An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding

An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding

Amruta Rout, Deepak BBVL, Bibhuti Bhusan Biswal, Golak Bihari Mahanta, Bala Murali Gunji
ISBN13: 9781799817543|ISBN10: 1799817547|EISBN13: 9781799817550
DOI: 10.4018/978-1-7998-1754-3.ch064
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MLA

Rout, Amruta, et al. "An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding." Robotic Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 1341-1357. https://doi.org/10.4018/978-1-7998-1754-3.ch064

APA

Rout, A., BBVL, D., Biswal, B. B., Mahanta, G. B., & Gunji, B. M. (2020). An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding. In I. Management Association (Ed.), Robotic Systems: Concepts, Methodologies, Tools, and Applications (pp. 1341-1357). IGI Global. https://doi.org/10.4018/978-1-7998-1754-3.ch064

Chicago

Rout, Amruta, et al. "An Optimal Image Processing Method for Simultaneous Detection of Weld Seam Position and Weld Gap in Robotic Arc Welding." In Robotic Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1341-1357. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1754-3.ch064

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Abstract

For robot path planning the weld seam positions need to be known in advance as the industrial robot generally work in teach and playback mode. In this paper, a vision sensor has been utilized for automation of robotic welding path planning. A seam tracking algorithm has been proposed for a butt type of weld joint with varying weld gap for effective measurement of weld path positions and weld gap simultaneously. For this first an image acquisition algorithm technique has been proposed for capturing of image of weld seam in gray scale mode. Then in image processing at first one pattern matching algorithm for tracking of weld seam path is performed. Then different edge detection techniques have been applied to find the most efficient edge detection method for obtaining the characteristics of weld seam edge. Then best edge fitting method has been applied to fit the edges along the weld seam edge and the pixel values on the edges were measured. The weld gap and the midpoint between edges points are measured simultaneously by vision assistant toolbox in LabVIEW software background.

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