A novel pavement mean texture depth evaluation strategy based on three-dimensional pavement data filtered by a new filtering approach. (15th December 2020)
- Record Type:
- Journal Article
- Title:
- A novel pavement mean texture depth evaluation strategy based on three-dimensional pavement data filtered by a new filtering approach. (15th December 2020)
- Main Title:
- A novel pavement mean texture depth evaluation strategy based on three-dimensional pavement data filtered by a new filtering approach
- Authors:
- Liang, Jia
Gu, Xingyu
Chen, Yizheng
Ni, Fujian
Zhang, Tianjie - Abstract:
- Abstract: Automatic pavement inspection is a reliable strategy to evaluate pavement conditions. Generally, the skid resistance of asphalt pavement is employed to characterize the pavement surface characteristics. The mean texture depth (MTD) of pavement is a crucial metric to characterize the macrotexture of asphalt pavement. The primary aim of this article is to evaluate pavement MTD. To evaluate this parameter based on three-dimensional (3-D) point cloud data extracted from a self-developed 3-D detection system, a novel filtering method and reference surface integral method were proposed. The novel filtering method was first employed to eliminate the isolated noise of the extracted 3-D point cloud data and was compared with the primary surface profile (PSP)-based filtering method. Then, a 3-D virtual model of pavement texture was generated based on the filtered 3-D data. Finally, a novel method, the reference surface integral, was proposed to evaluate the pavement MTD. The evaluated results were compared with the results measured via manual sand-patch testing. The results show that the novel filtering method performs better filtering performance than PSP-based filtering. The error between the evaluated MTD and the measured MTD is within 3.28%, which demonstrates that the proposed filtering method and MTD evaluation method have robust advantages and can be employed to evaluate pavement performance.
- Is Part Of:
- Measurement. Volume 166(2020)
- Journal:
- Measurement
- Issue:
- Volume 166(2020)
- Issue Display:
- Volume 166, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 166
- Issue:
- 2020
- Issue Sort Value:
- 2020-0166-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-12-15
- Subjects:
- Pavement engineering -- Mean texture depth -- Point cloud data -- 3-D reconstruction
Weights and measures -- Periodicals
Measurement -- Periodicals
Measurement
Weights and measures
Periodicals
530.8 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02632241 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.measurement.2020.108265 ↗
- Languages:
- English
- ISSNs:
- 0263-2241
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5413.544700
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- 14370.xml