A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION

The development of underground pipeline plays a vital role in the advancement of the oil and gas industry in Malaysia and worldwide. Most existing pipelines are aged and tend to fail due to external and internal factors. Material fatigue, sudden changes in pipeline pressure or other critical factors...

Full description

Main Author: MOHD JAAFAR, NUR SYAKIRAH
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.20501 /
Published: 2019
Subjects:
T Technology (General)
Online Access: http://utpedia.utp.edu.my/20501/1/Nur%20Syakirah%20binti%20Mohd%20Jaafar_16001470.pdf
http://utpedia.utp.edu.my/20501/
Tags: Add Tag
No Tags, Be the first to tag this record!
id utp-utpedia.20501
recordtype eprints
spelling utp-utpedia.205012021-08-30T16:31:41Z http://utpedia.utp.edu.my/20501/ A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION MOHD JAAFAR, NUR SYAKIRAH T Technology (General) The development of underground pipeline plays a vital role in the advancement of the oil and gas industry in Malaysia and worldwide. Most existing pipelines are aged and tend to fail due to external and internal factors. Material fatigue, sudden changes in pipeline pressure or other critical factors lead to failure in pipelines and their material properties, impact on environmental conditions, and excessive internal and external loads. When the pipeline starts to deteriorate through mechanisms such as leakage, it is regarded as experiencing failure. Due to the rapid increase of spending on pipeline leak detection for the oil and gas industry, it is a challenging task to study the ways in which information from the time–frequency analysis of signal processing is communicated about leakages in pipelines. 2019-10 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20501/1/Nur%20Syakirah%20binti%20Mohd%20Jaafar_16001470.pdf MOHD JAAFAR, NUR SYAKIRAH (2019) A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic T Technology (General)
spellingShingle T Technology (General)
MOHD JAAFAR, NUR SYAKIRAH
A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
description The development of underground pipeline plays a vital role in the advancement of the oil and gas industry in Malaysia and worldwide. Most existing pipelines are aged and tend to fail due to external and internal factors. Material fatigue, sudden changes in pipeline pressure or other critical factors lead to failure in pipelines and their material properties, impact on environmental conditions, and excessive internal and external loads. When the pipeline starts to deteriorate through mechanisms such as leakage, it is regarded as experiencing failure. Due to the rapid increase of spending on pipeline leak detection for the oil and gas industry, it is a challenging task to study the ways in which information from the time–frequency analysis of signal processing is communicated about leakages in pipelines.
format Thesis
author MOHD JAAFAR, NUR SYAKIRAH
author_sort MOHD JAAFAR, NUR SYAKIRAH
title A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
title_short A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
title_full A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
title_fullStr A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
title_full_unstemmed A HYBRID FOURIER TRANSFORM -EMPIRICAL MODE DECOMPOSITION MODEL FOR LEAKAGE DETECTION
title_sort hybrid fourier transform -empirical mode decomposition model for leakage detection
publishDate 2019
url http://utpedia.utp.edu.my/20501/1/Nur%20Syakirah%20binti%20Mohd%20Jaafar_16001470.pdf
http://utpedia.utp.edu.my/20501/
_version_ 1741195628121161728
score 11.62408

Similar Items