Photovoltaic cell defect classification using convolutional neural network and support vector machine

Author:

Ahmad Ashfaq12ORCID,Jin Yi1,Zhu Changan1,Javed Iqra3,Maqsood Asim2,Akram Muhammad Waqar1ORCID

Affiliation:

1. Department of Precision Machinery & InstrumentationUniversity of Science and Technology of ChinaHefeiPeople's Republic of China

2. Department of Electronics & Electrical SystemsThe University of LahoreLahorePakistan

3. Department of Informatics and SystemsUniversity of Management and TechnologyLahorePakistan

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Reference44 articles.

1. Classification of manufacturing defects in multicrystalline solar cells with novel feature descriptor;Su B.;IEEE Trans. Instrum. Meas.,2019

2. A numerical model for soldering process in silicon solar cells;Nasr Esfahani S.;Sol. Energy,2017

3. Thermo‐mechanical behavior assessment of smart wire connected and busbar PV modules during production, transportation, and subsequent field loading stages;Li G.;Energy,2019

4. Characterization of cell mismatch in photovoltaic modules using electroluminescence and associated electro‐optic techniques magister scientiae;Crozier J.L.;Doctoral dissertation, Nelson Mandela Metropolitan University,2012

5. Detection and localization of defects in monocrystalline silicon solar cell;Tománek P.;Adv. Opt. Technol.,2010

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