Lecture 2

Lecture 2: 2D Digital Image Correlation (duration:1h30)

 

Objectives

  • Outline the basic principles of subset-based digital image correlation to perform displacement measurements.

Contents

  • Basic principles of DIC:  Image matching. Why is a speckle pattern needed ( correspondence problem)? What is subset size and step size (what are their limitations)?   
  • Correlation criterion: Cross correlation vs. Sum of Squared Differences, offset and scaling in lighting.
  • Interpolation: DIC measures displacements with subpixel accuracy. How to look in between sampled points.
  • Shape functions: Deformation of the subset for optimal matching according to the deformation process. What order to use? 
  • Optimization routines: How does a basic correlation run works (coarse and refinement) and how to interpret number of iterations.
  • How do we derive strains
  • Initial guess and incremental correlation for large deformations
  • Local versus Global approach

Competencies

  • The trainee is familiar with the basic parametric settings (subset size, step size, correlation criterion, interpolation, shape function …) in a DIC formalism to measure displacements and knows which ones to use in various circumstances.