GMAW metal transfer mode identification from welding sound

Zhao, S; Qiu, X; Burnett, I; Rigby, M; Lele, A

GMAW metal transfer mode identification from welding sound

Zhao, S

Qiu, X

Burnett, I

Rigby, M Lele, A

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Publication Type:: Conference Proceeding
Citation:: Australian Acoustical Society Annual Conference, AAS 2018, 2019, pp. 482 - 491
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Zhao, S https://orcid.org/0000-0002-6261-8864	en_US
dc.contributor.author	Qiu, X https://orcid.org/0000-0002-5181-1220	en_US
dc.contributor.author	Burnett, I https://orcid.org/0000-0003-3795-7722	en_US
dc.contributor.author	Rigby, M	en_US
dc.contributor.author	Lele, A	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Australian Acoustical Society Annual Conference, AAS 2018, 2019, pp. 482 - 491	en_US
dc.identifier.isbn	9781510877382	en_US
dc.identifier.uri	http://hdl.handle.net/10453/129926
dc.description.abstract	© 2019 Australian Acoustical Society Annual Conference, AAS 2018. All rights reserved. Gas Metal Arc Welding (GMAW) is an arc welding process that forms an electric arc between a consumable electrode and the base metal with a shielding gas to protect the arc. In GMAW, there are various metal transfer modes such as the short circuit mode, the globular mode, the spray mode, and the rotational transfer mode, which show different arc stabilities, weld pool penetrations and spatter production. Identifying the metal transfer mode is critical for process monitoring and quality control of GMAW. In this paper, a m ethod for metal transfer mode identification from the welding sound is presented. A recorder mounted on the welder helmet is used to record the sound signals generated by GMAW under different metal transfer modes, which are analysed in both time and frequency domains. New psychoacoustic parameters based on the auditory perception of an expert welder are extracted to distinguish the metal transfer modes. The Gaussian Mixture Model (GMM) is utilised to identify the metal transfer mode from the welding sound signals and a 10-fold cross validation shows 90% recognition accuracy.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP160100616
dc.relation.ispartof	Australian Acoustical Society Annual Conference, AAS 2018	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	GMAW metal transfer mode identification from welding sound	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2019 Australian Acoustical Society Annual Conference, AAS 2018. All rights reserved. Gas Metal Arc Welding (GMAW) is an arc welding process that forms an electric arc between a consumable electrode and the base metal with a shielding gas to protect the arc. In GMAW, there are various metal transfer modes such as the short circuit mode, the globular mode, the spray mode, and the rotational transfer mode, which show different arc stabilities, weld pool penetrations and spatter production. Identifying the metal transfer mode is critical for process monitoring and quality control of GMAW. In this paper, a m ethod for metal transfer mode identification from the welding sound is presented. A recorder mounted on the welder helmet is used to record the sound signals generated by GMAW under different metal transfer modes, which are analysed in both time and frequency domains. New psychoacoustic parameters based on the auditory perception of an expert welder are extracted to distinguish the metal transfer modes. The Gaussian Mixture Model (GMM) is utilised to identify the metal transfer mode from the welding sound signals and a 10-fold cross validation shows 90% recognition accuracy.

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http://hdl.handle.net/10453/129926