Comparative performance of DIC and optical flow algorithms for displacement and strain analysis in laser beam welding

Abstract

The measurement of strain and displacement in the context of the welding process represents a significant challenge. Optical methods, such as digital image correlation (DIC) or optical flow algorithms, have demonstrated their efficacy in robust and reliable data acquisition in harsh environments, including those encountered in welding processes. Concurrently, a trade-off between the accuracy of the measurement and the computational resources required for the associated calculations must be evaluated on a case-by-case basis. The application of filters to initial images represents a technique that serves to enhance the quality and accuracy of the strain and displacement prediction. In the present study, the estimated error of two algorithms, namely the Lucas-Kanade (LK) and the inverse compositional Gauss-Newton (IC-GN), is compared on the basis of both synthetic and real welding images. The displacement field is evaluated for different zones in the laser weld seam with varying contrast performance. Based on the aforementioned results, a strain calculation was conducted for both methods, which yielded comparable results for the LK and IC-GN algorithms