A Review on Defect Detection of Electroluminescence-Based Photovoltaic Cell Surface Images Using Computer Vision

Tahir Hussain, Muhammad Hussain, Hussain Al-Aqrabi, Tariq Alsboui, Richard Hill

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

The past two decades have seen an increase in the deployment of photovoltaic installations as nations around the world try to play their part in dampening the impacts of global warming. The manufacturing of solar cells can be defined as a rigorous process starting with silicon extraction. The increase in demand has multiple implications for manual quality inspection. With automated inspection as the ultimate goal, researchers are actively experimenting with convolutional neural network architectures. This review presents an overview of the electroluminescence image-extraction process, conventional image-processing techniques deployed for solar cell defect detection, arising challenges, the present landscape shifting towards computer vision architectures, and emerging trends.
Original languageEnglish
Article number4012
Number of pages19
JournalEnergies
Volume16
Issue number10
DOIs
Publication statusPublished - 10 May 2023

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