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

doi:10.3390/en16104012

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

Higher Colleges of Technology

Research output: Contribution to journal › Review article › peer-review

38 Citations (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 language	English
Article number	4012
Number of pages	19
Journal	Energies
Volume	16
Issue number	10
DOIs	https://doi.org/10.3390/en16104012
Publication status	Published - 10 May 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

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10.3390/en16104012Licence: CC BY

Cite this

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AU - Hill, Richard

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KW - Micro-cracks

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

Abstract

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