Thin film uniformity detection of solar wafers based on improved DeepLab v3+ and infrared thermal imaging technology

This paper discusses the importance and challenges of thin film uniformity inspection during wafer fabrication, and proposes a new solar wafer thin film uniformity inspection method that combines the improved DeepLab v3+ model and infrared thermal imaging technology. The images of wafer surface temperature distribution after deposition in PECVD process recorded by FLIR T860 equipment and image preprocessing are utilized to constitute the infrared imaging dataset of the wafer surface; based on the original model of DeepLab v3+, the backbone network is replaced with MobileNet v3, and the BAM attention mechanism is added to enhance the computational efficiency and feature extraction capability. The improved model significantly reduces computational complexity and memory consumption. Experiments are conducted with the wafer surface temperature distribution images recorded by FLIR T860 device as the data source, and the experiments show that the improved DeepLab v3+ model outperforms the original DeepLab v3+ model in all evaluation indexes, and the accuracy, MIoU, and detection time reach 91.2%, 85.3% and 25ms/image, respectively.