| The extra-long or long tunnel concrete pavement is repeatedly worn by heavy-duty trucks,which often leads to rapid deterioration of the pavement macrotexture,which seriously affects driving safety,causing frequent traffic accidents and affecting road traffic capacity.At present,the roughening treatment of tunnel concrete pavement is mainly to improve the surface macrotexture by grooving,milling and overlaying,and upgrade the service level of the pavement.However,it is often restricted by factors such as “mirror grooving” and tunnel elevation limit,resulting in poor practical application.In order to improve the macrotexture of wet road surface more quickly and economically,this paper studies the characterization and deterioration of the macrotexture of micro-milling pavement on the Sichuan Guanggan highway wet pavement improvement project.In this paper,the high-precision and high-density three-dimensional(3-D)point cloud data of micro-milled tunnel cement pavement were collected by using vehicle laser detection system.Considering 3-D data characteristics,invalid data repairing and the frequency domain filtering were preprocessed,the database of full-lane macrotexture index under long-term detection was established.On this basis,the macrotexture characterization and deterioration of micro-milled tunnel cement concrete pavement was studied in details.Based on the measured high-density and high-precision point cloud data of 3-D laser,the basic flow of least squares reference surface calibration-regular grid interpolation-point cloud implicit connection-color mapping was established by using the compiler environment of python3.Thus the freely interacting and 3-D visualization model of the milling surface was constructed.The texture characteristics of different regions after micromilling were analyzed by using the Ridge-to-valley difference(RVD)index,then the location and area of the bad micromilling area were determined.On this basis,three sample segments with high quality of micro-milling were selected,and the correlation between Mean-texture-depth(MTD)by laser methon and electric sand patch method was calculated under the approximate width of 50 mm and 100 mm.In addition,the accuracy of MTD index detected by 3D was verified.The distribution trends and correlations of MTD and ISO-25178 specifications indicators(Sa,Sq,Sdq,Sdr,Spd and Spc)were compared.The correlation between MTD and Spd is only 0.36,which indicates that the two indicators are used for macro-texture characterization of micromilled surface.The information is less repetitive.Based on the three-time detection data,the average amplitude variation of each frequency band is calculated,and the deterioration frequency domain variation characteristics of the macrotexture in the longitudinal direction at the wheel track are revealed.The MTD grade was assessed according to the specifications,and 13% of the regions were assessed as relatively poor and poor after 24 months.The spatial deterioration trend is analyzed by probability density distribution and box plot,which indicates that the MTD value at the wheel track is significantly smaller than that of the non-wheel track,and the lowest MTD value is offset from the centerline of the road by 100-200 mm.This paper shows that the full-lane and long-term detection based on 3D laser technology can comprehensively and accurately characterize the macrotexture deterioration trend of tunnel concrete pavement,and provide a basis for tunnel traffic safety risk assessment. |
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