DA-DCGAN: An Effective Methodology for DC Series Arc Fault Diagnosis in Photovoltaic Systems

DA-DCGAN: An Effective Methodology for DC Series Arc Fault Diagnosis in Photovoltaic Systems

DC arc faults, especially series arcing, can occur in photovoltaic (PV) systems and pose a challenging detection and protection problem. Machine learning-based methods are increasingly being used for fault diagnosis applications. However, the performance of such detection algorithms will degrade bec...

Full description

Bibliographic Details
Main Authors: Shibo Lu, Tharmakulasingam Sirojan, B. T. Phung, Daming Zhang, Eliathamby Ambikairajah
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep learning
domain adaptation
deep convolutional generative adversarial networks
DC series arc fault diagnosis
photovoltaic systems
Online Access:https://ieeexplore.ieee.org/document/8681389/

Internet

https://ieeexplore.ieee.org/document/8681389/

Similar Items