Development of a compact low coherence interferometer based on GPGPU for fast microscopic surface measurement on turbine blades

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Li, Y.; Kästner, M.; Reithmeier, E.: Development of a compact low coherence interferometer based on GPGPU for fast microscopic surface measurement on turbine blades. In: Proceedings of SPIE - The International Society for Optical Engineering 9525 (2015), 95250R. DOI:

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Sum total of downloads: 409

Vertical scanning interferometry (VSI) techniques are widely used to profile microscopic surface structures of industrial products. This paper introduces a high-precision fast optical measurement system with an optimized small sensor head for the measurement of precision surfaces on a turbine blade or blisks (blade integrated discs). The non-contact measurement system is based on a low coherence interferometer (LCI), which is capable of fast profiling of 3D sample surface with a nanometer resolution and has a larger measurement range compared to conventional microscopes. This results in a large amount of sampled data and a high computational time for the evaluation of the data. For this reason, the used evaluation algorithm in this paper is accelerated by the Compute Unified Device Architecture (CUDA) technology, which allows parallel evaluation of the data stack on independent cores of a General Purpose Graphics Processing Unit (GPGPU). As a result, the GPU-based optimized algorithm is compared with the original CPU-based single-threaded algorithm to show the approximate 60x speedup of computing the Hilbert Transformation, which is used to find the depth position in the correlogram of each pixel of the sampled data. The main advantage of the GPU computing for the evaluation algorithm of the LCI is that it can reduce the time-consuming data evaluation process and further accelerates the whole measurement. © 2015 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: 2015
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 194 47.43%
2 image of flag of United States United States 98 23.96%
3 image of flag of China China 26 6.36%
4 image of flag of Korea, Republic of Korea, Republic of 12 2.93%
5 image of flag of Taiwan Taiwan 10 2.44%
6 image of flag of Canada Canada 7 1.71%
7 image of flag of United Kingdom United Kingdom 6 1.47%
8 image of flag of Russian Federation Russian Federation 5 1.22%
9 image of flag of Netherlands Netherlands 5 1.22%
10 image of flag of India India 4 0.98%
    other countries 42 10.27%

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