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- W4383748168 abstract "The hot spot fault of photovoltaic modules seriously affects the power generation efficiency and safe operation of photovoltaic power stations, which is an urgent problem to be solved in the photovoltaic operation and maintenance. In this paper, a feature-based decision tree classification method for hot spot fault of photovoltaic modules is proposed, which extracts the geometric features of the hot spot target areas in the infrared thermal image of photovoltaic modules, then combines the decision tree classification algorithm to divide hot spot faults into two categories: external occlusion faults and internal defect faults, so as to provide a basis for photovoltaic operation and maintenance. MATLAB Simulation experiments demonstrate the effectiveness and accuracy of the proposed method." @default.
- W4383748168 created "2023-07-11" @default.
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- W4383748168 date "2023-05-12" @default.
- W4383748168 modified "2023-10-18" @default.
- W4383748168 title "Feature-Based Decision Tree Classification Method for Hot Spot Faults of Photovoltaic Modules" @default.
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- W4383748168 doi "https://doi.org/10.1109/cieec58067.2023.10166995" @default.
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