Surface roughness measurement of large areas with high spatial resolution by spectral speckle correlation

Roughness is one of the most important surface quality parameters in metal sheet processing. Thus contact-free optical methods are highly interesting. Using the innovative approach of spectral speckle correlation (SSC) has the potential to measure the spatial roughness distribution of large surfaces quickly and thus inline. In SSC, speckle patterns are recorded at different wavelengths and correlated with each other to determine the roughness of the sample. We show that the relationship between roughness and correlation coefficient as a function of wavelength difference is valid over a large range. The roughness of larger surfaces can be determined by separate evaluation of sub-images. We present the importance of the sub-image size to get reliable, reproducible measurements relating to existing standards. In this work we show how to measure the roughness parameter Sa for values ranging from 0.59 μm to 7.75 μm with a spatial resolution below 1 mm by SSC. We demonstrate that the theory is valid over a large range of wavelength differences. This is shown using wavelength differences between 0.2 nm and 93 nm in the visible spectrum.