Cross-border smuggling tunnels enable unmonitored movement of people and goods, and pose a severe threat to homeland security. In recent years, we have been working on the development of a system based on fiber- optic Brillouin time domain reflectometry (BOTDR) for detecting tunnel excavation. In two previous SPIE publications we have reported the initial development of the system as well as its validation using small-scale experiments. This paper reports, for the first time, results of full-scale experiments and discusses the system performance. The results confirm that distributed measurement of strain profiles in fiber cables buried at shallow depth enable detection of tunnel excavation, and by proper data processing, these measurements enable precise localization of the tunnel, as well as reasonable estimation of its depth.
Cross-border smuggling tunnels enable unmonitored movement of people, drugs and weapons and pose a very
serious threat to homeland security. Recently, Klar and Linker (2009) [SPIE paper No. 731603] presented an
analytical study of the feasibility of a Brillouin Optical Time Domain Reflectometry (BOTDR) based system for
the detection of small sized smuggling tunnels. The current study extends this work by validating the analytical
models against real strain measurements in soil obtained from small scale experiments in a geotechnical centrifuge.
The soil strains were obtained using an image analysis method that tracked the displacement of discrete patches
of soil through a sequence of digital images of the soil around the tunnel during the centrifuge test. The results of
the present study are in agreement with those of a previous study which was based on synthetic signals generated
using empirical and analytical models from the literature.
BOTDR is one of the strain measurement technologies that is suitable for smart monitoring of civil engineering
infrastructures. While the technology has the advantage of supplying spatially distributed data, it is currently
limited to a spatial resolution of about 1m. This infers that the technology may lack the ability to identify
the exact type and source of damage; that is, different geometrical configurations of cracking within a concrete
beam may lead to similar BOTDR readings, and hence the exact nature of cracking might not be resolved by the
BOTDR. This study suggests different crack indicators, and examines, both analytically and experimentally, their
correlation with BOTDR readings of damaged reinforced concrete beams. The analytical part entails statistical
analysis of hundreds of cracking cases in fractured reinforced concrete beams and their effect on the simulated
BOTDR readings. The analysis is conducted within COMSOL-Multiphysics, and is aimed to understand the
correlation between different crack indicators and the beam curvature as would be obtained by the BOTDR.
The experimental part consists of a controlled load test of a reinforced beam instrumented by BOTDR fibers,
and is aimed to support the analytical findings.
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). 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 interaction is 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 (0.5m diameter) as deep
as 20 meter.