한국생산제조학회 학술지 영문 홈페이지
[ Article ]
Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 27, No. 4, pp.363-370
ISSN: 2508-5107 (Online)
Print publication date 15 Aug 2018
Received 05 Jun 2018 Revised 20 Jul 2018 Accepted 28 Jul 2018
DOI: https://doi.org/10.7735/ksmte.2018.27.4.363

수직 GMA 용접부에서 화상처리를 위한 추출 알고리즘에 대한 연구

김창곤a ; 박민호a ; 손준식b ; 윤태종a ; 김일수a, *
Study of Extraction Algorithm for Image Processing in Vertical GMA Welding
Chang-Gon Kima ; Min-Ho Parka ; Joon-Sik Sonb ; Tae-Jong Yuna ; Ill-Soo Kima, *
aDepartment of Machanical Engineering, Mokpo National University, 1666, Yeongsan-ro, Chonggye-myon, Muan-gun, Jeonnam-do, 58579, Korea
bResearch Institute of Medium& Small Shipbuilding, 55, Daebuljugeo 3-ro, Samho-eup, Yeongam-gun, Jeonnam-do, 58457, Korea

Correspondence to: *Tel.: +82-61-454-3455 Fax: +82-61-452-6376 E-mail address: ilsookim@mokpo.ac.kr (Ill-Soo Kim).

Abstract

A welding monitoring system is indispensable for ensuring high-quality weldments in the vertical gas metal arc (GMA) process, and techniques for analyzing the arc characteristics by extracting welding arc lines from the welds are required. In this study, we have developed intelligent and effective algorithms for image processing in GMA welding based on thermal high-speed cameras. The proposed algorithms were verified and compared, to obtain the optimal one for each image-processing step. Finally, the validity of the proposed algorithms was examined using welding arc line images obtained under different welding environments. The results proved that the performance of the proposed algorithm was excellent in eliminating variable noise and extracting the feature points and centerline for vertical GMA welding, and can be employed for general industrial applications.

Keywords:

Vertical GMA welding, Welding arc, Image processing, Binarization, Feature points dectction

References

  • Liu, S. Y., Wang, G. R., Zhang, H., Jia, J. P., 2010, Design of Robot Welding Seam Tracking System With Structured Light Vision, Chinese Journal of Mechanical Engineer, 23:4 436-442.
  • Kim, I. S., Kang, B. Y., 2006, A Study on Development of Sensing System for Welding Automation, Journal of KWJS, 24:3 9-14.
  • Huang, W., Kovacevic, R., 2011, A Laser-Based Vision System for Weld Quality Inspection, Sensors 11 506-521. [https://doi.org/10.3390/s110100506]
  • Kim, H. H., Kim, I. S., Park, C. U., Son, J. S., Seo, J. H., Jung, J. W., Jeon, G. S., 2006, Development of Weld Automation Equipments Using the Infrared Temperature Sensor, Proceedings of KWJS, 46 301-303.
  • Hwang, H., Haddad, R. A., 1995, Adaptive Median Filters:New Algorithms and Results, IEEE Transactions on Image Processing, 4 499-502. [https://doi.org/10.1109/83.370679]
  • Vijaykumar, V. R., Vanathiand P. T., Kanagasabapathy, P., 2010, Fast and Efficient Algorithm to Remove Gaussian Noise in Digital Images, International Journal of Computer Science, 37 122-125.
  • Gupta, G., 2011, Algorithm for Image Processing Using Improved Median Filter and Comparison of Mean, Median and Improved Median Filter, International Journal of Soft Computing and Engineering, 1 304-311.
  • Dawood, F. A., Rahmat, R. W., Kadiman, S. B., Abdullah L. N., Zamrin, M. D., 2012, Effect Comparison of Speckle Noise Reduction Filters on 2D-Echocardigraphic Images, World Academy of Science, Engineering and Technology, 69 425-430.
  • Gil, J., Kimmel, R., 2002, Efficient Dilation, Erosion, Opening and Closing Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 24:12 1606-1617.
  • Jankowski, M., 2006, Dilation and Related Operators, Proceeding of 8th International Mathematical Symposium.
  • Otsu, N., 1979, A Threshold Selection Method from Gray-Level Histogram, IEEE Transactions on Systems, Man, and Cybernetics SMC, 9:1 62-66.
  • Greenspan, H., Laifenfeld, M., Einav, S., Barnea, O., 2001, Evaluation of Center-Line Extraction Algorithms in Quantitative Coronary Angiography, IEEE Transactions on Medical Imaging, 20:9 928-941.
  • Aichholzer, O., Aurenhammer, F., Alberts, D., Gätner, B., 1995, A Novel Type of Skeleton for Polygons, Journal of Universal Computer Science, 1:12 752-761.
  • Nobi, M. N., Yousuf, M. A., 2011, A New Method to Remove Noise in Magnetic Resonance and Ultrasound Images, Journal of Scientific Research, 3:1 81-89.
  • Gil, J., Kimmel R., 2002, Efficient Dilation, Erosion, Opening and Closing Algorithms, IEEE Transactions on PatternAnalysis and Machine Intelligence, 24:12 1606-1617.
  • Jin, B. J., Lee, J. P., Park, M. H., Kim, D. H., Wu, Q. Q., Kim, I. S., Son, J. S., 2016, A Study on Development of the Optimization Algorithms to Find the Seam Tracking, Journal of Welding and Joining 34:2 59-66.
  • Sahoo, P. K., Soltani, S., Wongand A. K. C., Chen, Y., 1988, A Survey of Thresholding Techniques, Comput. Graph Image Process 41 233-260. [https://doi.org/10.1016/0734-189X(88)90022-9]
  • Harris. C., Stephens, M., 1988, A Combined Corner and Edge Detector, Fourth Alvey Vision Conference, 147-152. [https://doi.org/10.5244/C.2.23]
  • Tomasi, C., Kanade, T., 1991, Detection and Tracking of Point Features, Carnegie Mellon University Technizal Report CMU-CS, 91-132.