Solar Panel Defects Detection Using Convolutional Neural Network (CNN)

Authors

  • Haziq Farhan Abdul Karim Universiti Tun Hussein Onn

Keywords:

Deep Learning, CNN, Trasnfer Learning, Solar Panel Defect

Abstract

Solar panels need to be checked for flaws automatically more and more as the number of new solar energy systems being made and installed around the world grows. Deep convolutional neural networks (CNN) do a very good job of classifying images from different domains, which is very impressive. In this paper, the convolutional neural network is used to describe the surface of the PV panel and find the defect. The use of transfer learning with AlexNet CNN gave a very promising result and showed how the method could be used to find different problems on the surface of a solar panel.

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Published

25-05-2023

Issue

Section

Electrical, Electronics, and Energy

How to Cite

Abdul Karim, H. F. (2023). Solar Panel Defects Detection Using Convolutional Neural Network (CNN). Progress in Engineering Application and Technology, 4(1), 345-352. https://publisher.uthm.edu.my/periodicals/index.php/peat/article/view/10598