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Strain Measurement Using Digital Image Correlation Method
|關鍵字:||Digital Image Correlation Method;數位影像相關法;Correlation Coefficient;Newton's Method;Strain Measurement;相關係數;牛頓法;應變量測||出版社:||機械工程學系所||引用:||1. 趙崇閔，應用數位影像相關技術於平面位移量測，國立中興大學機械工程研究所碩士學位論文，台中，2006 2. Daniel P. Nicolella, Arthur E. Nicholls, James Lankford and Dwight T. Davy, "Machine vision photogrammetry: a technique for measurement of microstructural strain in cortical bone", Journal of Biomechanics,Vol.34, pp.135-139, 2001 3. Peng Zhou and Kenneth E. Goodson, "Subpixel displacement and deformation gradient measurement using digital image/speckle correlation (DISC) ", Society of Photo-Optical Instrumentation Engineers, pp.1613, 2001 4. Zhen-De Hou and Yu-Wen Qin, "The study of fractal correlation method in the displacement measurement and its application", Optics and Lasers in Engineering, Vol.39, pp.465-472, 2003 5. Guan-Chang Jin, Zhen Wu, Ni-Keng Bao and Xue-Feng Yao, "Digital speckle correlation method with compensation technique for strain field measurements", Optics and Lasers in Engineering, Vol.39, pp.457-464, 2003 6. Jin-Long Chen, Gan-Min Xia, Ke-Bin Zhou,Gui-Suo Xia and Yu-Wen Qin, "Two-step digital image correlation for micro-region measurement", Optics and Lasers in Engineering ,Vol.43, pp.836-846, 2005 7. Bing Pan, Hui-Min Xie, Bo-Qin Xu and Fu-Long Dai, "Performance of sub-pixel registration algorithms in digital image correlation", Meas. Sci. Technol., Vol.17, pp.1615-1621, 2006 8. Yao-Feng Sun and John H.L. Pang, "Study of optimal subset size in digital image correlation of speckle pattern images", Optics and Lasers in Engineering, Vol.45, pp.967-974, 2007 9. Bing Pan, Anand Asundi, Hui-min Xie and Jian-xin Gao, "Digital image correlation using iterative least squares and pointwise least squares for displacement field and strain field measurements", Optics and Lasers in Engineering, Vol.47, pp.865-874, 2009 10. Shun-Fa Hwang, Jhih-Te Horn and Hou-Jiun Wang, "Strain measurement of SU-8 photoresist by a digital image correlation method with a hybrid genetic algorithm", Optics and Lasers in Engineering, Vol.46, pp.281-289, 2008 11. Bing Pan, Hui-min Xie , Tao Hua and Anand Asundi, "Measurement of coefficient of thermal expansion of films using digital image correlation method", Polymer Testing, Vol.28, pp.75~83, 2009 12. F. Grytten, H. Daiyan, M. Polanco-Loria and S. Dumoulin, "Use of digital image correlation to measure large-strain tensile properties of ductile thermoplastics", Polymer Testing, Vol.28, pp.653~660, 2009 13. D. Nowell and P.F.P de Matos, "Application of digital image correlation to the investigation of crack closure following overloads", Procedia Engineering, Vol.2, pp.1035~1043, 2010 14. Shih-Heng Tung , Ming-Hsiang Shih and Jui-Chao Kuo, "Application of digital image correlation for anisotropic plastic deformation during tension testing", Optics and Lasers in Engineering, Vol.48, pp.636~641, 2010 15. R. Zitoune , L. Crouzeix, F. Collombet , T. Tamine and Y.-H. Grunevald," Behaviour of composite plates with drilled and moulded hole under tensile load", Composite Structures, Vol.93, pp.2384-2391, 2011||摘要:||
Digital image correlation method is a non-contact, non-destructive optical measuring method, the principle is the second image by comparing each pixel with the first image (reference image) in the fixed point of reference pixel correlation to find images from the second image with the first reference pixel has a maximum correlation of the pixels, the point that this reference in the second pixel of the image of the corresponding points in the statistics there are several kinds of method used to calculate the correlation coefficient, used in digital image correlation method is the most common use of Pearson''s correlation coefficient for correlation matching of operations.
In this study, obtained by deformation of the surface before and after images, and image distortion as a reference image before using the digital image correlation method to find the reference image of each pixel in the deformed image of the integer corresponding to the point, and by a simple displacement equation and the brightness of the transformation model with the theory of the Newton equation of motion optimization, and then obtained through iteration after the surface displacement and strain in the deformation of sub-pixel part, and then calculate the displacement and strain by filtering the of smoothing, and then obtain the deformed surface in the global displacement field and strain field.
|Appears in Collections:||機械工程學系所|
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