关键词: 工业零部件, 深度学习, RPN+RCNN检测网络, 定位检测

Abstract: Several object detection problems inevitably occur when the product components are detected in the packaging procedure of the traditional industrial production line, including slow detection speed, low-level automation, and low detection accuracy. To solve these problems, a vision-based industrial objects detection system is established to automatically inspect the product components, which is based on deep learning. Firstly, an experimental platform is designed to obtain the images containing product components. The convolution layer structures shared by the region proposal network and region convolutional neural network are modified. Thus, a novel object detection method is proposed to accurately locate the product components, which can adaptively detect different product components with different shapes and different sizes by means of an end-to-end mode. The experimental results show that the established system is superior to the existing detection methods, which has the advantages of high detection speed and high detection accuracy.

Key words: industrial objects, deep learning, Region Proposal Network and Region Convolutional Neural Network（RPN+RCNN）, location detection