Image Preprocessing for Outdoor Luminescence Inspection of Large Photovoltaic Parks
Abstract
:1. Introduction
2. Calibration Principle
3. Pattern Detection Procedure
3.1. PV Module Corner Detection
3.2. Binarization for Cell Gap Detection
3.3. Identification of Line Structures
- Filter out straight lines by angle and position that do not match the perspective of the PV module
- Reduce the number of straight lines for one curved line structure to one straight line with the closest representation
- Distinguish between cell gap line and busbar line
- Weight () of each line—sum of distance weighted pixel intensity.
- (Intersection) of lines. Wherever two found lines of the same cluster (long-to-long or short-to-short module edge) intersect, the line with the higher weight is assumed as the valid line and is used for further steps.
3.4. Precise Cell Gap Joint (CGJ) Search in ROI
4. Experiment
4.1. Setup
4.2. Results
4.2.1. Experiment 1—Parameter Estimation Quality Depending on the Amount of Image Planes
4.2.2. Experiment 2—Calibration Quality for Large On-Field Datasets
Quality Evaluation Metric
- Ideal equidistant grid points, in a undistorted and perspective transformed image—target points (of perspective transformation)
- CGJ points as detected in the distorted image, undistorted and perspective transformed—source
- Ground truth CGJ points labeled by an expert in the distortion corrected and perspective transformed image—real location of CGJ after correction
Self Calibration Quality
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
DUT | Device Under Test |
EL | Electroluminescence |
CGJ | Cell Gap Joints |
KF | Key Figures |
ML | Machine Learning |
PV | Photovoltaic |
PID | Potential Induced Degradation |
CMOS | Complementary Metal-Oxide-Semiconductor |
ROI | Region Of Interest |
SE | Standard Error |
RSE | Relative Standard Error |
Appendix A. Images after the Processing Steps
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Kölblin, P.; Bartler, A.; Füller, M. Image Preprocessing for Outdoor Luminescence Inspection of Large Photovoltaic Parks. Energies 2021, 14, 2508. https://doi.org/10.3390/en14092508
Kölblin P, Bartler A, Füller M. Image Preprocessing for Outdoor Luminescence Inspection of Large Photovoltaic Parks. Energies. 2021; 14(9):2508. https://doi.org/10.3390/en14092508
Chicago/Turabian StyleKölblin, Pascal, Alexander Bartler, and Marvin Füller. 2021. "Image Preprocessing for Outdoor Luminescence Inspection of Large Photovoltaic Parks" Energies 14, no. 9: 2508. https://doi.org/10.3390/en14092508