In-situ Online Measurement of Rhombic Distortion in Billets
Volume 5, Issue 2, June 2020, Pages: 10-16
Received: Jul. 5, 2019;
Accepted: Jul. 26, 2019;
Published: May 28, 2020
Views 82 Downloads 33
Prabal Patra, Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India
Ashish Tiwari, Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India
Punit Rathore, Instrumentation & Control, Automation Division, Tata Steel Jamshedpur, India
Follow on us
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.
Rhombic Distortion in Billets, Shape Defects in Continuous Casting, Quadrilateral Detection, Hough Transform, Gaussian Penalty Function, KL-divergence Measure
To cite this article
In-situ Online Measurement of Rhombic Distortion in Billets, Engineering Science.
Vol. 5, No. 2,
2020, pp. 10-16.
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
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.
Kegham M. Markarian & Robert Sobolewski (1981), Distortion measurement in casting, US Patent US4538669A.
Markus Schmid & Adolf Fuchs (1975). Apparatus for measuring the geometry of the hollow mold compartment of continuous casting molds, US Patent US4087918A.
P. V. C. Hough. Method and means for recognizing complex patterns, US Patent 3069654.
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.
D. H. Ballard. Generalizing the hough transform to detect arbitrary shapes. pages 714–725, 1987.
John Canny. A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PAMI-8 (6): 679–698, Nov. 1986.
S. Kullback, Information theory and statistics, Dover Publications, New York, 1968.
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.
Daniel C. Cole, Reinvestigation of the thermodynamics of blackbody radiation via classical physics, Phys. Rev. A 45, 8471 – Published 1 June 1992.