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Abstract:
In the last decade, slope-measuring deflectometry has seen rapid progress in configuration design, hardware calibration, and computational processing. As a highly-reconfigurable, non-null surface metrology technique, deflectometry fills many widening metrology gaps left by optical design trends in freeform industrial optics and astronomical reflectors. This study advances the accuracy of the art and the variety of measurable optical surfaces across three major topics.
The first topic is the measurement of astronomical gossamer reflectors with phase-measuring deflectometry. The metrology of these inflatable membrane structures remains challenging. Internal pressure, anisotropic mechanical film properties, and circumferential boundary conditions imbue highly dynamic slopes to a varifocal optical surface. Beyond full-aperture measurement in ambient, I present the analysis technique and experimental results for measuring the 1-meter inflatable reflector’s shape across multiple refractive interfaces in cryogenic vacuum.
In the second topic, I develop a novel on-axis deflectometry system that uses a custom non-planar illumination source to measure convex axicons. Axicons are challenging to measure due to their characteristically steep, convex geometry. However, if an axicon is coaxially aligned with a camera and a surrounding cylindrical illumination source, high-resolution surface measurements can be obtained. Deflectometry measurements of a 100° and 140° axicon showed holistic cone angle agreement within 0.035° against touch probe data and up to 7.93 um root mean square difference from a best-fit cone.
In the final topic, I propose and examine the influence of radiometric shift variance in long-wave infrared line-scanning deflectometry. I show the combined effect of irradiance fall-off with object field angle and the blur of extended source points manifests as low-order shape error. Then, I provide a radiometrically-faithful suite of raytrace studies to obtain the surface error as a function of system geometry. Empirical relationships generalize how the classical centroiding algorithm underestimates surface power and overestimates astigmatism in final surface maps.