Development of a Simulation Tool and a Monitoring System for Laser Welding Quality Inspection

레이저 용접품질 검사기법 개발을 위한 시뮬레이션 툴과 이를 이용한 감시 시스템의 개발

  • 이명수 (동명정보대학교 컴퓨터공학과) ;
  • 권장우 (동명정보대학교 컴퓨터공학과) ;
  • 길경석 (한국해양대학교 전기공학과)
  • Published : 2001.09.01

Abstract

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.