Optimized Parametric Optical Surface Characterization Process for Smooth Engineered Surfaces

Parametric optical scattered light measuring techniques enable surface roughness characterizations in running production processes (in-process). The resulting speckle distributions show roughness dependent intensity modulations. Digital processing and evaluation of the speckle patterns quantifies an optical roughness parameter, which correlates with the rms- roughness of the surface. Current investigations concern the optimization of the measurement data acquisition with respect to individual micro topography properties and of the image processing. Measuring process simulations based on the Kirchhoff theory are carried out for measured data sets of large surface areas and for corresponding model topographies. The calculated digital speckle pattern images are evaluated with correlation methods by the use of Fast Fourier Transforms. The analysis of the results enables to optimize the selection of the measurement equipment (e.g., laser, optics and camera). Furthermore, the image processing and evaluation algorithms are prepared for the transfer to a high performance parallel computing hardware (FPGA). The contribution illustrates the optimization process and presents first results.