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Narrow-seam identification and deviation detection in keyhole deep-penetration TIG welding

  • Baori Zhang
  • Yonghua ShiEmail author
  • Shengyong Gu
ORIGINAL ARTICLE
  • 52 Downloads

Abstract

A narrow-seam identification algorithm is developed to achieve seam tracking in keyhole deep-penetration tungsten inert gas welding (TIG). The welding images are captured by a high-dynamic-range camera and denoised by a bilateral filter based on a noise model analysis. The arc area is extracted as a fixed region of interest. Then, an improved Otsu algorithm and a parabolic fitting algorithm are used to obtain the centerline of the arc. The seam area is extracted as an adaptive region of interest based on a proposed HOG+LBP algorithm. Thereafter, a continuous single-pixel edge contour is extracted by the canny algorithm, and a proposed contour curvature evaluation method is used to obtain the corresponding pixel coordinates. After testing and analysis, the deviation can be reliably detected with an average measurement error within ± 0.04 mm. As a result, the algorithm proposed in this study can accurately identify the deviation during keyhole deep-penetration TIG welding, and has application prospects in the narrow-seam welding field.

Keywords

Keyhole deep penetration TIG welding Narrow seam tracking Adaptive region of interest Curvature evaluation method 

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Notes

Funding information

This study is financially supported from the Science and Technology Planning Project of Guangdong Province (grant no. 2015B010919005) and the Science and Technology Planning Project of Guangzhou City (grant no. 201604046026, 201510010230).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.Guangdong Provincial Engineering Research Center for Special Welding Technology and EquipmentSouth China University of TechnologyGuangzhouChina

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