Research On The Technology Of Monitoring And Quality Evaluation Of The Cooperative Construction Of Asphalt Pavement

The construction quality of asphalt pavement has a direct impact on the stability and durability of road usage.The control and management of traditional asphalt pavement construction processes and pavement performance testing mainly rely on supervision and paper reports.Although some information platforms are used,monitoring data is only used for recording purposes,which leads to problems such as delayed quality control during the construction process and insufficient use of informationized data.Therefore,under the support of the Shaanxi Provincial Department of Transportation Science and Technology Research Project "Information Technology Research on Intelligent Highway Construction and Operation Management(21-04X)",A set of asphalt pavement cooperative construction monitoring scheme was designed,established pavement performance prediction model and asphalt pavement cooperative construction quality evaluation model based on material test and production monitoring data,and realizes the process control of pavement performance and construction quality.It has positive practical significance in improving project management efficiency.Firstly,the requirements for data collection and monitoring management at various stages of asphalt pavement production and construction technology are analyzed,and an overall plan for collaborative construction monitoring and quality evaluation of asphalt pavement covering "construction management,construction technology,performance testing,mixing production,and material transportation" was designed.Further,the pavement collaborative construction module is designed and implemented.Secondly,based on the experimental and production data collected by the monitoring module,a multiple linear regression prediction model for asphalt pavement performance was constructed using Spearman+Principal Component Analysis(PCA)preprocessing optimization.The correlation coefficients between the predicted stability and flow values of the core Marshall test and the actual values were as high as 0.959 and 0.811,respectively.Both are significantly superior to traditional Back Propagation(BP)neural networks and Spearman+PCA preprocessing optimized BP neural networks,proving that this model is suitable for predicting road performance tests and solving the problem of delayed road performance test results.Finally,by analyzing the logical relationship between evaluation indicators and combining various technical standards and specifications for asphalt pavement construction,a DPSIR(Drive Pressure State Impact Response)asphalt pavement collaborative construction quality evaluation index system was established.This system can analyze and divide the evaluation indicators according to the relationship between construction management,construction technology,and pavement performance,and evaluate the quality of asphalt pavement construction from four aspects: driving pressure,state,impact,and response.Through the use of this evaluation index system,it is possible to comprehensively evaluate the quality of asphalt pavement construction and improve project management effectiveness.The asphalt pavement collaborative construction monitoring module designed has achieved good results in engineering application validation,providing data support for pavement performance prediction and construction quality evaluation.The established asphalt pavement collaborative construction quality evaluation system serves as the basis for guiding production and construction,and is of great significance for maximizing the benefits of informationized platform collaborative construction,ensuring the systematic,scientific,and modernized decision-making of highway construction management.