The concept of process signature uses the relationship between a material load and the resulting modification remaining in the workpiece to better understand and optimize manufacturing processes. The metrological recording of the loads occurring during the machining process in the form of mechanical deformations is the basic prerequisite for this approach. An appropriate characterization method is speckle photography, which is already applied for in-plane deformation measurements in various manufacturing processes. A shortcoming of this fast and robust measurement technique based on image correlation techniques is that deformations in the direction of the measurement system are not detected and that they increase the error of measurement for in-plane deformations. Therefore, this work investigates a method that infers local out-of-plane motions of the workpiece surface from the decorrelation of speckle patterns and thus is able to reconstruct three-dimensional deformation fields. The implementation of the evaluation method in existing sub-pixel interpolation algorithms enables a fast reconstruction of 3D deformation fields, so that the desirable in-process capability remains given. Using a deep rolling process, first measurements show that dynamic 3D-deformations below the tool can be detected, which confirms the suitability of the speckle photography not only for the 2D- but also the 3D-analysis of deformations in manufacturing processes.
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