...
首页> 外文期刊>Tunnelling and underground space technology >Feasibility study of automated detection of tunnel excavation by Brillouin optical time domain reflectometry
【24h】

Feasibility study of automated detection of tunnel excavation by Brillouin optical time domain reflectometry

机译:布里渊光学时域反射仪自动检测隧道开挖的可行性研究

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Cross-borders smuggling tunnels enable unmonitored movement of people, drugs and weapons and pose a very serious threat to homeland security. Recent advances in strain measurements using optical fibers allow the development of smart underground security fences that could detect the excavation of smuggling tunnels. This paper presents the first stages in the development of such a fence using Brillouin optical time domain reflectometry (BOTDR). Two fiber optic layouts are considered and evaluated in a feasibility study that includes evaluation of false detection and sensitivity: (1) horizontally laid fiber buried at a shallow depth, and (2) fibers embedded in vertical mini-piles. In the simulation study, two different ground displacement models are used in order to evaluate the robustness of the system against imperfect modeling. In both cases, soil-fiber and soil-structure interactions are considered. Measurement errors, and surface disturbances (obtained from a field test) are also included in the calibration and validation stages of the system. The proposed detection system is based on wavelet decomposition of the BOTDR signal, followed by a neural network that is trained to recognize the tunnel signature in the wavelet coefficients. The results indicate that the proposed system is capable of detecting even small tunnel (0.5 m diameter) as deep as 20 m (under the horizontal fiber) or as far as 10 m aside from the mini-pile (vertical fiber), if the volume loss is greater than 0.5%.
机译:跨边界走私隧道使人们,毒品和武器的不受监视的流动成为可能,对国土安全构成了非常严重的威胁。使用光纤进行应变测量的最新进展允许开发智能地下安全围栏,该围栏可以检测走私隧道的开挖。本文介绍了使用布里渊光学时域反射仪(BOTDR)开发这种围栏的第一步。在可行性研究中考虑并评估了两种光纤布局,其中包括对错误检测和灵敏度的评估:(1)埋在浅深度的水平铺设光纤,以及(2)嵌入垂直微型桩的光纤。在仿真研究中,使用了两个不同的地面位移模型来评估系统对不完善建模的鲁棒性。在这两种情况下,都考虑了土壤纤维和土壤结构的相互作用。系统的校准和验证阶段还包括测量误差和表面干扰(从现场测试中获得)。所提出的检测系统基于BOTDR信号的小波分解,然后是经过训练以识别小波系数中的隧道特征的神经网络。结果表明,所提出的系统甚至能够检测深达20 m(在水平光纤下)或距离微型桩(垂直光纤)最远10 m的小隧道(0.5 m直径)(如果体积很大)损失大于0.5%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号