Poster + Paper
2 March 2022 Quality inspection of translucent and micro-structured functional surfaces
Nicole Brosch, Laurin Ginner, Sarah Schneider, Doris Antensteiner, Lukas Traxler
Author Affiliations +
Proceedings Volume 12019, AI and Optical Data Sciences III; 120190P (2022) https://doi.org/10.1117/12.2605273
Event: SPIE OPTO, 2022, San Francisco, California, United States
Conference Poster
Abstract
Micro-structured films with surface riblets are used to reduce aerodynamic drag. This is especially relevant on fast and large objects such as on aircraft wings, where they are installed to increase efficiency (e.g., reduce fuel consumption). Their fuel reduction efficiency depends directly on the structural integrity of the films. Therefore, we propose a photometric inspection tool, a hardware setup and tailored analysis algorithms, which detect typical defects of riblet micro-structures occurring during their operational lifetime. We propose two inspection approaches to analyze the micro-structures, (i) a statistical data processing method and (ii) a machine learning algorithm based on convolutional autoencoders. We tested both inspection approaches on rendered and real world data of riblet films on airplane elements, carbon-fiber parts of race cars, and wind turbine blades.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nicole Brosch, Laurin Ginner, Sarah Schneider, Doris Antensteiner, and Lukas Traxler "Quality inspection of translucent and micro-structured functional surfaces", Proc. SPIE 12019, AI and Optical Data Sciences III, 120190P (2 March 2022); https://doi.org/10.1117/12.2605273
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Inspection

Machine learning

Translucency

Defect detection

Statistical analysis

Data modeling

Data processing

Back to Top