A strategy for locating and tracking pipeline inspection gauge (PIG) in the pipeline via phase-sensitive optical time domain reflectometry (φ-OTDR) and you only look once v5 (YOLOv5) target detection algorithm is proposed.Vibration will be generated when the cups at both ends of the PIG collide with the welding seam of the pipeline.The φ〖ＷＴＢＺ〗-OTDR technology can be used to collect the vibration signal and present an "inverted V" feature that distinguishes it from other background noises on the space-time map.A training set and a test set are constructed by obtaining a large number of space-time maps containing "inverted V" features.The training set is used to train the YOLOv5 network model,and the test set is used to test the trained YOLOv5 network.The trained model is proved to be able to accurately capture the "inverted-V" feature in the space-time map,thereby inverting the real-time position and path of the PIG.The distributed optical fiber sensor and neural network algorithm are combined to further improve the convenience and accuracy of PIG positioning and tracking,which is conducive to the realization of PIG online and automatic tracking.