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Deformation measurement of flexible birdlike airfoil with optical flow

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Języki publikacji
EN
Abstrakty
EN
The application of the Lucas-Kanade (LK) optical flow technique has seen a huge success in a wide variety of fields. The goal of this paper is to apply the Lucas-Kanade technique in measuring the deformation of flexible birdlike airfoil due to steady aerodynamic loads at transitional low Reynolds-numbers with a single pixel resolution. A pyramidal scheme is used to implement a coarse-to-fine warping strategy to allow large displacements. A nonlinear structure tensor is employed to diffuse local data anisotropically to preserve discontinuities in the optical flow field. Median filtering is introduced after each iteration to remove outliers. The upper surface of the airfoil is sprayed with stochastic ink dot pattern for easy capture by two cameras observed from two different angles above the airfoil to create a pattern on the airfoil for the deformation measurement. Finally, a general result of wind tunnel experiments is selected, two optical flow fields are calculated on two images generated from each camera respectively, and the optical flow results are compared with the image correlation results.
Rocznik
Strony
173--184
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
autor
  • Northwestern Polytechnical University
autor
  • Technische Universität Braunschweig
Bibliografia
  • [1] Dial K P 1994 Report the Aerospace Profession, 38th Symposium Proceedings, The Beverly Hilton, Beverly Hills, CA
  • [2] Heathcote S and Gursul I 2007 AIAA J. 45 (5) 1066
  • [3] Biesel W, Butz H and Nachtigall W 1985 Biona-Report 3 139
  • [4] Johnson J T, Hughes S and Dam J V 2009 J. AS ME - Early Career Technical 8(1)1
  • [5] Burner A W, Fleming G A and Hoppe J C 2000 38th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, AIAA 2000-0835
  • [6] Barrows D A 2007 45th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, AIAA 2007-1163
  • [7] Horn B K P and Schunck B C 1981 Artificial Intelligence 17 185
  • [8] Lucas B and Kanade T 1981 Proc. Int. Joint Conf. Artificial Intelligence, pp. 674-679
  • [9] Bruhn A, Weickert J and Schnörr C 2005 Int. J. Computer Vision 61 (3) 211
  • [10] Baker S and Matthews I 2004 Int. J. Computer Vision 56 (3) 221
  • [11] Bouguet J 2000 Pyramidal Implementation of the Lucas Kanade Feature Tracker, OpenCV Documentation, Intel Corporation, Microprocessor Research Labs
  • [12] Soloff S M, Adrian R J and Liu Z C 1997 Meas. Sci. Technol. 8 1441
  • [13] Barron J L, Fleet D J and Beauchemin S S 1994 Int. J. Computer Vision 12 (1) 43
  • [14] Brox T and Weickert J 2002 Lecture Notes in Computer Science, Springer, Berlin, 2449 446
  • [15] Westerweel J 1993 Exp. Fluids 16 236
  • [16] Wedel A, Pock T. Zach C, Cremers D and Bischof H 2008 An Improved Algorithm for TV-Li Optical Flow, in Dagstuhl Motion Workshop
  • [17] Bansmer S. Radespiel R, Unger R, Haupt M and Horst P 2010 AIAA J. 48 (9) 1959
  • [18] Galvin B, McCane B, Novins K, Mason D and Mills S 1998 Proc. 1998 British Machine Vision Confi, Southampton, England
  • [19] Otte M and Nagel H-H 1994 Proc. Eur. Con}. Computer Vision, pp. 51-60
  • [20] Raffel M, Willert C and Kompenhans J 1998 Particle Image Velocimetry, a Practical Guide, Springer, Berlin, Heidelberg, New York, pp. 134-145
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5770f094-fda1-40e9-90e2-6588182fa986
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