Distributed fiber optic strain sensing for performance assessment of a large-diameter JPCCP

Distributed fiber optic sensing (DFOS) enables continuous strain monitoring over long-distance underground pipelines, yet a systematic interpretation framework that transforms high-density raw strain measurements into actionable lifecycle performance indicators remains lacking for large-diameter jacking prestressed concrete cylinder pipeline (JPCCP). This study presents a DFOS-based performance assessment framework and applies it to a 52-m section of a deeply buried, 4.8-m diameter JPCCP flood-diversion pipeline. Four longitudinal distributed strain-sensing fibers were installed at the crown, invert, and two springlines using 1-m fixed-point anchoring clamps. A dual-baseline strain increment strategy with Hampel filtering was employed to separate construction-related and operational responses. These strain increments were decomposed into axial and bending components, classified into four dominant response modes by non-dimensional dominance coefficients, and further evaluated using neutral-axis offset indices and joint-influenced equivalent rotation characteristic values. Three key findings emerge: (1) the monitored pipeline exhibits a clear three-stage temporal evolution: construction disturbance release, early operational stabilization, and localized non-uniform response accumulation; (2) three bending-sensitive zones are identified at 11–27 m, 33–37 m, and 45–52 m, with most joint-influenced equivalent rotation values below 0.015°; (3) six key joint-influenced units are identified and classified using monitoring-based priority, among which J1 (persistent high response, max 0.116°) and J10 (delayed activation, max 0.063°) are identified as critical response locations warranting the highest maintenance priority. The proposed framework converts distributed strain-sensing data into interpretable strain-response indicators for performance assessment and maintenance prioritization, offering a practical paradigm for service performance assessment of large-scale underground pipelines.