Multi-stage diagnostic and characterization framework for bored pile defects driven by distributed thermo-mechanical sensing fingerprints

To overcome the non-uniqueness of defect signatures in Thermal Integrity Profiling (TIP) for bored pile evaluation, this paper proposes a systematic defect identification framework utilizing Distributed Fiber Optic Sensing (DFOS) for temperature-strain dual-parameter fusion. Large-scale model pile experiments were designed to simulate seven representative defects, including necking, bulging, soil inclusion, voids, stone inclusion, water inclusion, and broken piles. Temperature and strain data with high spatial and temporal resolution were continuously recorded during the concrete hydration process. The study elucidates the response mechanisms of different defects under thermo-mechano-chemical coupling during hydration. In the thermal dimension, bulging manifests as abnormally high temperatures, broken piles exhibit a temperature inversion pattern, and water inclusion shows a peak temperature hysteresis. To eliminate the identification ambiguity among defects characterized by low-temperature anomalies—namely necking, soil inclusion, and stone inclusion—and to remove the detection blind spot of voids associated with a single thermal parameter, the strain parameter was introduced into the analytical framework in this study. The results demonstrate significant strain concentrations induced by voids, necking, and soil inclusions, in stark contrast to the strain inhibition caused by stone inclusions. Circumferential strain uniformity effectively separates necking from soil inclusions. A multi-stage fingerprint matrix based on thermo-mechanical sensitivity was established to precisely identify and differentiate these defects. These findings provide a novel theoretical foundation and technical support for the smart monitoring and preventive maintenance of underground infrastructures.