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DIGITAL IMAGE CORRELATION

ADEEL ZAFAR. DIGITAL IMAGE CORRELATION. CEE 498KUC – Experimental Methods in Structures and Materials March 14th, 2008 . Digital Image Correlation ABSTRACT. Non-contact, optical technique for obtaining full-field deformation

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DIGITAL IMAGE CORRELATION

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  1. ADEEL ZAFAR DIGITAL IMAGE CORRELATION CEE 498KUC – Experimental Methods in Structures and Materials March 14th, 2008

  2. Digital Image Correlation ABSTRACT • Non-contact, optical technique for obtaining full-field deformation • It uses image processing to go from several images of material, and to then calculate the deformation at any point in the field , and to then find deformation and strain values

  3. Outline • Introduction to DIC • History and Developments • Concept and Approach • Methodology • Theoretical background • Calibration • DIC-3D • Various Tests and Results • Advantages and Disadvantages • Applications • Conclusion

  4. Introduction • What is DIC? • It is computer based process to obtain a 2-D full field information by recording deformation and motion of speckle patterns on a specimen surface before and after deformation of the body • It takes advantage of the fact that applied stresses change both the thickness and optical properties of materials, to determine displacement

  5. Introduction • Why need DIC? Although the bulk macroscale testing provides useful information about materials but many process occur at microscale and nanoscale. As a result testing methods are required to have that resolution and capture results at that level

  6. History and developments

  7. Developed in the early ’80s at the University of South Carolina to measure full-field in-plane displacements and displacement gradients of a strained body at the macroscale • 1987 – Methodology to measure crack initiation mode & stress intensity factor in brittle materials • 1988 – Mixed-mode loading • 1992 – 3D effects near a crack tip • 1997 – Deformations measured in micron and nanometer scales History and developments

  8. 1997 – Plastic deformation patterns in ductile materials • 1998 – Method to evaluate large deformations • 2002 – Professor Lambros constructed crack growth resistance curves for functionally graded materials History and developments Contd….

  9. Concept and approach

  10. Equipment • It is less demanding optically-ordinary incoherent light is sufficient and no need for optical components • Requires one Hi resolution camera for 2D displacement and for 3D displacement, 2 cameras • A computer and frame grabbing circuit card to digitize the output

  11. Concept • It is very simple in concept • Digital camera takes picture of surface of the specimen • Image is downloaded from camera to a frame grabbing circuit card • Analog signal from CCD array are then digitized • The data is stored for subsequent processing

  12. approach • Surface of specimen is sprayed with target pattern • This is photographed before and after specimen is deformed • Digital image of specimen contains intensity measurements at each pixel location on CCD (charge couple device-sensor) array before and after • Using target features and their location, displacement field is generated • Accuracy upto 0.02 pixels have been achieved

  13. Methodology

  14. Locating target feature • Camera with CCD array(Has small photosensitive cells and high pixel count) records intensity of light falling on a pixel. • Array in high resolution camera is rectangular with thousand or more pixels per line and a thousand or more lines per image. (3x3 pixel) • Signal from CCD array is digitized and gives a reading of the light intensity for each pixel. Intensity readings are shown as 0 from dark pixels and 100 for light pixel(Grey Scale) • Storage of image into pixel and combination of pixel is called CONVOLUTION

  15. Locating target feature • To locate the target from intensity data on pixel array, DIC uses intensity pattern matching method called CORRELATION • This is done by defining the subset of pixels that surround the key feature on target • Matching two patterns establishes target displacement Initial After

  16. target feature requirement • If you have same type of target, then it would be impossible to distinguish between them • Need to have unique shape for each point • This is achieved with “speckles” • Speckle should cover at least 3x3 pixel area

  17. Speckle patterns • Techniques in creating speckles are :- • For small speckles-Spraying white paint and sprinkling of carbon particles • For moderate speckles-Spraying white paint and the black paint is sprayed with light pass • For large speckles-Spraying white paint and brushing black paint • For very high resolution- Fluorescent paint is used

  18. Speckle Matching • It is done based on algorithm for matching intensity field of many speckles because of richness of intensity data as compared to individual speckle matching

  19. Speckles with respect to scale Speckles must be custom made to fit the scale of observation. Thus, for the nanoscale, a smaller speckle pattern must be used than for the macroscale. Macroscale Nanoscle

  20. digital image • Typical digital image captured by CCD camera • Corresponding intensity profile as a surface plot

  21. Digital Image processingtheoretical background

  22. Theoretical Background • 2-D deformation • In-plane displacement • Strain fields • Known discrete functions • f(x,y)—Undeformed • g(x’,y’)—Deformed

  23. Theoretical Background • Components of displacement vector of point p in x and y direction: vp up

  24. Using g(x’,y’) • Position of any point can be defined by correlation functions: • Use above equations to solve for displacement vector :

  25. Mapping Displacement(matching) • Correlation involves comparison of intensity data of two pixel fields. Mapping the coordinates between the two fields is accomplished by using:- • X = x+u(x,y) • Y= y+v(x.y) • Matching process involves minimizing coefficient that measure how well both configuration compare

  26. Two different coefficient have been used to compare accuracy Least-square correlation coefficient Cross-correlation coefficient is a light intensity value (grayscale level) is corresponding intensity value of the same point q after deformation Matching Process

  27. Least-Squares

  28. Cross-Correlation

  29. Smoothing the intensity data • Digital Image contains thousands of pixels with different gray scale values. Usually they change abruptly • This produces mathematical difficulties when determining mapping parameter • Therefore data is smoothed over the entire field in both images. Process is called INTERPOLATION

  30. Smoothing the intensity data • Interpolation over the intensity values of deformed configuration is needed to determine these sub-pixel location intensity values • Following interpolation schemes are generally used;- • Bilinear • Cubic • Both interpolations approximates intensity value of any point that lies between pixels

  31. interpolations BICubic interpolation Bilinear interpolation

  32. Determination of displacement vector • Two methods exist:- • Coarse-Fine method. “Brute force” approach in which minimization coefficients are computed for a wide range of values and are minimized independently. Time consuming • Newton-Raphson method . All coefficients are minimized simultaneously. Faster • The process involves in obtaining optimum solution by searching over given range for the deformation parameters

  33. Calibration

  34. calibration • Determination of Magnification factor • Relates to dimension on specimen to a corresponding dimension on the image plane of camera • Location of lens center • Center of camera lens should coincide with center of area of interest • Lens Distortion • Lens with long focal lengths are employed to minimize lens distortion

  35. DIC - 3DOut of plane displacement

  36. Stereo imaging technique • Measurement of 3D component on a specimen is much more difficult • 2 CCD cameras are employed • Procedure is to get image from both cameras and then develop stereo imaging equations before correlation process

  37. Tests and results

  38. Process Live field Deformation vector field Strain field

  39. translation test

  40. Rotation tests

  41. Tension tests • Contour plot of displacement

  42. Fracture test

  43. Fracture test

  44. Fracture test Live field Deformation vector field Strain field

  45. Fracture test

  46. Advantages and disadvantages

  47. Advantages • Preparation of the specimen is relatively simple as the speckle patterns used as unique targets are made by spray painting its surface. • Ordinary white light is used to illuminate the surface of the specimen. • Specimen size is not an issue as the method can be applied to both large and small specimens. Specimen size is accommodated by changing the magnification used in recording the image. • The method is not overly sensitive to vibration and a vibration isolation table is not necessary. However, it is essential that both the specimen and the camera be stable during the time required to record the image. • Large strains or significant rigid body movement does not cause difficulties if the specimen does not move out of the field of view of the camera.

  48. Disadvantages • Sensitive to fluctuation and nonuniformity of light intensity • Measuring out of plain displacement requires more equipment and expertise • Mathematics involved is challenging • The calibration process is tedious

  49. Professional development • LaVision’s StrainMaster • Correlation Solution in Biomechanics • Research development Applications Velocity vectors in displacement zone of steel during cold-rolling process

  50. Summary • DIC is a non-contact method for measuring whole field displacement • Method involves interpolation to smooth gray scale levels and then applies coefficient to map the parameters to find strains • Mathematics involved is challenging, but if computer code is available, mapping process becomes automatic • Accuracy is often quoted as  0.02 pixels for each displacement component. Accuracy depends on:- • Interpolation schemes • Lens distortion • Uniformity of light distribution • Quality of speckle pattern

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