Research On Intelligent Inversion Of Dynamic Modulus Of Roadbed Pavement Based On Rayleigh Wave Dispersion Characteristics

As an important mechanical parameter to evaluate the bearing capacity of road,the dynamic modulus directly affects the service life of the whole road structure.Therefore,how to scientifically and reasonably obtain the dynamic modulus of each structural layer of the road to analyze and evaluate its structural bearing capacity has become the primary task of the performance evaluation of the subgrade and pavement structure.At present,the main method to obtain the dynamic modulus of the road structure layer is to establish the relevant theoretical analysis model and perform modulus inversion based on dynamic deflection data such as FWD.However,the existing problems are as follows: the established theoretical analysis model is mostly static,and the mechanical response of the driving load is dynamic response,which leads to a certain difference between the evaluation results and the actual working conditions.Most of the modulus inversion algorithms use heuristic algorithms such as genetic algorithms.The main shortcomings are long calculation time,poor reproducibility of inversion results,and weak data batch processing capabilities.In view of the above problems,this thesis studies the dispersion characteristics of Rayleigh wave in road layered structure based on elastic dynamics theory.According to the data characteristics of Rayleigh wave dispersion data,different neural network inversion models are constructed for simulation analysis,and the trained model is used to invert the modulus of the measured data.The correlation between the inversion results and the results of different field test data is analyzed.The feasibility,rationality and effectiveness of the intelligent inversion method are verified from both theoretical and practical applications.The main research contents and conclusions of this thesis are as follows:(1)By analyzing the influence of the modulus,thickness and density of each structural layer of the road on the theoretical dispersion curve,the theoretical dispersion characteristics of Rayleigh wave in the layered structure of the road are studied.The research shows that the modulus of each structural layer has the greatest influence on the dispersion characteristics of road Rayleigh wave,followed by the thickness,and the density has the least influence.(2)By studying the modulus sensitivity of the theoretical dispersion curve,the corresponding sensitive frequency band response range of each structural layer of different typical subgrade pavement structure models is analyzed.In addition,the typical subgrade and pavement structure model is refined and layered,and its equivalence is analyzed by calculating the theoretical dispersion curve before and after the refinement.It is found that the road Rayleigh wave dispersion data have significant spatial correspondence characteristics,and the theoretical dispersion curve is consistent before and after the road structure is refined and layered,which is equivalent.(3)Based on the Rayleigh wave dispersion characteristics,the neural network inversion model is studied by establishing the mapping relational database between the modulus of each layer of different road structures and the Rayleigh wave dispersion curve.The simulation results show that the different neural network inversion models can realize the intelligent inversion of the dynamic modulus of subgrade and pavement,and the inversion speed is fast and the inversion result is unique.In addition,the neural network inversion model based on the optimization of road structure refinement and stratification can not only solve the problem of universality of the model in dealing with different road structure design,but also improve the vertical resolution of the detection area.(4)The Rayleigh wave test,FWD test and indoor impact echo test of core specimens were carried out on the full-scale forming test section,and the intelligent inversion results of PMCNN-LSTM inversion model were compared with FWD test results and indoor impact echo test results.The results show that the intelligent inversion results can show good correlation with the test results of FWD and indoor impact echo,and the correlation coefficient is greater than 0.85.