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Using Neural Network Algorithm for Bead Visualization

뉴럴 네트워크 알고리즘을 이용한 비드 가시화

  • Koo, Chang-Dae (Dept. of Automation of Industrial Installation Korea Polyteching VI College) ;
  • Yang, Hyeong-Seok (Dept. of Automation of Industrial Installation Korea Polyteching VI College) ;
  • Kim, Jung-Yeong (Korea Polyteching V College Iksan Campus) ;
  • Shin, Sang-Ho (Dept. of Bio-medical Engineering Institute TOTAL SOFT BANK LTD.)
  • 구창대 (한국폴리텍VI대학 산업설비학과) ;
  • 양형석 (한국폴리텍VI대학 산업설비학과) ;
  • 김중영 (한국폴리텍V대학 산학협력팀) ;
  • 신상호 ((주)토탈소프트뱅크 의공학연구소)
  • Received : 2013.06.14
  • Accepted : 2013.10.16
  • Published : 2013.10.31

Abstract

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

Keywords

References

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