Unsupervised defect detection for solar photovoltaic cells based on convolutional autoencoder

Solar photovoltaic (PV) cells are inevitably subject to defects during the production process, affecting their power generation efficiency and life. Electroluminescence (EL) imaging is the mainstream non-destructive method for PV cell defect detection. Aiming at PV cell EL images, an unsupervised de...

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Veröffentlicht in:	Nondestructive testing and evaluation Jg. 40; H. 12; S. 6143 - 6159
Hauptverfasser:	Zhang, Yufei, Zhang, Xu, Tu, Dawei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 02.12.2025 Taylor & Francis Ltd
Schlagworte:	convolutional autoencoder Defect detection Defects Nondestructive testing Perception Performance measurement Photovoltaic cells PV cell Solar cells unsupervised learning
ISSN:	1058-9759, 1477-2671
Online-Zugang:	Volltext
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