Monitoring and Diagnostics of Photovoltaic Cells by Electroluminescence
Author:
Affiliation:
1. University of Miskolc,Institute of Physics and Electrical Engineering,Department of Electrical and Electronic Engineering,Miskolc,Hungary,H-3515
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9805807/9805809/09805888.pdf?arnumber=9805888
Reference13 articles.
1. Defects Inspection in Polycrystalline Solar Cells Electroluminescence Images Using Deep Learning
2. Automatic classification of defective photovoltaic module cells in electroluminescence images
3. Automatic Defect Inspection for Monocrystalline Solar Cell Interior by Electroluminescence Image Self-Comparison Method
4. Advanced large area characterization of thin-film solar modules by electroluminescence and thermography imaging techniques
5. CNN based automatic detection of photovoltaic cell defects in electroluminescence images
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1. Photovoltaic Module Defects Classification Analysis Using ShuffleNet Architecture in Electroluminescence Images;2023 9th International Conference on Computer and Communication Engineering (ICCCE);2023-08-15
2. Redundant Fault Diagnosis for Photovoltaic Systems Based on an IRT Low-Cost Sensor;Sensors;2023-01-24
3. A Fault Detection Method Based on CNN and Symmetrized Dot Pattern for PV Modules;Energies;2022-09-03
4. Solar Photovoltaic Modules’ Performance Reliability and Degradation Analysis—A Review;Energies;2022-08-17
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