[IEEE 2019 IEEE International Conference on Smart Internet of Things (SmartIoT) - Tianjin, China (2019.8.9-2019.8.11)] 2019 IEEE International Conference on Smart Internet of Things (SmartIoT) - Optical Fiber Defect Detection Method Based on DSSD Network

摘要： Optical fiber surface defects have diverse features and different complicated factors. Therefore, the surface defect detection method for optical fiber has good generalization performance. Aiming at the problems of low efficiency, long detection time and high false detection rate in the traditional detection methods of fiber defects on the production line, we establish a database containing three kinds of surface defect samples on the fiber and augmented it in order to reduce over-fitting. This paper proposes a fiber surface detection method based on DSSD algorithm. In the convolutional neural network, the basic network ResNet-101 is utilized to enhance the network feature extraction capability and improve the robustness of the algorithm. The experimental data shows that the detection rate based on DSSD algorithm can reach 96.7%, which proves that the designed fiber intelligent defect detection method can not only greatly reduce the detection time, but also improve the detection efficiency and detection accuracy.