Development And Application Of Asphalt Pavement Structure Information Data Analysis System

As a typical external structure,the pavement structure is affected by complex environmental factors and vehicle loads during the service process,resulting in a variety of road performance degradation,cracking,rutting and other diseases.Traditional road performance testing methods are mostly discontinuous manual inspections,which can only be detected and repaired after surface damage occurs on the road surface.It is impossible to understand the road performance status and potential damage development status in time.Taking into account the long-term freeze-thaw cycles,alternating high and low temperatures,and the harsh natural conditions of high UV radiation intensity in seasonal frozen ground areas,the road surface is more prone to rutting,cracking and other structural diseases.This study established the asphalt pavement structure information in Tonghua,Jilin Province.Monitoring system to obtain relevant mechanical and environmental parameters in the asphalt pavement service.The monitoring project has accumulated massive data so far.If there is no suitable data processing method,massive data will become a constraint for research.To this end,this study introduced digital signal processing methods and information data processing tools,analyzed signal characteristics of road surface dynamic response data,studied signal abnormality processing methods,and compiled and integrated data processing methods based on MATLAB platform,combined with measured data after processing.Analyze and forecast the temperature condition of asphalt pavement and evaluate the performance status of asphalt pavement.The main research contents and results are as follows:Firstly,the construction process of the asphalt pavement structure information monitoring system in this research project was introduced,including the selection,determination and site burial of sensors;the analysis of the existing original data storage format,and the establishment of the storage original database based on the selected Oracle database management system.Database;and from the perspective of data organization strategy,analyzes the deficiencies in the original data storage format,and proposes an integrated database construction plan for asphalt pavement structure information that meets the requirements of relational database standardization.Secondly,for the problem of abnormal data and excessive data in the signal collected by the asphalt pavement structure monitoring system,combined with the subsequent analysis requirements,based on the theoretical basis of the digital signal processing method,the characteristics of the actual sampling signal and noise in the road surface dynamic response data are analyzed.Differences,study algorithms for noise reduction of compiled signals,effective signal judgment under load,and peak extraction algorithm;compile and integrate relevant digital signal processing method tools on MATLAB/GUI platform,design dynamic response monitoring data processing and analysis software for highway asphalt pavement,provide peak value Density function,correlation analysis and other time-frequency analysis windows,and reserved relevant interfaces for subsequent asphalt pavement performance analysis.Thirdly,based on the field measurement data of the research project,the distribution of temperature field of asphalt pavement was studied.The temperature field changes under special climatic conditions such as rainfall were comparatively studied.The existing two types of asphalt pavement temperature estimation method models were summarized and considered.There are large regional differences in the estimation model.The empirical model is used to fit the existing empirical prediction model,and the existing temperature prediction model is analyzed by determining the coefficient,residual sum of squares,regression sum of squares,and other statistical indicators.Advantages and disadvantages;combined with the principle of road surface heat transfer,a multivariate regression model and a neural network model suitable for the temperature field of asphalt pavement structures in seasonally frozen areas were revised and established.Finally,the dynamic response time-history curves of asphalt pavement under different working conditions of different axial numbers,different temperatures,and different structures are analyzed.For the two types of typical failures of asphalt pavement fatigue cracking and permanent deformation,the asphalt in mainstream design methods at home and abroad is investigated and summarized.Pavement performance prediction model,based on the actual measurement information of the project and indoor test results,establishes the fatigue damage model and rutting damage model of asphalt pavement based on the measured information;combined with the existing software interface,the interface of the measured load information axis is completed based on MATLAB/GUI.The influence of temperature was taken into account in the damage model,and the applicability of the four types of asphalt pavement structures in the seasonal frozen area was analyzed in combination with the damage calculation results.