Wavefront predictions for the automated assembly of optical systems

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Schindlbeck, C.; Pape, C.; Reithmeier, E.: Wavefront predictions for the automated assembly of optical systems. In: Proceedings of SPIE 10815 (2018), 108150B. DOI: https://doi.org/10.1117/12.2500000

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Sum total of downloads: 111




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Abstract: 
Industrial assembly of optical systems is still a tedious and cost-intensive task that is mostly dominated by manual labor. Positional fine-adjustment of optical components is pivotal to ensure a desired performance of the optical device at hand. In this paper, we use wavefront predictions to aim for fully automated assembly procedures. Wavefront measurements along with position identification methods can be utilized to continuously update a simulation model which in turn allows for predictions on future wavefront errors. This enables to take according correction measures during the assembly process if a certain wavefront tolerance specification is not met. In order to demonstrate the efficacy of the proposed approach and methods, a beam expander is sequentially assembled. The setup consists of a laser, two bi-convex lenses, and a Shack-Hartmann wavefront sensor and has to satisfy a certain wavefront tolerance specification after its assembly. © 2018 SPIE.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
Document Type: BookPart
Publishing status: publishedVersion
Issue Date: 2018
Appears in Collections:Fakultät für Elektrotechnik und Informatik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 36 32.43%
2 image of flag of United States United States 31 27.93%
3 image of flag of China China 11 9.91%
4 image of flag of Czech Republic Czech Republic 7 6.31%
5 image of flag of Hong Kong Hong Kong 5 4.50%
6 image of flag of Russian Federation Russian Federation 4 3.60%
7 image of flag of United Kingdom United Kingdom 3 2.70%
8 image of flag of Poland Poland 2 1.80%
9 image of flag of India India 2 1.80%
10 image of flag of Ireland Ireland 1 0.90%
    other countries 9 8.11%

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