Semiconductor Optoelectronics, Volume. 44, Issue 2, 161(2023)

Progress in Artificial Intelligence Thermal Infrared Detection Technology for Photovoltaic Modules in Power Plant

NING Jing1...2,3, XU Shengzhi1,2,3,*, GONG Youkang1,2,3, WANG Lichao1,2,3, and JIANG Qian1,23 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    The defect detection of photovoltaic modules based on temperature infrared image is an important technology to realize the large-scale modules quality detection of photovoltaic power plant. In this paper, the causes and hazards of hot spot of photovoltaic modules were briefly introduced. The artificial neural network model and its performance of infrared image and video of photovoltaic modules were summarized and compared from three aspects: hot spot detection, hot spot location and extraction. The hot spot detection accuracy of the improved YOLOv5 model for photovoltaic modules reached 98.8%, and the hot spot positioning accuracy of the Lucas-Kanade sparse optical flow algorithm reached 97.5%. At the end of this paper, the development trend of hot spot detection technology adapted to meet the operation and maintenance needs of large-scale photovoltaic power plant was briefly discussed.

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    NING Jing, XU Shengzhi, GONG Youkang, WANG Lichao, JIANG Qian. Progress in Artificial Intelligence Thermal Infrared Detection Technology for Photovoltaic Modules in Power Plant[J]. Semiconductor Optoelectronics, 2023, 44(2): 161

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    Paper Information

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    Received: Jan. 16, 2023

    Accepted: --

    Published Online: Aug. 14, 2023

    The Author Email: Shengzhi XU (185859840@qq.com)

    DOI:10.16818/j.issn1001-5868.2023011601

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