ST-YOLO: A defect detection method for photovoltaic modules based on infrared thermal imaging and machine vision technology

Photovoltaic panels are the core components of photovoltaic power generation systems, and their quality directly affects power generation efficiency and circuit safety. To address the shortcomings of existing photovoltaic defect detection technologies, such as high labor costs, large workloads, high...

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Veröffentlicht in:	PloS one 2024, Vol.19 (12), p.e0310742
Hauptverfasser:	Xie, Hanfei, Yuan, Baoxi, Hu, Chengyu, Gao, Yujie, Wang, Feng, Wang, Chunlan, Wang, Yuqian, Chu, Peng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Alternative energy sources Climate change Cold Computer and Information Sciences Computer vision Convolution Defects Economic development Efficiency Electric power generation Electric Power Supplies Energy industry Engineering and Technology Failure rates False alarms Heat detection Infrared imagery Infrared imaging Infrared Rays Lasers Machine vision Network reliability Object recognition Parameters Photovoltaic cells Photovoltaics Physical Sciences R&D Renewable resources Research & development Research and Analysis Methods Research methodology Solar energy Sustainability Tariffs Thermal imaging
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