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Automated Inspection System for Brake Shoe of Rolling Stock  

Kim, Hyun-Cheol (Dept. of Electronics Computer Engineering, Hanyang University)
Kim, Whoi-Yul (Dept. of Electronics Computer Engineering, Hanyang University)
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Abstract
In this paper, we have proposed an automated system that accurately measures the thickness and unbalanced wear of brake shoes, and the distance between brake shoes and wheels for travelling rolling stock. The images of brake shoes are captured automatically while rolling stock is passing by an inspection station. And in order to measure the thickness, etc. the locations of brake shoes are first determined because the locations are not the same in the captured image. Toward this goal, shadow regions between the brake shoes and wheels are utilized that are common in all captured images. The boundary of the shadow regions is modeled by an second order polynomial, and constrained curve fitting method is adopted to detect a curve (the initial curve) that passes through the regions. Then, three curves that correspond to the front, back of brake shoes and wheels, and a line that passes through the vertical surface of brake shoes are detected using the initial curve and intensity change information. Finally, the thickness, etc. are calculated using the detected curves and line, and experimental results showed that the brake shoe thickness was measured with an accuracy of 0.654mm.
Keywords
brake shoe; automated inspection system; constrained curve fitting;
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  • Reference
1 http://www.intra-corp.net
2 http://www.wabco-auto.com
3 R. O. Duda and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Communications of the ACM, vol. 15, pp. 11-15, 1972   DOI
4 G. Strang, Linear Algebra and Its Applications, Brooks/Cole
5 G. Taubin, "Estimation of Planar Curves, Surfaces and Non-Planar Space Curves Defined by Implicit Equations, With Applications to Edge and Range Image Segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 11, pp. 1115-1138, 1991   DOI   ScienceOn
6 J. F. Canny, "A Computational Approach To Edge Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, pp. 679-714, 1986   DOI   ScienceOn
7 H. Sato, H. Nishii, and S. Adachi, "Automatic Thickness Measuring System by Image Processing for Brake Shoes of Traveling Rolling Stock," Kawasaki Steel Technical Report, no. 27, 1992
8 T. F. Coleman and Y. Li, "An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds," SIAM Journal on Optimization, vol. 6, pp. 418-445, 1996
9 A. Fitzgibbon, M. Pilu, and R. B. Fisher, "Direct Least Square Fitting of Ellipses," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 5, pp. 476-480, 1999   DOI   ScienceOn
10 D. W. Marquardt, "An Algorithm for Least-Squares Estimation of Nonlinear Parameters," SIAM Journal on Applied Mathematics, vol. 11, pp. 431-441, 1963   DOI   ScienceOn
11 R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 2002
12 http://www.vision.caltech.edu/bouguetj/calib_doc/
13 T. F. Coleman and Y. Li, "On the Convergence of Reflective Newton Methods for Large-Scale Nonlinear Minimization Subject to Bounds," Mathematical Programming, vol. 67, no. 2, pp. 189-224, 1994   DOI
14 G. Glogowski and J. Sawatzky, "Computer Vision Measurement of Brake Shoes for Fort Garry Industries," B.Sc. Thesis in University of Manitoba, 2006
15 J. E. Dennis, Jr., Nonlinear least squares and equations, in. The State of the Art of Numerical Analysis edited by D. Jacobs, Academic Press, pp. 269-312, 1977
16 W. Gander, G. H. Golub, and R. Strebel, "Least-Squares Fitting of Circles and Ellipses," BIT, no. 34, pp. 558-578, 1994   DOI