Details
| Original language | English |
|---|---|
| Pages (from-to) | 680-690 |
| Number of pages | 11 |
| Journal | TM. Technisches Messen |
| Volume | 85 |
| Issue number | 11 |
| Publication status | Published - 17 Oct 2017 |
Abstract
Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg-Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.
Keywords
- interferometry, Optical measurement technology, parallel computing, surface measurement
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Instrumentation
- Engineering(all)
- Electrical and Electronic Engineering
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In: TM. Technisches Messen, Vol. 85, No. 11, 17.10.2017, p. 680-690.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Optimization of the GPU-based data evaluation for the low coherence interferometry
AU - Li, Yinan
AU - Kästner, Markus
AU - Reithmeier, Eduard
N1 - Funding information: Acknowledgement: The authors would like to thank the “German Research Foundation” (DFG) for funding this project A2 “Multi Scale Geometry Measurement” within the Collaborative Research Centre (CRC) 871 Regeneration of Complex Goods (http://www.sfb871.de).
PY - 2017/10/17
Y1 - 2017/10/17
N2 - Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg-Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.
AB - Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg-Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.
KW - interferometry
KW - Optical measurement technology
KW - parallel computing
KW - surface measurement
UR - http://www.scopus.com/inward/record.url?scp=85037627732&partnerID=8YFLogxK
U2 - 10.1515/teme-2017-0091
DO - 10.1515/teme-2017-0091
M3 - Article
AN - SCOPUS:85037627732
VL - 85
SP - 680
EP - 690
JO - TM. Technisches Messen
JF - TM. Technisches Messen
SN - 0171-8096
IS - 11
ER -