Non-contact displacements measurement using an improved particle swarm optimization based digital speckle correlation method

The digital speckle correlation method (DSCM) is a non-contacting and practical tool for quantitative in-plane deformation measurement of a planar object surface. The method is based on correlating the speckle surface of the object before and after deformation and provides whole-field measurement with sub-pixel accuracy. This paper reviews a DSCM based on Particle Swarm Optimization (PSO) to measure surface displacements and strains by assuming first order linear deformation. In this paper, a two steps optimization routine involving a coarse search followed by an adaptive inertia weight PSO algorithm which was developed by Wang is implemented. The optimization routine is further improved using an intelligent automatic subset size selection technique developed by Pan. This method is first applied in DSCM and its feasibility is investigated in this paper. Results have shown that the improved PSO method can guarantee a solution with an accuracy of 0.002 pixels by comparing computer simulated images. This method is also compared with other PSO variants and Genetic Algorithm optimization for validation. Comparison has shown that adaptive inertia weight PSO is recommended for improving the performance of DSCM.