GASF-ConvNeXt-TF Algorithm for Perimeter Security Disturbance Identification Based on Distributed Optical Fiber Sensing System

作者：Yajun Wang, Zhuo Wen, Bin Liu, Juan Liu, Yingying Hu, Yue Fu, Wenbo Xiao, Xingdao He, Jinhui Yuan, Qiang Wu · 发表于：IEEE Internet of Things Journal · 年份：2024 · DOI：10.1109/jiot.2024.3360970 · 被引用次数：30 · 研究领域：Advanced Fiber Optic Sensors、Structural Health Monitoring Techniques、Advanced Optical Sensing Technologies

φ-OTDR technology can transform the fiber optic cable into a large-scale sensor array for distributed acoustic sensing (DAS), which is an emerging infrastructure for the Internet of Things. However, it’s limitated in event recognition capability, which is a major factor preventing its practical field application. This paper proposes a perturbation recognition algorithm based on GASF-ConvNeXt-TF with fast process and high recognition accuracy. Firstly, GASF (Gramian angular summation field) algorithm is used to encode external disturbance signal to transform the one-dimensional time series signal into a more concentrated two-dimensional image feature. Then the CNN model ConvNeXttiny network is applied as the classifier. In order to prevent the weight gradient from oscillating back and forth during network training process, a cosine annealing algorithm is introduced to control the decay of the learning rate. Meanwhile, transfer learning is used to further optimize the network model, resulting in higher classification accuracy and faster convergence. Finally, two different experimental scenarios are arranged in a total length of 2.2 kilometers of optical fiber cable, and six different disturbance events (shaking, kicking, knocking, trampling, wheel rolling, and impacting) are set. Different from previous perimeter security disturbance identification experiments, not only single-point disturbance recognition is performed, but also two points disturbances are simultaneously recogn...