Title

應用影像量測方法建立結構桿件之位移場與應變場

Translated Titles

Applications of Image-Based Measurements to Establish Displacement and Strain Fields of Structural Elements

DOI

10.6342/NTU201801757

Authors

葉風

Key Words

數位影像相關法 ; 影像量測 ; 非接觸式 ; 應變場 ; 位移場 ; Digital image correlation ; Image-based measurements ; Non-contact instrumentation ; Strain field ; Displacement field

PublicationName

臺灣大學土木工程學研究所學位論文

Volume or Term/Year and Month of Publication

2018年

Academic Degree Category

碩士

Advisor

張家銘

Content Language

繁體中文

Chinese Abstract

隨著現今攝影科技的進步與普及,藉由高解析度之影像獲得更多清楚的資訊已非難事,本研究即是將這些資訊蒐集、分析並運用在數位影像量測上,這種非接觸及非破壞性的量測方法,可以減少實驗裝設之感測器數量,並且能夠在佈線困難的結構如大樓、橋梁等處進行測量,不但提升量測便利性,更使量測成本大幅降低。結構桿件之位移場為其受力後位移表現,而應變場則是反映應變分佈。本研究應用皮爾森相關係數及特徵點提取,兩者皆藉由比對第二張影像中像素與前一張影像(參考影像)參考像素點的相關性,並從第二張影像中找出與前一張影像有最大相關性之位置,並計算其皮爾森相關係數或是特徵點。本研究會以這兩種方法為基礎,對已有實驗數據之結構桿件進行分析,並使用高解析度相機,並針對桿件上之感測器做位移量測。利用影像量測所得到的資料與實驗已有的位移資料進行比對,以驗證本研究位移量測方法的準確度。

English Abstract

With the advancement and popularization of the photography technology, high resolution images can yield much more information from nowadays. In this study, we collect, analyze, and apply digital image measurements to extract some structural information (e.g., deformations and strains). Digital image measurements are typically non-contact and non-destructive, and this method can measure displacements of bridges or buildings which have difficulties to instrument displacement-type sensors. To extract displacements from digital images, this study mainly applies two computer vision techniques: 1) Pearson correlation coefficients and 2) Feature points. The idea of these two techniques is to compare the pixels between two images. A reference image refers to the basis to be compared with. These two techniques basically compute the correlation of pixel points of an image with the reference image. Then, the pixels that have the greatest correlation with the reference image result in the movement of an object by calculating its Pearson correlation coefficients or feature points. This study introduces the theories of image processing and computer vision associated with digital image correlation and then analyzes the structural members in terms of displacements and strains. To construct displacement and strain fields of structural members, the LED targets, which are originally used in another optical instrumentation, namely the Krypton coordinate measurement machine, are adopted to estimate surface deformations. The estimated deformations are compared with the Krypton results, while the strains are obtained from various finite element-based methods to the calculated displacements. As found in the results, the proposed approach in this research is feasible to establish a displacement or strain field of a structural member subjected to dynamic or pseudo-dynamic loading.

Topic Category 工學院 > 土木工程學研究所
工程學 > 土木與建築工程
Reference
  1. [1] Chu T.C., Ranson W.F. and Sutton M.A. (1985), “Applications of Digital-Image Correlation Techniques to Experimental Mechanics,” Experimental Mechanics, 25(3), 232–244.
  2. [2] Vendroux G. and Knauss W.G. (1998), “Submicron Deformation Field Measurements: Part 2. Improved Digital Image Correlation,” Experimental Mechanics, 38(2), 86–92.
  3. [3] Peters W.H. and Ranson W.F. (1982), “Digital Imaging Techniques in Experimental Stress Analysis, ” Optical Engineering, 21, 427-432
  4. [4] Sutton M.A., Wolters W.J., Peters W.H., Ranson W.F. and McNeill S.R. (1983), “Determination of Displacements Using an Improved Digital Correlation Method,” Image and Vision Computing, 1, 133-139,
  5. [5] Sutton M.A., Wolters W.J., Peters W.H., Ranson W.F. and McNeill S.R. (1986), “Application of an Optimized Digital Image Correlation Method to Planar Deformation Analysis,” Image and Vision Computing, 4, 143-150.
  6. [6] Bruck H.A., McNeil S.R., Sutton M.A. and Peters W.H. (1989), “Digital Image Correlation Using Newton-Raphson Method of Partial Differential Correction,” Experimental Mechanics., 29, 261-267.
  7. [7] Sutton M.A., McNeil S.R., Jang J. and Babai M. (1988), “The Effect of Subpixel Image Restoration on Digital Image Correlation Estimates,” Optical Engineering, 27, 870-877.
  8. [8] Lu H. and Cary P.D. (2000), “Deformation Measurements by Digital Image Correlation: Implementation of Second-order Displacement Gradient,” Experimental Mechanics., 40, 393-400,
  9. [9] Bing P., Kemao Q., Huimin X. and Anand A. (2009), “Two-Dimensional Digital Image Correlation for In-Plane Displacement and Strain Measurement: a review,” Measurement Science and Technology, 20(6)
  10. [10] Blaber J., Adair B. and Antoniou A. (2005), “Ncorr: Open-Source 2D Digital Image Correlation Matlab Software,” Experimental Mechanics, 55, 1105–1122
  11. [11] Hung P.C. (1998), “Strain Analysis by Digital Image Correlation,” Ph. D.dissertation, Lehigh University.
  12. [12] Harris, C. and M. Stephens. (1988), “A Combined Corner and Edge Detector,” Proceedings of the 4th Alvey Vision Conference, 147-151.
  13. [13] Peters W.H., He Z.H., Sutton M.A. and Ranson W.F. (1984), “Two-Dimensional Fluid Velocity Measurements by Use of Digital Speckle Correlation Techniques”, Experimental Mechanics., 24, 117-121.
  14. [14] Wu W., Peters W.H. and Hammer M.E. (1987), “Basic Mechanical Properties of Retina In Simple Elongation”, Journal of Biomechanical Engineering, 109, 65-67.
  15. [15] Peters W.H., Ranson W.F., Sutton M.A., Chu T.C. and Anderson J. (1983), “Applications of Digital Correlation Methods to Rigid Body Mechanics,” Optical Engineering., 22, 738-742.
  16. [16] Han G., Sutton M.A. and Chao Y.J.. (1994), “Study of Stationary Crack-Tip Deformation Fields in Thin Sheets by Computer Vision,” Experimental Mechanics, 34, 125-140
  17. [17] Küntz M., Jolin M., Bastien J., Perez F. and Hild F. (2006), “Digital Image Correlation Analysis of Crack Behavior in a Reinforced Concrete Beam During a Load Test,” Canadian Journal of Civil Engineering, 33(11), 1418-1425.
  18. [18] Gongkang Fu, Adil G.M. (2009), “Structural Damage Diagnosis Using High Resolution Images,” Structural Safety, 23, 281-295.
  19. [19] Wahbeh A. M., John P. Caffrey and Sami F. Masri. (2003), “A Vision-Based Approach for the Direct Measurement of Displacements in Vibrating Systems,” Smart Materials and Structures, 12, 785–794.
  20. [20] Yang G. and Kui W. (2007), “Principles and Research of a High Accuracy Digital Image Correlation Measurement System,” Optical Engineering, 46(5), 051006.
  21. [21] Sun Z., Lyons J.S. and McNeill S.R. (1997), “ Measuring Microscopic Deformations with Digital Image Correlation”, Optics and Lasers in Engineering, 27, 409-428.
  22. [22] Nonis C., Niezrecki C., Yu T. , Ahmed S., Su C. and Schmidt T. (2013), “Structural Health Monitoring of Bridges using Digital Image Correlation,”  Proceedings of SPIE - The International Society for Optical Engineering, 8695. 869507.
  23. [23] Yoneyama S., Kitagawa A., Iwata S., Tani K. and Kikuta H., Bridfe. (2009), “Bridge Deflection Measurement Using Digital Image Correlation,” Materials Transactions, 53, 285-290.
  24. [24] Reagan D., Sabato A., Niezrecki C. (2017), “Feasibility of Using Digital Image Correlation for Unmanned Aerial Vehicle Structural Health Monitoring of Bridges,” An International Journal.
  25. [25] Canny J. (1986), “A Computational Approach to Edge Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679-698.
  26. [26] Lim and Jae S. (1990), “Two-Dimensional Signal and Image Processing,” Englewood Cliffs, NJ, Prentice Hall, 478-488.
  27. [27] Parker and James R. (1997), “Algorithms for Image Processing and Computer Vision,” New York, John Wiley & Sons, Inc., 23-29.