Vision system based on deep learning for product inspection in casting manufacturing: Pump impeller images

Abstract

Products inspection is important issues in casting manufacture, because it is the final process before sending products to customers. To prevent a mistake from human operating error, vision systems are widely applied into this process nowadays. However, these systems still have some disadvantages which are sensitive to lightning and setup conditions. In this paper, the proposed approach for products inspection of submersible pump impeller images by the vision system based on deep learning with convolutional neural network architecture for casting manufacture is significant. It achieves the high accuracy of results as 99.7% on the top view of submersible pump impeller images dataset and requires less computational power and time. Moreover, it takes only 56.87 milliseconds for predicting one image. For proposing more details about this research, the submersible pump impeller images dataset is firstly presented. Subsequently, convolutional neural network, methods, evaluation and results are presented. Finally, all works in this study are summarized.