On-line seam detection in rolling processes using snake projection and discrete wavelet transform

Jing Li, Jianjun Shi, Tzyy Shuh Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an on-line quality inspection method to detect seam, a major type of surface defect generated in rolling processes. A feature-preserving snake-projection procedure is first adopted to convert the images of suspect seams to one-dimensional sequences. Discrete Wavelet Transform is then performed on the derived sequences with features extracted from wavelet coefficients. Finally, T 2 control chart is established to discriminate between real seams and false positives. Minimization of the discrimination error based on training data is also presented with illustrations. On-line implementation of the proposed method shows that it satisfies the requirements of both detection accuracy and detection speed.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Manufacturing Science and Engineering
Volume2006
StatePublished - 2006
Externally publishedYes
EventInternational Conference on Manufacturing Science and Engineering, MSEC 2006 - Ypsilanti, MI, United States
Duration: Oct 8 2006Oct 11 2006

Other

OtherInternational Conference on Manufacturing Science and Engineering, MSEC 2006
CountryUnited States
CityYpsilanti, MI
Period10/8/0610/11/06

Keywords

  • Dimension reduction
  • Discrete wavelet transforms (DWT)
  • Feature extraction
  • Seam detection
  • T control chart

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Li, J., Shi, J., & Chang, T. S. (2006). On-line seam detection in rolling processes using snake projection and discrete wavelet transform. In Proceedings of the International Conference on Manufacturing Science and Engineering (Vol. 2006)