Classification of shot peening coverage based on deep learning technologies

Abstract

Shot peening is a cold working process widely used in the aerospace industry, currently, the shot peening process involves mainly an inspector performing visual inspection using a 10x magnifier and comparing the mental visual with an image reference. The state-of-art-technology for coverage inspection involves deep learning. However, there have been no implementing of an automated coverage inspection system using Deep Learning technology. Hence, this paper aims to explore and evaluate different convolutional neural network architecture to evaluate the functionality and performance of a vision inspection system.