible method for classifying the damages into classes with the accuracy ranged from 75% to 82%. These results are important to provide substantial information for active condition monitoring activities. 2018-04 Thesis http://eprints.uthm.edu.my/188/ http://eprints.uthm.edu.my/188/1/24p%20HATEM%20MOSTAFA%20ELWALWAL.pdf text en public http://eprints.uthm.edu.my/188/2/HATEM%20MOSTAFA%20ELWALWAL%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/188/3/HATEM%20MOSTAFA%20ELWALWAL%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Mekanikal dan Pembuatan
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TA401-492 Materials of engineering and construction Mechanics of materials
spellingShingle	TA401-492 Materials of engineering and construction Mechanics of materials Elwalwal, Hatem Mostafa Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
description	Monitoring and inspecting the health condition and state of the pipelines are significant processes for an early detection of any leaking or damages for avoiding disasters. Although most Non Destructive Test (NDT) techniques are able to detect and locate damage during the maintenance intervals, interrupted services could result in high cost and lots of time consumed. In addition, most NDTs are utilized to detect and locate single damage such as axial crack, circular crack, or vertical crack only. Unfortunately, these NDTs are unable to detect or localize multi-type of damages, simultaneously. In this research, the proposed method utilizes the Structural Health Monitoring (SHM) based on guided wave techniques for monitoring steel pipeline continuously in detecting and locating multi-damages. These multi damages include the circumference, hole and slopping cracks. A physical experimental works as well as numerical simulation using ANSYS were conducted to achieve the research objectives. The experimental work was performed to validate the numerical simulation. An artificial neural network was used to classify the damages into ten classes for each type of damage including circumference, hole and sloping cracks. The obtained results showed that the numerical simulation was in agreement with the experimental work with relative error of less than 1.5%. In addition, the neural network demonstrated a feasible method for classifying the damages into classes with the accuracy ranged from 75% to 82%. These results are important to provide substantial information for active condition monitoring activities.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Elwalwal, Hatem Mostafa
author_facet	Elwalwal, Hatem Mostafa
author_sort	Elwalwal, Hatem Mostafa
title	Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
title_short	Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
title_full	Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
title_fullStr	Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
title_full_unstemmed	Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
title_sort	detection of multiple defects based on structural health monitoring of pipeline using guided waves technique
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Mekanikal dan Pembuatan
publishDate	2018
url	http://eprints.uthm.edu.my/188/1/24p%20HATEM%20MOSTAFA%20ELWALWAL.pdf http://eprints.uthm.edu.my/188/2/HATEM%20MOSTAFA%20ELWALWAL%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/188/3/HATEM%20MOSTAFA%20ELWALWAL%20WATERMARK.pdf
_version_	1747830549360148480

Detection of multiple defects based on structural health monitoring of pipeline using guided waves technique

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