Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel

Detection of severe defects such as porosity underneath the weld bead during the welding process is vital during installation of a gas pipeline network because such defects might lead to fatigue crack. In this study, the work associated with detection of porosity through analysis of the acquired arc...

Full description

Bibliographic Details
Main Authors:	Mohd Fadhlan, Mohd Yusof, Muhammad Aizat, Kamaruzaman, M., Ishak, M. F., Ghazali
Format:	Article
Language:	English English
Published:	Springer-Verlag 2016
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/1/Porosity%20detection%20by%20analyzing%20arc%20sound%20signal%20acquired%20during%20the%20welding%20process%20of%20gas%20pipeline%20steel.pdf http://umpir.ump.edu.my/id/eprint/14543/7/fkm-2016-mishak-Porosity%20Detection%20by%20Analyzing%20Arc%20Sound%20Signal.pdf

id	ump-14543
recordtype	eprints
spelling	ump-145432017-08-23T04:19:33Z http://umpir.ump.edu.my/id/eprint/14543/ Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel Mohd Fadhlan, Mohd Yusof Muhammad Aizat, Kamaruzaman M., Ishak M. F., Ghazali TJ Mechanical engineering and machinery Detection of severe defects such as porosity underneath the weld bead during the welding process is vital during installation of a gas pipeline network because such defects might lead to fatigue crack. In this study, the work associated with detection of porosity through analysis of the acquired arc sound is presented. Air-borne acoustic signal was acquired during the metal inert gas welding process on API 5L X70 gas pipeline steel. Then, the acquired signal was analyzed using Hilbert Huang transform (HHT), which uses empirical mode decomposition for the purpose of filtering unrelated-to-damage signal components, and Hilbert spectral analysis to obtain the energy-frequency-distance plot. Results showed a significant energy amplitude pattern at the region where both surface- and subsurface-pores existed. Thus, the application of HHT analysis to the acquired arc sound signal has significantly assisted in identifying hidden information that is related to the existence of defects. This finding would enhance the development of an online welding defect detection system during the welding process. Springer-Verlag 2016 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14543/1/Porosity%20detection%20by%20analyzing%20arc%20sound%20signal%20acquired%20during%20the%20welding%20process%20of%20gas%20pipeline%20steel.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/14543/7/fkm-2016-mishak-Porosity%20Detection%20by%20Analyzing%20Arc%20Sound%20Signal.pdf Mohd Fadhlan, Mohd Yusof and Muhammad Aizat, Kamaruzaman and M., Ishak and M. F., Ghazali (2016) Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel. The International Journal of Advanced Manufacturing Technology. pp. 1-10. ISSN 0268-3768 (Print), 1433-3015 (Online) http://dx.doi.org/10.1007/s00170-016-9343-4 DOI: 10.1007/s00170-016-9343-4
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Mohd Fadhlan, Mohd Yusof Muhammad Aizat, Kamaruzaman M., Ishak M. F., Ghazali Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
description	Detection of severe defects such as porosity underneath the weld bead during the welding process is vital during installation of a gas pipeline network because such defects might lead to fatigue crack. In this study, the work associated with detection of porosity through analysis of the acquired arc sound is presented. Air-borne acoustic signal was acquired during the metal inert gas welding process on API 5L X70 gas pipeline steel. Then, the acquired signal was analyzed using Hilbert Huang transform (HHT), which uses empirical mode decomposition for the purpose of filtering unrelated-to-damage signal components, and Hilbert spectral analysis to obtain the energy-frequency-distance plot. Results showed a significant energy amplitude pattern at the region where both surface- and subsurface-pores existed. Thus, the application of HHT analysis to the acquired arc sound signal has significantly assisted in identifying hidden information that is related to the existence of defects. This finding would enhance the development of an online welding defect detection system during the welding process.
format	Article
author	Mohd Fadhlan, Mohd Yusof Muhammad Aizat, Kamaruzaman M., Ishak M. F., Ghazali
author_facet	Mohd Fadhlan, Mohd Yusof Muhammad Aizat, Kamaruzaman M., Ishak M. F., Ghazali
author_sort	Mohd Fadhlan, Mohd Yusof
title	Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
title_short	Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
title_full	Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
title_fullStr	Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
title_full_unstemmed	Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel
title_sort	porosity detection by analyzing arc sound signal acquired during the welding process of gas pipeline steel
publisher	Springer-Verlag
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/ http://umpir.ump.edu.my/id/eprint/14543/1/Porosity%20detection%20by%20analyzing%20arc%20sound%20signal%20acquired%20during%20the%20welding%20process%20of%20gas%20pipeline%20steel.pdf http://umpir.ump.edu.my/id/eprint/14543/7/fkm-2016-mishak-Porosity%20Detection%20by%20Analyzing%20Arc%20Sound%20Signal.pdf
first_indexed	2023-09-18T22:18:25Z
last_indexed	2023-09-18T22:18:25Z
_version_	1777415492939546624

Porosity Detection by Analyzing arc Sound Signal Acquired During the Welding Process of Gas Pipeline Steel

Similar Items