Abstract:
Considering the advantages of simple operation and high detecting accuracy, all aspects involved in solar cell surface defect detection methods based on machine vision were reviewed in this paper. First of all, the various imaging techniques and common defect types of solar cells surface were summarized. Secondly, the existing detection methods were introduced and compared with each other according to the different idea of mathematical modeling. Finally, a brief summary of this article and perspective of future research are presented. It can be concluded that the solar cell surface defect detection methods based on machine vision have made great progress. However, there is still room for improvement in algorithm design of feature extraction, such as feature extraction algorithm based on deep neural networks.