Monitoring and Quality Control of Stud Welding

This study is conducted to carry out a straightforward way appropriate for quality monitoring and stability of arc stud welding process, followed by a number of procedures to control the quality of welded samples, namely torque destructive testing and visual inspection context. Those procedures were...

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Autores principales:	Saif Ghazy Faisal Ibrahim, Hussam K. Abdul Ameer, Nabeel K. Abid Al-Sahib
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2009
Materias:	(Arc stud welding Current peak value Electronic Welding monitoring system Stud welding torque test Neural Networks) Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/9d588cf227b94bf48863f2f43a38d9c6
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spelling	oai:doaj.org-article:9d588cf227b94bf48863f2f43a38d9c62021-12-02T07:39:27ZMonitoring and Quality Control of Stud Welding1818-1171https://doaj.org/article/9d588cf227b94bf48863f2f43a38d9c62009-01-01T00:00:00Zhttp://www.iasj.net/iasj?func=fulltext&aId=2272https://doaj.org/toc/1818-1171This study is conducted to carry out a straightforward way appropriate for quality monitoring and stability of arc stud welding process, followed by a number of procedures to control the quality of welded samples, namely torque destructive testing and visual inspection context. Those procedures were being performed to support the monitoring system and verify its validity. Thus, continuous on-line monitoring guarantees earlier discovering stud welding defects and avoiding weld repeatability. On-line welding electronic monitoring system is for non destructive determining if a just completed weld is satisfactory or unsatisfactory, depending on welding current peak value detected by the system. Also, it has been observed significant harmonize which is mutually linking the monitored current peak values and quality control measures. So this concept is accordingly contributed in the process of supporting the fundamental objective of this research. On the other hand, two feed-forward neural networks have been developed for monitoring and control arc stud welding quality. First network predicts two output quality parameters (current peak value) and (torque testing value at failure). Second, predicts one output quality parameter (visual inspection). Networks have been trained to a set of data, which made them ready to receive new information for subsequent quality parameters prediction. Both networks showed up good response and acceptable resultsSaif Ghazy Faisal IbrahimHussam K. Abdul AmeerNabeel K. Abid Al-SahibAl-Khwarizmi College of Engineering – University of Baghdadarticle(Arc stud weldingCurrent peak valueElectronic Welding monitoring systemStud welding torque testNeural Networks)Chemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 5, Iss 1, Pp 53-70 (2009)
institution	DOAJ
collection	DOAJ
language	EN
topic	(Arc stud welding Current peak value Electronic Welding monitoring system Stud welding torque test Neural Networks) Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	(Arc stud welding Current peak value Electronic Welding monitoring system Stud welding torque test Neural Networks) Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Saif Ghazy Faisal Ibrahim Hussam K. Abdul Ameer Nabeel K. Abid Al-Sahib Monitoring and Quality Control of Stud Welding
description	This study is conducted to carry out a straightforward way appropriate for quality monitoring and stability of arc stud welding process, followed by a number of procedures to control the quality of welded samples, namely torque destructive testing and visual inspection context. Those procedures were being performed to support the monitoring system and verify its validity. Thus, continuous on-line monitoring guarantees earlier discovering stud welding defects and avoiding weld repeatability. On-line welding electronic monitoring system is for non destructive determining if a just completed weld is satisfactory or unsatisfactory, depending on welding current peak value detected by the system. Also, it has been observed significant harmonize which is mutually linking the monitored current peak values and quality control measures. So this concept is accordingly contributed in the process of supporting the fundamental objective of this research. On the other hand, two feed-forward neural networks have been developed for monitoring and control arc stud welding quality. First network predicts two output quality parameters (current peak value) and (torque testing value at failure). Second, predicts one output quality parameter (visual inspection). Networks have been trained to a set of data, which made them ready to receive new information for subsequent quality parameters prediction. Both networks showed up good response and acceptable results
format	article
author	Saif Ghazy Faisal Ibrahim Hussam K. Abdul Ameer Nabeel K. Abid Al-Sahib
author_facet	Saif Ghazy Faisal Ibrahim Hussam K. Abdul Ameer Nabeel K. Abid Al-Sahib
author_sort	Saif Ghazy Faisal Ibrahim
title	Monitoring and Quality Control of Stud Welding
title_short	Monitoring and Quality Control of Stud Welding
title_full	Monitoring and Quality Control of Stud Welding
title_fullStr	Monitoring and Quality Control of Stud Welding
title_full_unstemmed	Monitoring and Quality Control of Stud Welding
title_sort	monitoring and quality control of stud welding
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2009
url	https://doaj.org/article/9d588cf227b94bf48863f2f43a38d9c6
work_keys_str_mv	AT saifghazyfaisalibrahim monitoringandqualitycontrolofstudwelding AT hussamkabdulameer monitoringandqualitycontrolofstudwelding AT nabeelkabidalsahib monitoringandqualitycontrolofstudwelding
_version_	1718399296857964544

Monitoring and Quality Control of Stud Welding

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