KEYWORDS: Independent component analysis, Data acquisition, Fiber optics, Signal detection, Temperature sensors, Detection and tracking algorithms, Sensors, Sensing systems, Principal component analysis, Data modeling
Distributed temperature sensors (DTS) based on fiber optics present an efficient means for temperature data
acquisition. The use of DTS data to detect leakages in dikes necessitates some processing of this data. Formulating
leakage detection as a source separation problem, the goal of this paper is to compare various blind source
separation techniques for percolation type leakage detection using a real data set. Singular value decomposition
can be used as the first step to separate out the ground response where acquisitions are made. Two independent
component analysis algorithms, JADE and FastICA, assuming independence of sources, are tested to find the
best solution for leakage detection.
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