Conceptual introduction of a high-resolution image-based defect inspection method for photovoltaic panels
Photovoltaic (PV) systems require accessible and reliable inspection approaches to support quality control and defect diagnosis, especially in settings where advanced imaging systems such as electroluminescence may be unavailable, impractical, or cost-intensive. In this context, the present study introduces a systematic high-resolution image-based inspection workflow for the visual assessment of surface defects in PV panels and positions this workflow as a digital twin-oriented inspection layer rather than a fully synchronized digital twin implementation. Under controlled laboratory lighting conditions, defective PV panel regions were photographed using a high-resolution digital camera, and the acquired images were processed through a systematic enhancement workflow including brightness adjustment, contrast optimization, noise reduction, and edge sharpening. The enhanced images improved the visual interpretability of several visible defect categories, including ribbon deflection, EVA bubbles, uncut cells, cell particles, ribbon-tab defects, visible cell fractures, and non-laminated EVA regions. The findings indicate that high-resolution image enhancement can provide a low-cost and portable visual basis for defect-oriented PV inspection by increasing local contrast and defect readability under controlled conditions. However, the proposed approach functions as a qualitative and modular visual foundation for future digital twin integration, rather than as a complete digital twin system.
Authors
- Bülent Yeşilata (ORCID: https://orcid.org/0000-0002-1552-5403)
- Ömer Önder Erat (ORCID: https://orcid.org/0000-0002-7527-196X)
- Kaan Berk Çelik (ORCID: https://orcid.org/0009-0002-5694-5508)
Institutions
- Ankara Yıldırım Beyazıt University (TR)
Publication Details
- Journal
- International Journal of Energy Studies
- Published
- 2026-09-29
- DOI
- https://doi.org/10.58559/ijes.1961986
- Primary Topic
- Photovoltaic System Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00