Dropout and Pruned Neural Networks for Fault Classification in Photovoltaic Arrays

Dropout and Pruned Neural Networks for Fault Classification in Photovoltaic Arrays

Automatic detection of solar array faults reduces maintenance costs and increases efficiency. In this paper, we address the problem of fault detection, localization, and classification in utility-scale photovoltaic (PV) arrays using machine learning methods. More specifically, we develop a series of...

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Bibliographic Details
Main Authors: Sunil Rao, Gowtham Muniraju, Cihan Tepedelenlioglu, Devarajan Srinivasan, Govindasamy Tamizhmani, Andreas Spanias
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Dropout neural networks
machine learning
photovoltaic panel fault detection
pruned neural networks
solar array fault classification
Online Access:https://ieeexplore.ieee.org/document/9525102/

Internet

https://ieeexplore.ieee.org/document/9525102/

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