Early detection of leakages in hydraulic infrastructures is important to ensure their safety and security. Significant flow of water through the dike can be an indicator of internal erosion and results in a thermal anomaly. Temperature measurements are therefore capable of revealing information linked to leakage. Optical fiber–based distributed temperature sensors present an economically viable and reliable solution for recording spatio-temporal temperature data over long distances, with spatial and temperature resolutions of 1 m and 0.05°C, respectively. The acquired data are influenced by several factors, among them water leakages, heat transfer through the above soil depth, seasonal thermal variations, and the geomechanical environment. Soil properties such as permeability alter the acquired signal locally. This article presents leakage detection methods based on signal processing of the raw temperature data from optical fiber sensors. The first approach based on source separation identifies leakages by separating them from the non-relevant information. The second approach presents a potential alarm system based on the analysis of daily temperature variations. Successful detection results for simulated as well as real experimental setups of Electricité de France are presented.

The development of automated monitoring systems for the detection of singularities, such as leakages in dikes, is indispensable to avoid mass disaster. An efficient solution for dike survey is the use of distributed temperature sensors (DTSs) based on optical fiber, offering a multitude of advantages such as low cost, extreme robustness, long-range measurement, etc. However, the temperature data acquired with DTSs, being not directly interpretable, require intervention of signal processing techniques. This paper addresses this signal processing aspect, exploiting the key idea that the temperature variations over the course of a day for singular zones are quite different from those for nonsingular zones. A daily reference temperature variation, which is representative of the nonsingular zones, is estimated using singular value decomposition (SVD). The residue subspace of SVD contains information linked to the deviations from this reference, thus allowing the degree of singularity to be quantified by a dissimilarity measure such as the L₂-norm. To detect only the singularities in dikes, such as leakages or drains, a constant false alarm rate (CFAR) detector is proposed by modeling each daily dissimilarity measure with a mixture of Gamma and uniform distributions. The proposed automatic singularity detection system was validated under different scenarios on real data over periods from 2005 to 2007. The first scenario depicted the detection of percolation-type artificial leakages with their detection strength depending on their flow rates. Another scenario allowed detecting the presence of a real water leakage at the site, which was previously unobserved during manual inspections. The repeatability of the system was also verified by periodic analysis.

The estimation of sinkhole-induced ground displacement is an important issue for monitoring soil structures. Distributed optical fiber sensors (DOFSs) composed of an interrogator based on scattering effects in an optical fiber cable sensing element can be used to assess ground displacement. These sensors provide longitudinal strain measurements of the soil structure. This paper proposes a methodology that enables the estimation of displacement fields in the soil structure when a sinkhole appears. It also exposes an experiment that was carried out to create an artificial sinkhole instrumented by optical fiber sensors. This is the first time that those sensors are used to provide submillimeter vertical displacements. The first step of the methodology is to model the ground displacement under 2-D conditions. The longitudinal strain measured by a DOFS can thus be linked to the displacement of the structure. This model is described by the following parameters: 1) the spatial extent of the displacement signature; 2) a coefficient that depends on the interface between the optical fiber cable and the soil; 3) the depth of the sinkhole; and 4) the maximal vertical displacement. The second step consists of the estimation of each parameter independently. The spatial extension is given by fitting the measured strain signature with the empirical model. The depth of the sinkhole can be determined by the measurement of the spatial extension of the ground-displacement profile at several observation depths in the structure. Finally, the vertical maximal displacement is furnished with high precision.