Monitoring and early detection of internal erosion: Distributed sensing and processing - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Structural Health Monitoring Année : 2014

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

Résumé

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 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.
Fichier principal
Vignette du fichier
Structural_Health_Monitoring-2014-Khan.pdf (2.25 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01001765 , version 1 (04-06-2014)

Identifiants

Citer

A. A. Khan, Valeriu Vrabie, Y. L. Beck, Jerome I. Mars, Guy d'Urso. Monitoring and early detection of internal erosion: Distributed sensing and processing. Structural Health Monitoring, 2014, 13 (5), pp.1-15. ⟨10.1177/1475921714532994⟩. ⟨hal-01001765⟩
160 Consultations
1205 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More