Brightness-based selection and edge detection-based enhancement separation algorithm for low-resolution metal transfer images

Zhen Zhou Wang, Yuming Zhang

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Next-generation gas metal arc welding (GMAW) machines require the rapid metal transfer process be accurately monitored using a high-speed vision system and be feedback controlled. However, the necessity for high frame rate reduces the resolution achievable and bright welding arc makes it difficult to clearly image the metal transfer process. Processing of images for real-time monitoring of metal transfer process is thus challenging. To address this challenge, the authors analyzed the characteristics of metal transfer images in a novel modification of GMAW, referred to as double-electrode GMAW, and proposed an algorithm consisting of a system of effective steps to extract the needed droplet feedback information from high frame rate low-resolution metal transfer images. Experimental results verified the effectiveness of the proposed algorithm in automatically locating the droplet and computing the droplet size with an adequate accuracy.

Original languageEnglish
Article number4472180
Pages (from-to)181-187
Number of pages7
JournalIEEE Transactions on Automation Science and Engineering
Volume6
Issue number1
DOIs
StatePublished - Jan 2009

Bibliographical note

Funding Information:
Manuscript received March 28, 2007. First published March 14. 2008; current version published December 30, 2008. This paper was recommended for publication by Associate Editor Y. F. Li and Editor M. Wang upon evaluation of the reviewers’ comments. This work was supported in part by the National Science Foundation under Grant CMMI-0355324.

Keywords

  • Edge detection
  • Gas metal arc welding (GMAW)
  • Image processing
  • Interpolation
  • Machine vision
  • Metal transfer
  • Welding

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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