基于Rayleigh波频散特征的路基模量反演成像方法与试验研究

路基动态回弹模量是影响路基路面结构耐久性与稳定性的关键参数之一。为了实现路基动态回弹模量无损检测精细化，基于Rayleigh波在弹性层状体系中的传播特性，揭示了Rayleigh波在基准路基路面结构中的理论频散特征，并通过显式瞬态动力有限元方法对路基路面结构体系中Rayleigh波场响应进行了数值计算，结合频域波数域变换法与相位移法建立了路基路面结构中Rayleigh波频散曲线的联合提取方法。通过将提取的Rayleigh波频散曲线按自适应遗传算法反演的路面各结构层模量值作为已知约束条件，进一步对路基工作区细化分层，以此建立了路基工作区动态回弹模量的反演成像方法。通过在足尺道路试槽内点对点依次进行Rayleigh波、FWD、承载板和弯沉测试，建立了各测试结果之间的相关关系。研究结果表明：Rayleigh波反演的路基动态回弹模量与其他测试方法相应结果的判定系数R²均大于0.85，且反演成像结果能够全面、清晰地反映路基的承载能力与压实质量。研究成果可为路基路面工作特性智能感知方法与技术的发展提供理论参考。

Inversion Imaging Method and Experimental Study of Subgrade Modulus Based on Rayleigh Wave Dispersion Characteristics

The dynamic resilient modulus of a subgrade is a key parameter that affects the durability and stability of the subgrade and pavement structure. To realize the refinement of nondestructive sensing of the subgrade dynamic modulus of resilience, based on the dispersion theory of Rayleigh waves in an elastic layered system, this study revealed the theoretical dispersion characteristics of Rayleigh waves in the reference structure of the subgrade and pavement. The Rayleigh wave field response in a subgrade pavement structure system was numerically calculated using the explicit transient dynamic finite-element method. Combined with the frequency-wavenumber domain transformation and phase-shift method, a joint extraction method for the dispersion curve of Rayleigh waves suitable for subgrade and pavement structures was established. The extracted dispersion curve of the Rayleigh wave was fitted by an adaptive genetic algorithm back analysis to obtain the modulus of each pavement layer, which was considered a known constraint condition. The roadbed work area was further refined and layered, and an inversion imaging method of the dynamic resilient modulus field in a roadbed work area was developed. The Rayleigh wave, FWD, bearing plate, and deflection tests were carried out point-to-point in a full-scale road test slot, and the correlation between the test outcomes was established. The results show that all determination coefficients between the dynamic resilient modulus of a subgrade inverted by a Rayleigh wave and the outcomes corresponding to other test methods are greater than 0.85, and the inversion imaging results can fully and clearly reflect the bearing capacity and compaction quality of the subgrade. The research results provide a theoretical reference for the development of smart sensing methods and technologies for subgrade and pavement working characteristics.