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[IEEE 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) - Fukuoka, Japan (2020.2.19-2020.2.21)] 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) - Photovoltaic Cell Defect Detection Model based-on Extracted Electroluminescence Images using SVM Classifier
摘要： Electroluminescence (EL) imaging is used to analyze the characteristics of solar cells. This technique provides various details about solar panel modules such as solar cell characteristics, materials used, health status, defects, etc. The derived features from solar panel images provide a significant source of information for photovoltaic applications such as fault detection assessment. In this work, a method for classifying between the normal and a defective solar cell was implemented using EL imaging with selected digital image processing techniques through the Support Vector Machine (SVM) classifier. The EL images are processed using feature extraction procedures. The system was observed to provide an accuracy of 95%. The algorithm presented was implemented in MATLAB R2019b programming environment.
关键词： photovoltaic module,solar panel,and support vector machine.,digital processing,image electroluminescence imaging
更新于2025-09-23 15:21:01
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Imaging and micro-structural characterization of moisture induced degradation in crystalline silicon photovoltaic modules
摘要： Moisture induced degradation in photovoltaic (PV) modules operate via multiple chemical mechanisms commonly identi?ed by the sole use of destructive techniques. However, in such cases, e?ective use of spatial imaging techniques can aid identi?cation of certain operating mechanisms on the basis of degradation pattern characteristics. This paper presents an approach of imaging the e?ects of moisture induced degradation in crystalline silicon PV modules under damp heat (DH) test conditions using electroluminescence (EL) and dark lock-in-thermography (DLIT) imaging techniques. The a?ected regions were extracted for identi?cation of degradation products using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) micro-structural characterization technique. Consequently, combination of both imaging and micro-structural characterization techniques were used to propose the mechanism of degradation. The presented approach was instrumental in identi?cation of the e?ects of moisture induced degradation through imaging techniques, moreover the investigation also provided insights in this ?eld of work. The results present signature image patterns for identi?cation and di?erentiation of dominant chemical mechanisms under moisture induced conditions viz. tin migration at the ?nger-wafer interface and formation of silver oxide at cell cracks and edges. The ribbon interconnects was identi?ed as an active site for deposition of oxides from solder material, and aluminium electrode in presence of water as an electrolyte. Moreover, loss in interfacial adhesion between wafer, encapsulant and ?nger. In addition, material quality, manufacturing distinctions, and module design parameters seem to be responsible for observing di?erent operating mechanisms. Also, the obtained insights were applied for investigation of a 20-year-old aged PV module.
关键词： Chemical degradation,Damp heat test,Photovoltaic modules,Electroluminescence imaging,Dark lock-in thermography imaging,Moisture induced degradation
更新于2025-09-11 14:15:04