Evolution Characteristics of the Surface Texture of the Wearing Coat on Asphalt Pavement Based on Accelerated Pavement Polishing

2021 ◽  
Author(s):  
Shiyu Zhu ◽  
Xiaoping JI ◽  
Yun Chen ◽  
Hangle Li ◽  
Xinquan Xu
Keyword(s):  
Surface Texture ◽  
Asphalt Pavement ◽  
Evolution Characteristics

Measuring surface texture of in-service asphalt pavement: evaluation of two proposed hand-portable methods

2021 ◽  
pp. 1-17
Author(s):  
Glenn R. Matlack ◽  
Andrea Horn ◽  
Aldo Aldo ◽  
Lubinda F. Walubita ◽  
Bhaven Naik ◽  
...  
Keyword(s):  
Surface Texture ◽  
Asphalt Pavement ◽  
Measuring Surface ◽  
Pavement Evaluation

Characterization of Asphalt Pavement Surface Texture

2012 ◽  
Vol 2295 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Timothy Miller ◽  
Daniel Swiertz ◽  
Laith Tashman ◽  
Nader Tabatabaee ◽  
Hussain U. Bahia
Keyword(s):  
Spectral Analysis ◽  
Surface Texture ◽  
Asphalt Pavement ◽  
Friction Characteristics ◽  
Frictional Properties ◽  
Pavement Surface ◽  
Analysis Methods ◽  
Texture Parameters ◽  
Laser Profiling

This paper presents improved analysis methods for characterizing asphalt pavement surface texture and focuses on the use of laser profiling techniques to estimate friction characteristics. Derived from signal processing theories, texture spectral analysis methods show promise for improving characterization of the tire–pavement interface. Texture parameters measured with spectral analysis techniques represent a means for quantifying surface properties. Current methods to analyze frictional properties rely on the mean profile depth (MPD) and mean texture depth (MTD) texture parameters. Although these parameters are used widely, they do not capture the range and distribution of surface asperities on the pavement surface. Knowing the distribution of surface asperities is critical for assessing friction characteristics. Thus, texture spectral analysis methods are anticipated to improve on the MPD and MTD parameters by capturing relevant texture-level distributions. This study investigates the applicability of laser profiling systems for measuring pavement surface texture and subsequent relationships to friction. Models accounting for aggregate and mixture properties are developed and related to texture parameters through analysis of constructed field sections and corresponding laboratory samples. Results indicate that stationary laser profiling systems can capture the microtexture and macrotexture spectrum and suggest that a comprehensive friction characterization of asphalt mixtures can be obtained in a laboratory setting. With this analysis system, it is believed that asphalt mixture designers will have an improved tool by which to estimate pavement surface texture and frictional properties.

scholarly journals Acquisition method of asphalt pavement texture information based on the CPR Technology

2019 ◽  
Vol 275 ◽  
pp. 04003
Author(s):  
Chen Jiaying ◽  
Zheng Binshuang ◽  
Chen Xi ◽  
Zhao Runmin ◽  
Huang Xiaoming
Keyword(s):  
Real Time ◽  
Surface Texture ◽  
Laser Scanning ◽  
Asphalt Pavement ◽  
Road Surface ◽  
Root Mean Square Roughness ◽  
Scanning Method ◽  
Close Range Photogrammetry ◽  
Texture Information ◽  
Close Range

In order to obtain the asphalt pavement texture information in real time and accurately monitor the anti-skid performance of the road pavement, an automatic close range photogrammetry system (ACPR system) was proposed and built based on the circle arranged three cameras close range photogrammetry (CPR) technology to obtain the asphalt pavement surface texture. Automatic image acquisition and 3D reconstruction were achieved by the ACPR system. Sand patch method and laser scanning method (ZGScan) were used to collect the on-site comparison test of the asphalt pavement texture. Mean texture depth (MTD) and root mean square roughness (RSMR) were chosen as the statistical indicators of road surface texture. The results show that the texture data obtained by ACPR system has relatively high accuracy and efficiency, and the recognition accuracy is close to 0.02mm. The ACPR system improves the efficiency and accuracy of traditional close range photogrammetry and provides real-time and effective road surface anti-skid information for subsequent safety braking of autonomous vehicle.

The Improvement of PQI Density Testing Method of Considering Texture Depth of Asphalt Pavement

2013 ◽  
Vol 718-720 ◽  
pp. 1914-1918
Author(s):  
Chuang Min Li ◽  
Tai De ◽  
Zhi Yong Chen
Keyword(s):  
Measurement Error ◽  
Surface Texture ◽  
Asphalt Pavement ◽  
Core Sample ◽  
The Road ◽  
Average Value ◽  
The Core ◽  
Testing Method ◽  
Maximum Measurement ◽  
Maximum Measurement Error

In recent years, nondestructive testing is applied more and more widely on the road detection, PQI as a kind of advanced testing equipment in asphalt pavement detection, it has been paid great attention by the road testing personnel. Based on the analysis of the densities which measured by PQI of different types of asphalt pavement, it sums up that the surface texture depth of asphalt pavement significantly affects the measuring accuracy of the density of PQI. In this paper, it suggests to use sand to fill the surface texture depth of asphalt pavement combining with PQI for pavement density measurement. Field testing shows that, compared with the bulk density of core sampling method, the density measured by PQI has obviously been affected by the surface texture depth of asphalt pavement. As the surface texture depth of the asphalt pavement is deeper, the error between the two methods is larger. Considering the influence of texture depth, the author improved the PQI detection method. The improved method shows that, compared with the bulk density of the core sampling, the coefficient of variation of the original testing method is 10.2%, and the new method is 3.8%. In the original testing method , it use the average value of the core sample densities as the compensation value of PQI measurement in the degree of compaction testing, and the maximum measurement error reached up to 2.2%. While, the improved testing method use the average value of the core sample densities as the compensation value of PQI measurement, the maximum measurement error reduces to 0.7%, the accuracy of the testing result is significantly improved.

scholarly journals Assessing Surface Texture Features of Asphalt Pavement Based on Three-Dimensional Laser Scanning Technology

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 623
Author(s):  
Bo Chen ◽  
Chunlong Xiong ◽  
Weixiong Li ◽  
Jiarui He ◽  
Xiaoning Zhang
Keyword(s):  
Control System ◽  
Surface Area ◽  
Surface Texture ◽  
Laser Scanning ◽  
Asphalt Pavement ◽  
Asphalt Mixture ◽  
Three Dimensional ◽  
Texture Features ◽  
Road Surface ◽  
Asphalt Pavements

Pavement surface texture features are one of key factors affecting the skid resistance of pavement. In this study, a set of stable and reliable texture measurement equipment was firstly assembled by using the linear laser ranging sensor, control system and data acquisition system. Secondly, the equipment was calibrated, and the superposition error of sensor and control system was tested by making a standard gauge block. Thirdly, four different kinds of asphalt mixture were designed, and their surface texture features were obtained by leveraging a three-dimensional laser scanner. Therefore, the surface texture features were characterized as one-dimensional profile features and three-dimensional surface features. At the end of this study, a multi-scale texture feature characterization method was proposed. Results demonstrate that the measurement accuracy of the laser scanning system in the x-axis direction can be controlled ranging from −0.01 mm to 0.01 mm, the resolution in the XY plane is 0.05 mm, and the reconstructed surface model of surface texture features can achieve a good visualization effect. They also show that the root mean square deviation of surface profiles of different asphalt pavements fluctuates greatly, which is mainly affected by the nominal particle size of asphalt mixture and the proportion of coarse aggregate, and the non-uniformity of pavement texture distribution makes it difficult to characterize the roughness of asphalt pavement effectively by a single pavement surface profile. This study proposed a texture section method to describe the 3D distribution of road surface texture at different depths. The macrotexture of the road surface gradually changes from sparse to dense starting from the shallow layer. The actual asphalt pavement texture can be characterized by a simplified combination model of “cone + sphere + column”. By calculating the surface area distribution of macro and microtextures of different asphalt pavements, it was concluded that the surface area of asphalt pavement under micro scale is about 1.8–2.2 times of the cutting area, and the surface area of macrotexture is about 1.4 times of the cutting area. Moreover, this study proposed texture distribution density to characterize the roughness of asphalt pavement texture at different scales. The SMA index can represent the macroscopic structure level of different asphalt pavements to a certain extent, and the SMI index can well represent the friction level of different asphalt pavements.

scholarly journals Study on Asphalt Pavement Surface Texture Degradation Using 3-D Image Processing Techniques and Entropy Theory

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 208 ◽  
Author(s):  
Yinghao Miao ◽  
Jiaqi Wu ◽  
Yue Hou ◽  
Linbing Wang ◽  
Weixiao Yu ◽  
...  
Keyword(s):  
Surface Texture ◽  
Asphalt Pavement ◽  
Three Dimensional ◽  
Entropy Theory ◽  
Pavement Surface ◽  
Vehicle Load ◽  
Road Surfaces ◽  
Physical Information ◽  
Processing Techniques ◽  
Decay Behavior

Surface texture is a very important factor affecting the anti-skid performance ofpavements. In this paper, entropy theory is introduced to study the decay behavior of thethree-dimensional macrotexture and microtexture of road surfaces in service based on the field testdata collected over more than 2 years. Entropy is found to be feasible for evaluating thethree-dimensional macrotexture and microtexture of an asphalt pavement surface. The complexityof the texture increases with the increase of entropy. Under the polishing action of the vehicle load,the entropy of the surface texture decreases gradually. The three-dimensional macrotexture decaycharacteristics of asphalt pavement surfaces are significantly different for different mixturedesigns. The macrotexture decay performance of asphalt pavement can be improved by designingappropriate mixtures. Compared with the traditional macrotexture parameter Mean Texture Depth(MTD) index, entropy contains more physical information and has a better correlation with thepavement anti-skid performance index. It has significant advantages in describing the relationshipbetween macrotexture characteristics and the anti-skid performance of asphalt pavement.

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