Paper
7 March 2024 Defect detection of photovoltaic panel based on morphological segmentation
Bolin Cheng, Bolin Li, Liang Ye
Author Affiliations +
Proceedings Volume 13085, MIPPR 2023: Automatic Target Recognition and Navigation; 130850J (2024) https://doi.org/10.1117/12.3005227
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China
Abstract
The automatic inspection of photovoltaic panels based on infrared images is one of the important tasks in the daily maintenance of photovoltaic panels in photovoltaic power plants. In this paper, a defect detection method of infrared thermal image photovoltaic panel based on morphological segmentation is proposed. First of all, according to the infrared characteristics of the photovoltaic plant station and the morphological characteristics of the photovoltaic panel, the accurate region of each photovoltaic panel is determined in the inspection image. Then, statistical method is used for feature analysis to determine whether there are defects in photovoltaic panels, and then the defective photovoltaic panels are segmented and different defects are classified according to morphological characteristics, and finally the defect detection and classification of photovoltaic panels are realized. Through the experiment in the actual inspection image of photovoltaic plant station, it is verified that the proposed method has a high accuracy of defect detection and recognition.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Bolin Cheng, Bolin Li, and Liang Ye "Defect detection of photovoltaic panel based on morphological segmentation", Proc. SPIE 13085, MIPPR 2023: Automatic Target Recognition and Navigation, 130850J (7 March 2024); https://doi.org/10.1117/12.3005227
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KEYWORDS
Solar cells

Defect detection

Image segmentation

Thermography

Infrared imaging

Infrared radiation

Inspection

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