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Detecting the reflection of heliostat facets through computer vision.
- Source :
- AIP Conference Proceedings; 2023, Vol. 2815 Issue 1, p1-8, 8p
- Publication Year :
- 2023
-
Abstract
- Solar Power Tower systems use a series of tracking mirrors (heliostats) to concentrate sunlight into a central receiver. Each heliostat is composed of a series of smaller mirrors, called facets, that need to be correctly aligned to focus the beams into the receiver. A common problem associated with this technology is finding canting errors in the heliostat facets. One of the techniques proposed to overcome this problem includes using computer vision to accurately locate the facets and then using a heliostat's theoretical model to calculate the errors. This paper describes the computer vision mechanisms necessary to perform facet detection, proposing a quasi-automated process that minimizes the need for human input. Results show that the quasi-automated solution provides low errors in distance and slope with respect to a manual edge labelling. [ABSTRACT FROM AUTHOR]
- Subjects :
- HELIOSTATS
SOLAR energy
COMPUTER vision
MIRRORS
Subjects
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 2815
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 172853731
- Full Text :
- https://doi.org/10.1063/5.0148779