Suppr超能文献

基于探地雷达(GPR)在铁路道床检测中应用的最新研究综述。

State-of-the-Art Review of Ground Penetrating Radar (GPR) Applications for Railway Ballast Inspection.

机构信息

Infrastructure Inspection Research Institute, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China.

School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China.

出版信息

Sensors (Basel). 2022 Mar 22;22(7):2450. doi: 10.3390/s22072450.

Abstract

In the past 20 years, many studies have been performed on ballast layer inspection and condition evaluation with ground penetrating radar (GPR). GPR is a non-destructive means that can reflect the ballast layer condition (fouling, moisture) by analysing the received signal variation. Even though GPR detection/inspection for ballast layers has become mature, some challenges still need to be stressed and solved, e.g., GPR indicator (for reflecting fouling level) development, quantitative evaluation for ballast fouling levels under diverse field conditions, rapid GPR inspection, and combining analysis of GPR results with other data (e.g., track stiffness, rail acceleration, etc.). Therefore, this paper summarised earlier studies on GPR application for ballast layer condition evaluation. How the GPR was used in the earlier studies was classified and discussed. In addition, how to correlate GPR results with ballast fouling level was also examined. Based on the summary, future developments can be seen, which is helpful for supplementing standards of ballast layer evaluation and maintenance.

摘要

在过去的 20 年中,许多研究都致力于使用探地雷达(GPR)对道砟层进行检测和状态评估。GPR 是一种非破坏性的手段,可以通过分析接收到的信号变化来反映道砟层的状况(污垢、水分)。尽管 GPR 检测/检查道砟层已经成熟,但仍需要强调和解决一些挑战,例如,GPR 指标(用于反映污垢水平)的开发、不同现场条件下道砟污垢水平的定量评估、快速 GPR 检测以及将 GPR 结果与其他数据(例如,轨道刚度、轨枕加速度等)进行综合分析。因此,本文总结了早期关于 GPR 在道砟层状态评估中的应用研究。对早期研究中 GPR 的使用进行了分类和讨论。此外,还研究了如何将 GPR 结果与道砟污垢水平相关联。基于总结,可以看到未来的发展方向,这有助于补充道砟层评估和维护的标准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac4a/9003199/4407e31b4c71/sensors-22-02450-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验