An Improved Weld Seam Extraction Method Using Saliency Detection for Pipe-Line Welding Based on GMAW and Passive Light

Article Preview

Abstract:

To meet the need of the automation and intelligence of welding process, it’s very important to extract the edge of weld seam accurately for seam tracking. According to the characteristics of GMAW (gas metal arc welding), an image sensing system of weld pool region based on CCD (Charge-coupled Device) is established. An improved method of weld seam extraction is presented. Firstly, weld pool region localization method using saliency detection is proposed, and weld seam region is obtained from the right edge of weld pool, then Sobel transformation and computation model is used to extract the edge of weld seam. Experimental results show that our method can obtain a more accurate weld seam edge and cost less than other method.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

160-163

Citation:

Online since:

July 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Liang Cheng, Qu Feng, Zhang Tao: Mining Technology (2010. 1), pp.59-61. In Chinese.

Google Scholar

[2] Hu H L, Li J, Li F: Applied Mechanics and Materials Vol. 130 (2012), pp.2358-2363.

Google Scholar

[3] Liu J, Fan Z, Olsen S, et al. Using active contour models for feature extraction in camera-based seam tracking of arc welding[C]/Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. IEEE, 2009: 5948-5955.

DOI: 10.1109/iros.2009.5354390

Google Scholar

[4] Goumeidane A B, Khamadja M, Nafaa N, et al. Statistical deformable model based weld defect contour estimation in radiographic inspection[C]/Computational Intelligence for Modelling Control & Automation, 2008 International Conference on. IEEE, 2008: 420-425.

DOI: 10.1109/cimca.2008.178

Google Scholar

[5] Ma H, Wei S, Sheng Z: The International Journal of Advanced Manufacturing Technology Vol. 9-12 (2010), pp.945-953.

Google Scholar

[6] Itti L, Koch C, Niebur E: IEEE Transactions on pattern analysis and machine intelligence Vol. 11 (1998), pp.1254-1259.

DOI: 10.1109/34.730558

Google Scholar