Research On Compaction Detection Technology Of Subgrade And Base Based On Acceleration

Compaction is a key process to ensure the quality of highway construction and extend its service life.Traditional compaction degree detection methods are insufficient in terms of comprehensive and efficient detection.Intelligent compaction detection technology greatly improves detection efficiency and accuracy,which is of great significance for ensuring the compaction quality of subgrade and pavement.Currently,intelligent compaction detection technology mostly uses intelligent rollers,which are expensive.Furthermore,the mechanical indicators are not yet fully developed.An intelligent compaction detection system was built using simple equipment in this paper,and its application in the subgrade and base layer was studied based on the Funai Expressway project of China Railway 17 th Bureau Group.The main research work and conclusions are as follows:(1)Combining with the working principle of a vibratory roller,the compaction process can be simplified into a single degree of freedom(SDOF)model and a double degree of freedom(DDOF)model,representing the interaction between the vibrating wheel and the soil base/subgrade.The corresponding dynamic equations are established accordingly.By solving the dynamic equation of the SDOF model,it is found that the resistance of the fill material is related to the acceleration of the vibrating wheel,which increases as the acceleration of the vibrating wheel increases.By solving the dynamic equation of the DDOF model,it is discovered that the acceleration of the vibrating wheel is related to the stiffness and damping of the compacted fill material.As the stiffness increases and the damping decreases,the compaction degree increases.To solve mechanical indicators,decoupling of stiffness and damping is needed.(2)By adjusting the simulation parameters of the compacted fillers,a double-degree-offreedom model was established and simulated using MATLAB/SIMULINK software.The acceleration of the vibrating roller was analyzed as a function of the stiffness and damping of the compacted fillers.It was found that stiffness was the main factor affecting the acceleration of the vibrating wheel,while changes in damping had little impact.Based on this characteristic,the decoupling of the mechanical indicators’ dynamic equations was achieved by setting the damping to the standardized median value,and a direct relationship between acceleration and stiffness was established.The evaluation indices in this study included stiffness,acceleration domain indices,and frequency domain indices.(3)An intelligent compaction detection system has been developed based on an accelerometer sensor.The system consists of three main parts: data acquisition,computation and analysis,and compaction degree detection.The development of the system involves accelerometer data collection,preprocessing,evaluation index calculation,graph plotting,and frontend design.Preprocessing,evaluation index calculation,and graph plotting are all implemented using MATLAB code.The frontend design of the system uses a hybrid programming approach of MATLAB and C#,where C# language is used to call.M files for the fast processing of raw accelerometer data.(4)Indoor tests for subgrade soil and on-site tests for acceleration signals,sand filling,and visual determination of compaction degree were conducted on the subgrade and cement stabilized crushed stone base of a physical engineering project.Based on the test results,the temporal and spectral indicators of acceleration,mechanical properties,and their variation with the number of compaction cycles were analyzed for the subgrade and base test sections.Correlation fitting was performed between the significant indicators and the compaction degree,and the fitted formula was used to predict the compaction degree,which was compared with the actual measured compaction degree and visually evaluated.The test results show that both the acceleration time-domain index and mechanical index increase with the number of compaction passes,while the relationship between acceleration frequency-domain index and the number of compaction passes is not significant.The relationship equation between acceleration time-domain index,stiffness,and compaction degree has a coefficient of determination greater than 0.9 and can be used for on-site compaction degree prediction.Visual evaluation of compaction degree can effectively identify areas of insufficient compaction in the test section,thereby improving the quality of compaction.