RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULES BASED ON INFRARED IMAGES AND IMPROVED MOBILENET-V3

Ren Hui; Xia Jing; Lu Jinling; Wang Yunzhe; Xin Guoyu

doi:10.19912/j.0254-0096.tynxb.2022-0519

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (8) : 238-245. DOI: 10.19912/j.0254-0096.tynxb.2022-0519

RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULES BASED ON INFRARED IMAGES AND IMPROVED MOBILENET-V3

Ren Hui, Xia Jing, Lu Jinling, Wang Yunzhe, Xin Guoyu

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Abstract

In order to improve the reliability and performance of photovoltaic systems, a fault diagnosis method for photovoltaic modules based on infrared images and improved MobileNet-V3 is proposed. Firstly, the defect images of open-source photovoltaic modules and their existing problems are analyzed. Then, image and data enhancement are performed on the infrared defect images of photovoltaic modules aiming at the existing problems, so that the infrared images meet the requirements of image availability and sample quantity. Finally, the basic MobileNet-V3 network is improved to realize fault classification of photovoltaic modules. The experimental results show that, compared with the traditional CNN and the basic MobileNet-V3, the proposed fault classification method not only has high accuracy and fast diagnosis speed, but also has a high recognition rate for various fault categories, which has good practicability and application value.

Key words

photovoltaic modules / infrared imaging / image enhancement / fault diagnosis / improved MobileNet-V3 algorithm

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Ren Hui, Xia Jing, Lu Jinling, Wang Yunzhe, Xin Guoyu. RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULES BASED ON INFRARED IMAGES AND IMPROVED MOBILENET-V3[J]. Acta Energiae Solaris Sinica. 2023, 44(8): 238-245 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0519

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