Methodology and field implementation of pavement cavity detection via falling-weight acceleration

Subsurface cavity detection in cement pavements remains challenging despite advanced non-destructive techniques. This study develops and validates an automated impact detection methodology using acceleration signatures through integrated mechanisms, experimental, and field investigations. Hertz contact theory established the research foundation, demonstrating univariate correlation between peak acceleration ( a _max) and structural modulus ( E ₂). Laboratory tests with controlled cavities confirmed cavity-induced acceleration attenuation up to 48% in low-stiffness materials, with material elasticity governing detection sensitivity. Field validation included: 1) Instrumented test sections showing 27% acceleration reduction (1100 → 800 g) with increasing cavity size (0 → 40 cm). 2) Shaanxi highway deployments achieving 94.2% detection accuracy using a 1200 g threshold. 3) DAXIN highway slab corner diagnosis via 450 g threshold, enabling targeted grouting (95.1% recovery efficacy). The intelligent Falling Weight Acceleration (FWA) system was engineered for operational deployment, featuring real-time geospatial mapping, cloud-based analytics, and automated impact sequencing. Closed-loop verification demonstrated >95% cavity resolution through polymer grouting, with 75% of treated points exhibiting 10-40% acceleration recovery. These findings support the feasibility of impact-acceleration–based cavity screening and demonstrate its reliability in the investigated engineering cases.