Anomaly detection for dike monitoring using system identification

Structures such as seawalls, levees and dikes prevent low lying land from flooding. The structural health of these constructions is critical and needs to be maintained. In this paper, we present a data-driven approach that uses the information of different in-situ measurements to detect structural a...

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Bibliographic Details
Published in2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 399 - 403
Main Authors Thakre, Neha, Debes, Christian, Heremans, Roel, Zoubir, Abdelhak
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2014
Subjects
anomaly detection
Dike monitoring
Equations
Levee
Mathematical model
Monitoring
Signal processing
Stability analysis
system identification
Training
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Summary:Structures such as seawalls, levees and dikes prevent low lying land from flooding. The structural health of these constructions is critical and needs to be maintained. In this paper, we present a data-driven approach that uses the information of different in-situ measurements to detect structural anomalies at an early stage. Our approach is based on system identification, in which the dike is modeled as a single-input, multiple-output, linear system whose parameters can be learned based on training data. A statistical test is then deployed to perform a systematic detection of anomalies. We demonstrate the performance of the proposed approach on real data from an experimental dike setup.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2014.6853626