Predictor-corrector framework for the sequential assembly of optical systems based on wavefront sensing

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Schindlbeck, C.; Pape, C.; Reithmeier, E.: Predictor-corrector framework for the sequential assembly of optical systems based on wavefront sensing. In: Optics Express 26 (2018), Nr. 8, S. 10669-10681. DOI: https://doi.org/10.1364/OE.26.010669

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Sum total of downloads: 125




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Abstract: 
Alignment of optical components is crucial for the assembly of optical systems to ensure their full functionality. In this paper we present a novel predictor-corrector framework for the sequential assembly of serial optical systems. Therein, we use a hybrid optical simulation model that comprises virtual and identified component positions. The hybrid model is constantly adapted throughout the assembly process with the help of nonlinear identification techniques and wavefront measurements. This enables prediction of the future wavefront at the detector plane and therefore allows for taking corrective measures accordingly during the assembly process if a user-defined tolerance on the wavefront error is violated. We present a novel notation for the so-called hybrid model and outline the work flow of the presented predictor-corrector framework. A beam expander is assembled as demonstrator for experimental verification of the framework. The optical setup consists of a laser, two bi-convex spherical lenses each mounted to a five degree-of-freedom stage to misalign and correct components, and a Shack-Hartmann sensor for wavefront measurements.
License of this version: OSA Open Access License
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2018
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 77 61.60%
2 image of flag of United States United States 19 15.20%
3 image of flag of China China 9 7.20%
4 image of flag of Europe Europe 3 2.40%
5 image of flag of Switzerland Switzerland 3 2.40%
6 image of flag of Russian Federation Russian Federation 2 1.60%
7 image of flag of Poland Poland 2 1.60%
8 image of flag of India India 2 1.60%
9 image of flag of Canada Canada 2 1.60%
10 image of flag of New Zealand New Zealand 1 0.80%
    other countries 5 4.00%

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