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Detection of Noncircularity and Eccentricity of a Rolling Winder by Artificial Vision

Abstract

A common objective in the web transport industry is to increase the velocity as much as possible. Some disturbances drastically limit this velocity. Time-varying eccentricity of the rolling winder is one of the major disturbances which affect the quality of the rolling winder. This unsuitable factor can lead to a web break for a high-speed winding process. The main contribution of this work is to offer a new measurement technique that is able to provide on-line the estimation of the roll radius and its variations with a subpixel accuracy. A key feature within this work is the contour curvature classification by means of wavelets decomposition of the edge orientation function. We also propose a new model accounting for the increasing radius of the rolling winder, which confirms the experimental results and the reliability of the proposed approach.

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Correspondence to Christophe Doignon.

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Doignon, C., Knittel, D. Detection of Noncircularity and Eccentricity of a Rolling Winder by Artificial Vision. EURASIP J. Adv. Signal Process. 2002, 497390 (2002). https://doi.org/10.1155/S111086570220308X

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Keywords

  • shape-preserved filtering
  • curvature analysis
  • wavelets decomposition
  • contours classification
  • ellipse fitting
  • pose from ellipse