Polycrystalline silicon photovoltaic panel detection

How to classify defects in a polycrystalline silicon PV cell?

To classify the seven types of defects in a polycrystalline silicon PV cell, the proposed machine learning approaches are applied to the public dataset of solar cell EL images. The successful classification of these defects is a challenging task due to the background texture of the cells.

Can micro-cracks be detected in polycrystalline PV cells?

Anwar and Abdullah [ 17] proposed a method for micro-crack detection in polycrystalline PV cells using an improved anisotropic diffusion filter and image segmentation. However, this technique is not applicable to multiple defects classification in polycrystalline PV cells.

How do photovoltaic cell defect detection models improve the inspection process?

These models not only enhance detection accuracy but also markedly reduce the time required for defect detection, thus optimizing the overall inspection process. Zhang et al. 8 introduced a photovoltaic cell defect detection method leveraging the YOLOV7 model, which is designed for rapid detection.

Can a real-time defect detection model detect photovoltaic panels?

Efforts have been made to develop models capable of real-time defect detection, with some achieving impressive accuracy and processing speeds. However, existing approaches often struggle with feature redundancy and inefficient representations of defects in photovoltaic panels.

Can a photovoltaic cell defect detection model extract topological knowledge?

Visualizing feature map (The figure illustrates the change in the feature map after the SRE module.) We propose a photovoltaic cell defect detection model capable of extracting topological knowledge, aggregating local multi-order dynamic contexts, and effectively capturing diverse defect features, particularly for small flaws.

How machine vision is used in photovoltaic panel defect detection?

Machine vision-based approaches have become an important direction in the field of defect detection. Many researchers have proposed different algorithms 11, 15, 16 for photovoltaic panel defect detection by creating their own datasets.