Environmental Fault Diagnosis of Solar Panels Using Solar Thermal Images in Multiple Convolutional Neural Networks
Every year, each solar panel suffers an efficiency loss of 0.5% to 1%. This degradation of solar panels arises due to environmental and electrical faults. A timely and accurate diagnosis of environmental faults reduces the damage caused by faults on the panel. In recent years, deep learning precisel...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2022/2872925 |
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