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A Photovoltaic Panel Inspection Method for UAV Based on Attention Mechanism Target Detection
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Ying YAO, Bing GU, Zhengnan FANG
Electric Drive | 2025, 55(5) : 89 - 96
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Electric Drive | 2025, 55(5): 89-96
A Photovoltaic Panel Inspection Method for UAV Based on Attention Mechanism Target Detection
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Ying YAO, Bing GU, Zhengnan FANG
Affiliations
  • Zhejiang TaLent Electric Group Company Limited,Huzhou 313000,Zhejiang,China
Published: 2025-05-20 doi: 10.19457/j.1001-2095.dqcd25344
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With the wide application of solar photovoltaic panels,the detection of hidden dangers and faults of photovoltaic panels has become more and more important. In order to improve the inspection efficiency of photovoltaic panels and the accuracy of defect detection,a target detection algorithm based on attention mechanism was designed and a complete inspection scheme of photovoltaic panels combined with UAV technology was proposed. The method uses the high-resolution camera mounted on the UAV for image acquisition,and detects and identifies the defects of photovoltaic panels through the combination of the object detection of the attention mechanism and the UAV technology. The experimental results show that the proposed method has high accuracy and reliability in photovoltaic panel inspection,mean average accuracy (mAP) reaches 83.2%,F1 score is 84.5%,effectively improve the quality and effect of photovoltaic panel inspection,and has high practical value.

object detection  /  unmanned aerial vehicle (UAV)  /  attention mechanism  /  photovoltaic panel inspection
Ying YAO, Bing GU, Zhengnan FANG. A Photovoltaic Panel Inspection Method for UAV Based on Attention Mechanism Target Detection[J]. Electric Drive, 2025 , 55 (5) : 89 -96 . DOI: 10.19457/j.1001-2095.dqcd25344
Year 2025 volume 55 Issue 5
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Article Info
doi: 10.19457/j.1001-2095.dqcd25344
  • Receive Date:2023-09-01
  • Online Date:2025-11-05
  • Published:2025-05-20
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  • Received:2023-09-01
  • Revised:2023-11-13
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    Zhejiang TaLent Electric Group Company Limited,Huzhou 313000,Zhejiang,China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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