Laboratory application of imaging technology on pavement material analysis in multiple scales: A review

Du, Zhenyu; Yuan, Jie; Zhou, Quan; Hettiarachchi, Chamod; Xiao, Feipeng

doi:10.1016/j.conbuildmat.2021.124619

Cited by 11 publications

(6 citation statements)

References 141 publications

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“…Traditional methods mainly rely on features such as edge detection and colour change, however, these methods are often difficult to achieve accurate crack detection in the complex context of airport pavements. In recent years, deep learning-based methods have gradually gained attention, and through techniques such as convolutional neural networks (CNN), they are able to better capture the features of cracks and improve the accuracy of detection [10] [15].…”

Section: Related Workmentioning

confidence: 99%

The automated segmentation and enhancement of cracks on airport pavements using three-dimensional imaging techniques

Zhai,

2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

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Based on 3D images, this study aims to explore automatic segmentation and enhancement methods for airfield runway surface cracks. Firstly, a typical 2D Gaussian filter is used to remove noise from the road surface data. Then, Steerable Matched Filter (SMFB) is introduced to extract crack features. By constructing a set of 52 SMFB filters with different parameters, we are able to accurately capture cracks with different directions and sizes. After that, Tensor Voting (TV) technique is introduced to further enhance the continuity of the cracks. With this method, we are able to detect and segment the cracks in the airfield runway surface for a more accurate and comprehensive analysis. The experimental results show that the proposed method performs well in crack detection and segmentation, providing strong support for airport pavement maintenance and management.

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Section: Related Workmentioning

confidence: 99%

The automated segmentation and enhancement of cracks on airport pavements using three-dimensional imaging techniques

Zhai,

2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

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“…Furthermore, the DIC method was used for monitoring crack development due to the indirect tensile strength of RAP asphalt specimens [8]. In their review paper, Du et al [9] emphasised the advantages of DIC over linear variable differential transformers due to the unpredictability of the local damage location.…”

Section: Introductionmentioning

confidence: 99%

Pavement Structure Characteristics and Behaviour Analysis with Digital Image Correlation

2023

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Digital image correlation (DIC) is a method of point displacement measurement by an optical system. If two cameras are used for capturing the same point displacement, three-dimensional data are obtained using the 3D-DIC method. The areas of application of this method in pavement construction are diverse, but it is mainly used for displacement monitoring during standard tests of the failure of specimens due to load application. Furthermore, DIC technology was used only for testing particular material characteristics and assuming their influence on the overall pavement system. Within this research, DIC was applied in two areas: defining material mechanical characteristics and analyses of pavement structure behaviour under cyclic loading. The scope of this research was to gain more insights into DIC’s potential application within pavement behaviour analyses, specifically on cement-bound granular material (CBGM) characterisation. Results from this study confirm the suitability of 3D-DIC technology for pavement material characterisation. Furthermore, it is shown that certain trends of material behaviour defined on the simple material level of each independent pavement layer will significantly differ when it is placed in the system, and this kind of complex analysis is possible by using 3D-DIC technology.

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“…The conventional method calculates the ratio of the volume of the air void content in the mixture to that of the whole mixture containing both solids and air voids [21]. With hightech approaches, such as computerized tomography (CT) [22,23], air void details, such as their size and distribution in an asphalt mixture, can be characterized and analyzed. CT is a meso-structure testing approach that provides details on voids inside of samples to determine and evaluate the size and number of voids [24].…”

Section: Introductionmentioning

confidence: 99%

Calculation and Characterization of Air Void in Mortar of the Hot Mix Asphalt (HMA) Based on CT Scanning and Image Analysis Methods

Shu

Jiang

et al. 2023

Applied Sciences

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The air void content is one of the most important volumetric properties of asphalt matrixes, such as asphalt mixtures or mortars, because it can greatly affect the performance of the matrix. At the mixture level, there are standardized methods for measuring the air void content, which is an important design parameter of a mixture. However, at the mortar scale, no unified method has been proposed to determine the air void content corresponding to the asphalt mixture. Therefore, this research aims to, first, characterize the air void distribution within the mortar of an asphalt mixture and then develop an updated theoretical method for calculating the air void content of asphalt mortar. The internal structures of air voids from three commonly used asphalt mixtures with different gradations were captured using an industrial CT scanning technique and then morphologically characterized using the image analysis method. Three-dimensional models of the air voids were reconstructed, and the air void content calculated from the CT images was also verified by density tests. The scanning results show that the air void content and air void size fit the cumulative Weibull curve. The results show that the nominal maximum particle size (NMPS) of mortar and the mixture air void content were the main parameters that affected the mortar’s air voids. The mortar air void content had linear relationships with both the mixture air void content and the mixture asphalt aggregate ratio. The mortar air void content was more sensitive to the NMPS of the asphalt mixture compared with the air void content or asphalt aggregate ratio of the mixture. This research provides a quantitative method to calculate the air void content of asphalt mortar within a mixture, which may help in the matrix design of mortar.

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Laboratory application of imaging technology on pavement material analysis in multiple scales: A review

Cited by 11 publications

References 141 publications

The automated segmentation and enhancement of cracks on airport pavements using three-dimensional imaging techniques

The automated segmentation and enhancement of cracks on airport pavements using three-dimensional imaging techniques

Pavement Structure Characteristics and Behaviour Analysis with Digital Image Correlation

Calculation and Characterization of Air Void in Mortar of the Hot Mix Asphalt (HMA) Based on CT Scanning and Image Analysis Methods

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