신경회로망을 이용한 GMAW 공정 제어

• 영문명: Process Control of Gas Metal Arc Welding using Neural Network
• 발행기관: 한국산업기술융합학회(구. 산업기술교육훈련학회)
• 저자명: 이종덕(Jong-Deog Lee) 장우영(Woo-Young Jang)
• 간행물 정보: 『산업기술연구논문지』산업기술교육훈련논문지 제16권 4호, 285~290쪽, 전체 6쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2011.12.30

영문 초록

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc light. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding rate.

목차

Ⅰ. 서 론

Ⅱ. 영상처리 알고리즘

Ⅲ. 용접공정변수 추출

Ⅳ. 실험장치 및 방법

Ⅵ. 결 론

키워드

Gas Metal Arc Welding (GMAW, 가스메탈 아크용접) Vision Sensor (비젼센서) Hough Transformation (하프변환)