Abstract
This work addresses the online extraction of the geometry characteristics (width and centerline) of deposited beads with monocular cameras for wire arc additive manufacturing (WAAM). To enable online measurement and feature extraction from captured images, an adaptive threshold is used for segmentation, a Canny algorithm for edge detection, a Hough-line transform for feature identification of the bead edges, and a filtering step to attenuate the low signal-to-noise ratios of deposition processes. Online measurements are performed in single-bead and layer (multi-bead) scenarios. The proposed vision-based solution is experimentally implemented in a WAAM robotic system composed of a welding torch, a Kuka KR90 robot arm, a power source, wire feeder, and a passive monocular camera. Experimental results illustrate the performance and effectiveness of the proposed visual-based methodology.
Similar content being viewed by others
Notes
CMT is a modified metal inert gas welding process based on short-circuiting transfer, characterized by low heat input and no-spatter.
References
Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI, 8(6), 679–698.
Cao, Y., Zhu, S., Liang, X., & Wang, W. (2011). Overlapping model of beads and curve fitting of bead section for rapid manufacturing by robotic mag welding process. Robotics and Computer-Integrated Manufacturing, 27(3), 641–645.
Chen, S., Qiu, T., Lin, T., Wu, L., Tian, J., Lv, W., & Zhang, Y. (2004). Intelligent technologies for robotic welding. Robotic welding, intelligence and automation (pp. 123–143). Berlin: Springer.
Chen, X. Z., Chen, S. B., & Lin, T. (2007). Recognition of macroscopic seam for complex robotic welding environment. Robotic welding, intelligence and automation (Vol. 362, pp. 171–178). Berlin: Springer.
Chu, H. H., & Wang, Z. Y. (2016). A vision-based system for post-welding quality measurement and defect detection. The International Journal of Advanced Manufacturing Technology, 86, 3007–3014.
Cruz, J. G., Torres, E. M., & Absi Alfaro, S. C. (2015). A methodology for modeling and control of weld bead width in the GMAW process. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 37, 1529–1541.
Ding, D., Pan, Z., Cuiuri, D., & Li, H. (2015). A multi-bead overlapping model for robotic wire and arc additive manufacturing (WAAM). Robotics and Computer-Integrated Manufacturing, 31, 101–110.
Ding, D., Pan, Z., Cuiuri, D., & Li, H. (2015). Wire-feed additive manufacturing of metal components: technologies, developments and future interests. The International Journal of Advanced Manufacturing Technology, 81, 465–481.
Ding, D., Pan, Z., Cuiuri, D., Li, H., van Duin, S., & Larkin, N. (2016). Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing. Robotics and Computer-Integrated Manufacturing, 39, 32–42.
Ding, J., Colegrove, P., Mehnen, J., Ganguly, S., Sequeira Almeida, P., Wang, F., & Williams, S. (2011). Thermo-mechanical analysis of wire and arc additive layer manufacturing process on large multi-layer parts. Computational Materials Science, 50, 3315–3322.
Font Comas, T., Diao, C., Ding, J., Williams, S., & Zhao, Y. (2017). A passive imaging system for geometry measurement for the plasma arc welding process. IEEE Transactions on Industrial Electronics, 64(9), 7201–7209.
Gibson, I., Rosen, D. W., & Stucker, B. (2010). Additive manufacturing technologies. New York: Springer.
Pinto-Lopera, J. E., Motta, J. M. S., & Alfaro, S. C. A. (2016). Real-time measurement of width and height of weld beads in GMAW processes. Sensors (Switzerland), 16, 1–14.
Williams, S. W., Martina, F., Addison, A. C., Ding, J., Pardal, G., & Colegrove, P. (2016). Wire + arc additive manufacturing. Materials Science and Technology, 32, 641–647.
Wu, B., Pan, Z., Ding, D., Cuiuri, D., Li, H., Xu, J., & Norrish, J. (2018). A review of the wire arc additive manufacturing of metals: Properties, defects and quality improvement. Journal of Manufacturing Processes, 35, 127–139.
Wu, J., & Chen, S. B. (2007). Software system designs of real-time image processing of weld pool dynamic characteristics. Robotic welding, intelligence and automation (Vol. 362, pp. 303–309). Berlin: Springer.
Xiong, J., Zhang, G., Gao, H., & Wu, L. (2013). Modeling of bead section profile and overlapping beads with experimental validation for robotic GMAW-based rapid manufacturing. Robotics and Computer-Integrated Manufacturing, 29, 417–423.
Xiong, J., Zhang, G., Qiu, Z., & Li, Y. (2013). Vision-sensing and bead width control of a single-bead multi-layer part: Material and energy savings in GMAW-based rapid manufacturing. Journal of Cleaner Production, 41, 82–88.
Xu, Y., Fang, G., Chen, S., Zou, J. J., & Ye, Z. (2014). Real-time image processing for vision-based weld seam tracking in robotic GMAW. The International Journal of Advanced Manufacturing Technology, 73(9–12), 1413–1425.
Xu, Y., Lv, N., Fang, G., Du, S., Zhao, W., Ye, Z., & Chen, S. (2017). Welding seam tracking in robotic gas metal arc welding. Journal of Materials Processing Technology, 248, 18–30.
Li, Yuan, Li, You Fu, Wang, Qing Lin, De, Xu., & Tan, Min. (2010). Measurement and defect detection of the weld bead based on online vision inspection. IEEE Transactions on Instrumentation and Measurement, 59, 1841–1849.
Acknowledgements
An early version of this paper was presented at the XXIII Congresso Brasileiro de Automática (CBA 2020). This study was financed in part by Shell Brasil Petróleo Ltda, Empresa Brasileira de Pesquisa e Inovação Industrial (Embrapii), the National Council for Scientific and Technological Development (CNPq), and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES) Finance Code 001.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Couto, M.O., Rodrigues, A.G., Coutinho, F. et al. Mapping of Bead Geometry in Wire Arc Additive Manufacturing Systems Using Passive Vision. J Control Autom Electr Syst 33, 1136–1147 (2022). https://doi.org/10.1007/s40313-021-00880-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40313-021-00880-0