Abstract

Abstract The goal-oriented manipulation of surface integrity by certain manufacturing processes requires comprehensive knowledge of the physical stresses induced into the workpiece. Properties such as the hardness are strongly influenced by mechanical stresses, induced during machining. The basic prerequisite for a comprehensive comparison of different manufacturing processes is the ability to precisely determine the stresses in the form of plastic and elastic displacements during the running manufacturing process. Due to the rough environmental conditions in many metalworking manufacturing processes, there are no non-invasive commercial methods for measuring the loads in the processed zone. For this reason, the suitability of speckle photography for in-process measurements of displacements to determine material loads in the process of single-tooth milling, rolling, grinding and laser hardening is investigated and questions regarding the respective achievable measurement uncertainty are addressed. To prevent a decorrelation of the speckle patterns within a measurement series, the images are captured with a high-speed camera and the total surface displacement is calculated from the sum of the individual image-to-image shifts. The measurement uncertainty of the image series thus adds up slowly with the number of processed images. However, by locally averaging the image series when stitching the individual displacement fields together to form a larger overall measurement field, the measurement uncertainty in the applications under consideration can be reduced to 1% of the maximum displacement. In this context, the interrelation between the cumulative uncertainty of measurement and the lateral expansion or size of the total displacement fields under consideration is investigated. In particular, the measurement uncertainty can decrease even further, if the individual measurement fields overlap more and if the displacement fields are small in relation to the measuring field. As a result, speckle photography provides a low measurement uncertainty and shows its applicability under rough environmental conditions in the examined processes.

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