Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
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Classification of Surface Defects on Cold Rolled Strip by Tree-Structured Neural Networks

트리구조 신경망을 이용한 냉연 강판 표면 결함의 분류

  • 문창인 (서울산업대학교 산업대학원 메카트로닉스학과) ;
  • 최세호 (POSCO기술연구소, 서울산업대학교) ;
  • 김기범 (POSCO기술연구소, 서울산업대학교) ;
  • 주원종 (서울산업대학교 기계설계자동화)
  • Published : 2007.06.01
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Abstract

A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

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References

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