Boosting active contours for weld pool visual tracking in automatic arc welding

Jinchao Liu; Zhun Fan; Søren Ingvor Olsen; Kim Hardam Christensen; Jens Klæstrup Kristensen

doi:10.1109/TASE.2015.2498929

Boosting active contours for weld pool visual tracking in automatic arc welding

Jinchao Liu, Zhun Fan, Søren Ingvor Olsen, Kim Hardam Christensen, Jens Klæstrup Kristensen

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16 Citationer (Scopus)

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Abstract

Detecting the shape of the non-rigid molten metal during welding, so-called weld pool visual sensing, is one of the central tasks for automating arc welding processes. It is challenging due to the strong interference of the high-intensity arc light and spatters as well as the lack of robust approaches to detect and represent the shape of the nonrigid weld pool. We propose a solution using active contours including an prior for the weld pool boundary composition. Also, we apply Adaboost to select a small set of features that captures the relevant information. The proposed method is applied to weld pool tracking and the presented results verified its feasibility.

Originalsprog	Engelsk
Tidsskrift	IEEE Transactions on Automation Science and Engineering
Vol/bind	14
Udgave nummer	2
Sider (fra-til)	1096-1108
Antal sider	13
ISSN	1545-5955
DOI	https://doi.org/10.1109/TASE.2015.2498929
Status	Udgivet - apr. 2017

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Det Natur- og Biovidenskabelige Fakultet
Image analysis
computer vision
Machine vision
Welding

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10.1109/TASE.2015.2498929

Boosting_Active_Contours_for_Weld_Pool_Visual_Tracking_in_Automatic_Arc_Welding_2017_acceptedAccepteret manuskript, 2,39 MB

Citationsformater

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AU - Fan, Zhun

AU - Olsen, Søren Ingvor

AU - Christensen, Kim Hardam

AU - Kristensen, Jens Klæstrup

PY - 2017/4

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AB - Detecting the shape of the non-rigid molten metal during welding, so-called weld pool visual sensing, is one of the central tasks for automating arc welding processes. It is challenging due to the strong interference of the high-intensity arc light and spatters as well as the lack of robust approaches to detect and represent the shape of the nonrigid weld pool. We propose a solution using active contours including an prior for the weld pool boundary composition. Also, we apply Adaboost to select a small set of features that captures the relevant information. The proposed method is applied to weld pool tracking and the presented results verified its feasibility.

KW - Faculty of Science

KW - Image analysis

KW - computer vision

KW - Machine vision

KW - Welding

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JO - IEEE Transactions on Automation Science and Engineering

JF - IEEE Transactions on Automation Science and Engineering

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ER -

Boosting active contours for weld pool visual tracking in automatic arc welding

Abstract

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