Monitoring and early detection of internal erosion: Distributed sensing and processing

Abstract

International audienceEarly 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 1m 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

A Review of Measurement Calibration and Interpretation for Seepage Monitoring by Optical Fiber Distributed Temperature Sensors

“…This method is a medium-term monitoring technique that can be used to monitor leakage based on the months’ raw data [ 55 ]. The method is useful when a large number of acquisitions are provided by monitoring systems [ 56 ] as in the case of optical fiber DTS measurement. The known factors such as daily and seasonal effects and rainfall periods can be filtered from the data using the data filtering techniques such as low pass filter and Kurtosis based filtering [ 57 ].…”

“…Considering this assumption, the data matrix can be formulated as: here, is the data matrix as a linear mixture of independent sources, is the mixing matrix, and is the matrix of sources. is the number of independent sources that affect thermal behavior in the embankment [ 54 , 56 , 57 ]. Equation (9) presents a source separation problem.…”

“…ICA estimates the sources and their contributions to the mixture by considering mutual independence between the sources. Subspace presents the temperature variation due to leakage and the associated time and location of those variations The SVD and ICA mathematical processes are presented in Equation (10) and Equation (11) respectively [ 56 ]. More details on the SVD and ICA and their applications in the source separation method can be found in [ 56 , 57 , 58 ]: …”

Induced polarization tomography applied to the detection and the monitoring of leaks in embankments

“…On one hand, traditional geotechnical technics (e.g., cone penetration test and/or standard penetration tests) have limitations related to cost-effectiveness and the perturbation on the structures themselves (e.g., Fauchard and Mériaux, 2007;Cardarelli et al, 2014). Temperature measurements using fiber optics can be used to evaluate leakages (Beck et al, 2010;Khan et al, 2014), but such approaches are unfortunately intrusive. On the other hand, geophysical methods can provide fast and non-intrusive 3D and 4D tomograms of leakages using a variety of techniques (e.g., Rittgers et al, 2013;Ikard et al, 2015).…”

A Review of Distributed Fibre Optic Sensors for Geo-Hydrological Applications

“…Each of them works on a different time scale (i.e., daily, monthly, or annually, respectively), and is aimed at a different monitoring purpose; i.e., short-term/early warning, medium-and long-term monitoring, respectively [115]. Other existing methodologies deal with general signal processing techniques [116,117].…”