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In-situ Online Measurement of Rhombic Distortion in Billets

Received: 5 July 2019    Accepted: 26 July 2019    Published: 28 May 2020
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Abstract

DD (diagonal-difference) is considered as measure of rhombic distortion, aka Rhomboidity, which is a shape related defect in square cross-section billets. Rhomboidity in billets starts with non-uniform shell solidification in the mold primarily due to inconsistent cooling causing irregular heat transfer. The higher diagonal difference greatly impacts the quality of billets to be rolled at various mills. Rhomboidity at or over 4% leads to billet twisting in the roughing stands of the rolling mill. Currently, billet rhomboidity is measured manually at end of casting operation. The presented work describes an optical, online & real-time image processing based method to determine the rhomboidity induced in each strand and alerts the operator to take corrective actions. The online Rhomboidity Measurement System employs sophisticated image acquisition & processing techniques to determine face contours of the billet with sub-pixel accuracy. The key features of RMS are the construction of a gaussian penalty function for selection of suitable 4-lines combination that precisely fits the billet face and use of a highly efficient and accurate statistical indicator, based on KL-Divergence measure, to estimate the rhomboidity even in presence of partial occlusion of billet face by scales. The expected savings are to the tune of 0.27 Million USD.

Published in Engineering Science (Volume 5, Issue 2)
DOI 10.11648/j.es.20200502.11
Page(s) 10-16
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Rhombic Distortion in Billets, Shape Defects in Continuous Casting, Quadrilateral Detection, Hough Transform, Gaussian Penalty Function, KL-divergence Measure

References
[1] V. Samarasekera & J. K. Brimacombe, The influence of mold behavior on the production of continuously cast steel billets. Metallurgical Transactions B, March 1982, Volume 13, Issue 1, pp 105–116.
[2] S. Kumar, J. A. Meech, I. V. Samarasekera, J. K. Brimacombe & V. Racosevic, Development of intelligent mould for online detection of defects in steel billets. Ironmaking & Steelmaking – Process, Product & Application, Volume-26, pp 269-284.
[3] Kegham M. Markarian & Robert Sobolewski (1981), Distortion measurement in casting, US Patent US4538669A.
[4] Markus Schmid & Adolf Fuchs (1975). Apparatus for measuring the geometry of the hollow mold compartment of continuous casting molds, US Patent US4087918A.
[5] P. V. C. Hough. Method and means for recognizing complex patterns, US Patent 3069654.
[6] Richard O. Duda and Peter E. Hart. Use of the hough transformation to detect lines and curves in pictures. Commun. ACM, 15 (1): 11–15, January 1972.
[7] D. H. Ballard. Generalizing the hough transform to detect arbitrary shapes. pages 714–725, 1987.
[8] John Canny. A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PAMI-8 (6): 679–698, Nov. 1986.
[9] S. Kullback, Information theory and statistics, Dover Publications, New York, 1968.
[10] K. Weinberger, J. Blitzer, and L. Saul, Distance metric learning for large margin nearest neighbor classification, in Proc. NIPS, Y. Weiss, B. Scho¨lkopf, and J. Platt, Eds. Cambridge, MA: MIT Press, 2006, pp. 1475–1482.
[11] Daniel C. Cole, Reinvestigation of the thermodynamics of blackbody radiation via classical physics, Phys. Rev. A 45, 8471 – Published 1 June 1992.
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  • APA Style

    Prabal Patra, Ashish Tiwari, Punit Rathore. (2020). In-situ Online Measurement of Rhombic Distortion in Billets. Engineering Science, 5(2), 10-16. https://doi.org/10.11648/j.es.20200502.11

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    ACS Style

    Prabal Patra; Ashish Tiwari; Punit Rathore. In-situ Online Measurement of Rhombic Distortion in Billets. Eng. Sci. 2020, 5(2), 10-16. doi: 10.11648/j.es.20200502.11

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    AMA Style

    Prabal Patra, Ashish Tiwari, Punit Rathore. In-situ Online Measurement of Rhombic Distortion in Billets. Eng Sci. 2020;5(2):10-16. doi: 10.11648/j.es.20200502.11

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  • @article{10.11648/j.es.20200502.11,
      author = {Prabal Patra and Ashish Tiwari and Punit Rathore},
      title = {In-situ Online Measurement of Rhombic Distortion in Billets},
      journal = {Engineering Science},
      volume = {5},
      number = {2},
      pages = {10-16},
      doi = {10.11648/j.es.20200502.11},
      url = {https://doi.org/10.11648/j.es.20200502.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.es.20200502.11},
      abstract = {DD (diagonal-difference) is considered as measure of rhombic distortion, aka Rhomboidity, which is a shape related defect in square cross-section billets. Rhomboidity in billets starts with non-uniform shell solidification in the mold primarily due to inconsistent cooling causing irregular heat transfer. The higher diagonal difference greatly impacts the quality of billets to be rolled at various mills. Rhomboidity at or over 4% leads to billet twisting in the roughing stands of the rolling mill. Currently, billet rhomboidity is measured manually at end of casting operation. The presented work describes an optical, online & real-time image processing based method to determine the rhomboidity induced in each strand and alerts the operator to take corrective actions. The online Rhomboidity Measurement System employs sophisticated image acquisition & processing techniques to determine face contours of the billet with sub-pixel accuracy. The key features of RMS are the construction of a gaussian penalty function for selection of suitable 4-lines combination that precisely fits the billet face and use of a highly efficient and accurate statistical indicator, based on KL-Divergence measure, to estimate the rhomboidity even in presence of partial occlusion of billet face by scales. The expected savings are to the tune of 0.27 Million USD.},
     year = {2020}
    }
    

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    AU  - Prabal Patra
    AU  - Ashish Tiwari
    AU  - Punit Rathore
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    DO  - 10.11648/j.es.20200502.11
    T2  - Engineering Science
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    JO  - Engineering Science
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.es.20200502.11
    AB  - DD (diagonal-difference) is considered as measure of rhombic distortion, aka Rhomboidity, which is a shape related defect in square cross-section billets. Rhomboidity in billets starts with non-uniform shell solidification in the mold primarily due to inconsistent cooling causing irregular heat transfer. The higher diagonal difference greatly impacts the quality of billets to be rolled at various mills. Rhomboidity at or over 4% leads to billet twisting in the roughing stands of the rolling mill. Currently, billet rhomboidity is measured manually at end of casting operation. The presented work describes an optical, online & real-time image processing based method to determine the rhomboidity induced in each strand and alerts the operator to take corrective actions. The online Rhomboidity Measurement System employs sophisticated image acquisition & processing techniques to determine face contours of the billet with sub-pixel accuracy. The key features of RMS are the construction of a gaussian penalty function for selection of suitable 4-lines combination that precisely fits the billet face and use of a highly efficient and accurate statistical indicator, based on KL-Divergence measure, to estimate the rhomboidity even in presence of partial occlusion of billet face by scales. The expected savings are to the tune of 0.27 Million USD.
    VL  - 5
    IS  - 2
    ER  - 

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Author Information
  • Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India

  • Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India

  • Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India

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