|Implementation of a Fault Diagnosis System Using Neural Networks for Solar Panel
Hye-Rin Hwang, Berm-Soo Kim, Tae-Hyun Cho, and In-Soo Lee*
International Journal of Control, Automation, and Systems, vol. 17, no. 4, pp.1050-1058, 2019
Abstract : "In this paper, we propose a fault diagnosis system for the solar panels of solar-powered street lights
that uses an adaptive resonance theory 2 neural network (ART2 NN) and a multilayer neural network (MNN). To
diagnose a fault in a solar panel, we use the open-circuit voltage with respect to the duty cycle as input for the two
neural networks. As a result, we can use them to double check the fault diagnosis for the solar panel. In addition,
we present a graphical user interface for the proposed solar panel fault diagnosis system. The fault diagnosis system
we propose has the potential for application in similar systems and devices."
"Adaptive resonance theory 2 neural network, fault diagnosis, graphical user interface, multilayer neural network, open-circuit voltage, solar panel."
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