A PIG Localization Method Based on Distributed Optical Fiber Vibration Sensing and Image Matching

In-line inspection of long-distance oil and gas pipelines is a critical maintenance measure to ensure pipeline structural integrity and the safe, efficient operation of transportation systems. Nevertheless, the Pipeline Inspection Gauge (PIG) is inevitably at risk of jamming while travelling through pipelines. Therefore, accurate PIG localization is essential for securing in-line inspection operations. Conventional PIG detection techniques fail to achieve full-range continuous positioning and monitoring of PIGs, exhibiting notable technical limitations. To address this issue, this paper proposes a spatiotemporal PIG localization method that combines Distributed Vibration Sensing (DVS) technology with a cross-correlation template-matching algorithm. The innovations of the proposed method are summarized as follows: (1) A DVS system is established. Sliding cross-correlation matching is performed by introducing a standard signal template into the time-frequency waterfall plot to accurately extract spatiotemporal position information of the moving PIG. (2) A physics-driven, training-free localization template is proposed to reduce dependence on labeled data and facilitate deployment across different pipeline sections. (3) The method requires no model training and enables weld-impact event localization through lightweight signal processing. Field experiments using a 40-km DVS system demonstrate its feasibility in the observed pipeline sections. Field experiments using a 40-km DVS system demonstrate the feasibility of identifying and localizing PIG-induced weld-impact events within the experimentally observed pipeline sections.