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About Detection of Malfunctioning Photovoltaic Modules Based On Machine Learning Algorithms
This document proposes a hybrid scheme using three machine learning methods to detect malfunctioning photovoltaic modules based on infrared thermographic images. The first method uses a convolutional neural network trained on infrared images preprocessed with an improved gamma correction function. The second method trains a CNN using infrared temperatures preprocessed with a threshold function. The third replaces the CNN with an XGBoost model trained on selected temperature statistics. Experimental results show all three methods can detect malfunctions with high accuracy and efficiency, and the hybrid scheme provides even better performance.
Detailed Information
| Author: | ['Rodrigo'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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