Heliostat Optical Error Inspection with Polarimetric Imaging Drone
Mo Tian, Kolappan Chidambaranathan, Md Zubair Ebne Rafique, Neel Desai, Jing Bai, Randy Brost, Daniel Small, David Novick, Julius Yellowhair, Yu Yao

TL;DR
This paper introduces a polarimetric imaging drone system that significantly improves the contrast and accuracy of heliostat mirror edge detection in CSP fields, enabling fast, non-intrusive, autonomous inspection during operation.
Contribution
The study develops a novel polarimetric imaging method integrated on UAVs, enhancing contrast for heliostat inspection and demonstrating its effectiveness through field tests.
Findings
Enhanced edge detection success rate in challenging scenarios
Improved imaging contrast with polarimetric method
Feasibility of real-time autonomous heliostat inspection
Abstract
On a Concentrated Solar Power (CSP) field, optical errors have significant impacts on the collection efficiency of heliostats. Fast, cost-effective, labor-efficient, and non-intrusive autonomous field inspection remains a challenge. Approaches using imaging drone, i.e., Unmanned Aerial Vehicle (UAV) system integrated with high resolution visible imaging sensors, have been developed to address these challenges; however, these approaches are often limited by insufficient imaging contrast. Here we report a polarimetry-based method with a polarization imaging system integrated on UAV to enhance imaging contrast for in-situ detection of heliostat mirrors without interrupting field operation. We developed an optical model for skylight polarization pattern to simulate the polarization images of heliostat mirrors and obtained optimized waypoints for polarimetric imaging drone flight path to…
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Taxonomy
TopicsInfrared Target Detection Methodologies · Advanced Measurement and Detection Methods · Optical Systems and Laser Technology
