Data Grouping Analysis of Asphalt Pavement Distress Using Sequential Cluster Method
编号:905 访问权限:仅限参会人 更新:2021-12-09 10:36:54 浏览:124次 张贴报告

报告开始:2021年12月17日 10:23(Asia/Shanghai)

报告时间:1min

所在会场:[P1] Poster2020 [P1T2] Track 2 Transportation Infrastructure Engineering

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摘要
Pavement Condition Index (PCI) is a comprehensive indicator describing the overall damage of pavement surface and can be used to determine the pavement maintenance needs. However, due to its combination of multiple distress, the same PCI score may represent different combinations of pavement distress, making it impossible to make accurate preservation decisions. Therefore, it is necessary to conduct a more detailed grouping study on pavement distress data and establish a relationship between the refined data packets and PCI. Based on the actual distress data of Shanghai urban asphalt pavement, this study firstly uses the sequential clustering method to group the pavement segment data according to the PCI score. Then the distress characteristics of each group were analyzed and the differences between different damages were quantitatively calculated. The results show that the impact of the pavement distress combination on PCI is not uniform and the PCI score cannot fully reflect the complexity of pavement distress. When the PCI level is moderate, the variability of the pavement distress combination is the largest.
关键词
CICTP
报告人
Li Li
Shanghai University

Tingting Guan
Shanghai Urban Construction and Operation (Group) Co., Ltd

稿件作者
Li Li Shanghai University
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重要日期
  • 会议日期

    12月17日

    2021

    12月20日

    2021

  • 12月16日 2021

    报告提交截止日期

  • 12月24日 2021

    注册截止日期

主办单位
Chinese Overseas Transportation Association
Chang'an University
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