Detection of corrosion on silvered glass reflectors via image processing
• Novel methodology for measuring and tracking corrosion on solar reflectors. • Round-Robin among 4 participants to evaluate the comparability of the methodology. • Total corroded area, corrosion spots and edge corrosion penetration were measured. • Methodology was applied to real samples after outdoor exposure. • Advantageous of the methodology compared to state-of-the-art techniques were shown. A novel characterization technique based on image analysis is presented, intended to complement state-of-the-art reflectometer measurements. The technique is developed by experts from different laboratories (OPAC, AGC, CEA and LNEG), which subsequently conduct two Round Robin experiments on corroded solar reflectors for validation. Regarding the inter-comparability, it is found that parameters like the corrosion spot density or the penetration maximum on coated edges exhibit an average coefficient of variation of 62.6 % and 54.9 %. Better agreement is found for parameters like the total corroded area and the maximum edge corrosion penetration, with coefficients of variation of 14.3 % and 13.4 %, respectively. The developed methodology is further applied during a 68-month lasting outdoor exposure campaign of two types of solar reflectors at two representative sites, one exhibiting corrosivity class C2 and the other C3. On the commercial coating RL1, a total corroded area of 59 mm² and 426 mm² is measured after the outdoor exposure on the C2 and the C3 site, respectively, while on the novel low-lead coated reflector RL3 corresponding values are 280 mm² and 1308 mm². This shows the superior quality of the coating RL1 in terms of corrosion resistance. Furthermore, the analysis highlights the importance of proper edge sealing for corrosion protection, since corrosion penetration is increased by a factor between 1.3 and 4.0 if the edges are unprotected. The reflectance decrease after the outdoor exposure is regarded as negligible (0.000 - 0.005), thus not permitting any of the conclusions that are made from the novel image analysis technique.
Authors
- Teresa C. Diamantino (ORCID: https://orcid.org/0000-0002-0481-0460)
- Filipa Santos
- Florian Wiesinger (ORCID: https://orcid.org/0000-0002-7062-0497)
- Cristina Ferreira
- Johannes Wette (ORCID: https://orcid.org/0000-0003-1389-5176)
- Florian Sutter (ORCID: https://orcid.org/0000-0002-2981-5807)
- Soraia Páscoa (ORCID: https://orcid.org/0000-0002-2015-4547)
- Aranzazú Fernández-García (ORCID: https://orcid.org/0000-0001-6044-4306)
- I. Catarino (ORCID: https://orcid.org/0000-0002-1562-7821)
- Estelle Le Baron (ORCID: https://orcid.org/0000-0001-7792-4648)
- R. Collignon (ORCID: https://orcid.org/0000-0001-9071-3300)
- Sarah Baghouil
- Jorge Facão
Institutions
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
- Laboratoire d’Innovation pour les Technologies des Énergies Nouvelles et les nanomatériaux (FR)
- National Laboratory of Energy and Geology (PT)
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (ES)
- Asahi Glass (Belgium) (BE)
- Universidade Nova de Lisboa (PT)
- Université Grenoble Alpes (FR)
Publication Details
- Journal
- Results in Engineering
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1016/j.rineng.2024.103781
- Citations
- 3
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05