Surface defect detection methods for industrial products: A review

Y Chen, Y Ding, F Zhao, E Zhang, Z Wu, L Shao - Applied Sciences, 2021 - mdpi.com
The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …

Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review

B Li, C Delpha, D Diallo, A Migan-Dubois - Renewable and Sustainable …, 2021 - Elsevier
The rapid development of photovoltaic (PV) technology and the growing number and size of
PV power plants require increasingly efficient and intelligent health monitoring strategies to …

Automatic classification of defective photovoltaic module cells in electroluminescence images

S Deitsch, V Christlein, S Berger, C Buerhop-Lutz… - Solar Energy, 2019 - Elsevier
Electroluminescence (EL) imaging is a useful modality for the inspection of photovoltaic (PV)
modules. EL images provide high spatial resolution, which makes it possible to detect even …

Failures of Photovoltaic modules and their Detection: A Review

MW Akram, G Li, Y Jin, X Chen - Applied Energy, 2022 - Elsevier
Photovoltaic (PV) has emerged as a promising and phenomenal renewable energy
technology in the recent past and the PV market has developed at an exponential rate …

CNN based automatic detection of photovoltaic cell defects in electroluminescence images

MW Akram, G Li, Y Jin, X Chen, C Zhu, X Zhao… - Energy, 2019 - Elsevier
Automatic defect detection is gaining huge importance in photovoltaic (PV) field due to
limited application of manual/visual inspection and rising production quantities of PV …

In-depth review of yolov1 to yolov10 variants for enhanced photovoltaic defect detection

M Hussain, R Khanam - Solar, 2024 - mdpi.com
This review presents an investigation into the incremental advancements in the YOLO (You
Only Look Once) architecture and its derivatives, with a specific focus on their pivotal …

Automatic detection of photovoltaic module defects in infrared images with isolated and develop-model transfer deep learning

MW Akram, G Li, Y Jin, X Chen, C Zhu, A Ahmad - Solar Energy, 2020 - Elsevier
With the rising use of photovoltaic and ongoing installation of large-scale photovoltaic
systems worldwide, the automation of photovoltaic monitoring methods becomes important …

A multi-stage model based on YOLOv3 for defect detection in PV panels based on IR and visible imaging by unmanned aerial vehicle

A Di Tommaso, A Betti, G Fontanelli, B Michelozzi - Renewable energy, 2022 - Elsevier
As solar capacity installed worldwide continues to grow, there is an increasing awareness
that advanced inspection systems are becoming of utmost importance to schedule smart …

Multiscale feature-clustering-based fully convolutional autoencoder for fast accurate visual inspection of texture surface defects

H Yang, Y Chen, K Song, Z Yin - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Visual inspection of texture surface defects is still a challenging task in the industrial
automation field due to the tremendous changes in the appearance of various surface …

Prognostics and health management of photovoltaic systems based on deep learning: A state-of-the-art review and future perspectives

Z Chang, T Han - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
As global photovoltaic (PV) power generation capacity rapidly expands, efficient and
effective health management of PV systems has emerged as a critical focal point. With the …