A correction algorithm for automatic pavement detection data bias
编号:2052 访问权限:仅限参会人 更新:2021-12-08 10:21:46 浏览:297次 张贴报告

报告开始:暂无开始时间(Asia/Shanghai)

报告时间:暂无持续时间

所在会场:[暂无会议] [暂无会议段]

演示文件 附属文件

提示:该报告下的文件权限为仅限参会人,您尚未登录,暂时无法查看。

摘要
The inspection results of the automated pavement inspection equipment often deviate from the pavement's actual condition, which leads to misjudgment of the pavement's technical condition. This study takes the inspection data obtained by the automated equipment commonly used on Shanghai highways as an example and proposes a data correction process that considers the pavement damage composition characteristics. Based on 10.8 km of automated equipment and manual comparative inspection testing, the study suggests a data correction algorithm based on the single damage index and establishes a PCI (Pavement Condition Index) calculation model based on automated inspection data that integrates block crack, alligator crack, line crack, and the interaction term. Finally, the proposed correction model is validated with actual pavement measurement data, and the results show that the model has good accuracy.
关键词
CICTP
报告人
Li Li
Shanghai University

Jiahui Yu
Shanghai University

稿件作者
Li Li Shanghai University
发表评论
验证码 看不清楚,更换一张
全部评论
重要日期
  • 会议日期

    12月17日

    2021

    至

    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
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询