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Open AccessArticle

Time-Frequency Methods for Structural Health Monitoring

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Siemens LLC, Corporate Technology, Volynskiy lane 3A, St. Petersburg, 191186, Russia
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University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
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St. Petersburg State University of Aerospace Instrumentation, Bolshaya Morskaia 67, St. Petersburg, 190000, Russia
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Siemens AG, Corporate Technology, Muenchen, 80200, Germany
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Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek (TNO), Eemsgolaan 3 NL-9727 DW, Groningen, The Netherlands
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National Research University ITMO, St. Petersburg, 197101, Russia
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St. Petersburg State Polytechnic University, St. Petersburg, 195251, Russia
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Nanyang Technological University, 639798, Singapore
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Author to whom correspondence should be addressed.
This paper includes materials from Pyayt et al. An approach for real-time levee health monitoring using signal processing methods. Procedia Computer Science 2013, 18, 2357–2366, doi:10.1016/j.procs.2013.05.407.
Sensors 2014, 14(3), 5147-5173; https://doi.org/10.3390/s140305147
Received: 14 November 2013 / Revised: 28 February 2014 / Accepted: 3 March 2014 / Published: 12 March 2014
(This article belongs to the Section Physical Sensors)
Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and concrete dams) using sensor data. We present a robust data-driven anomaly detection method that combines time-frequency feature extraction, using wavelet analysis and phase shift, with one-sided classification techniques to identify the onset of failure anomalies in real-time sensor measurements. The methodology has been successfully tested at three operational levees. We detected a dam leakage in the retaining dam (Germany) and “strange” behaviour of sensors installed in a Boston levee (UK) and a Rhine levee (Germany). View Full-Text
Keywords: anomaly detection; structural health monitoring; time-frequency analysis; sensors; flood protection systems; levee monitoring; one-side classification; leakage detection anomaly detection; structural health monitoring; time-frequency analysis; sensors; flood protection systems; levee monitoring; one-side classification; leakage detection
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MDPI and ACS Style

Pyayt, A.L.; Kozionov, A.P.; Mokhov, I.I.; Lang, B.; Meijer, R.J.; Krzhizhanovskaya, V.V.; Sloot, P.M.A. Time-Frequency Methods for Structural Health Monitoring. Sensors 2014, 14, 5147-5173. https://doi.org/10.3390/s140305147

AMA Style

Pyayt AL, Kozionov AP, Mokhov II, Lang B, Meijer RJ, Krzhizhanovskaya VV, Sloot PMA. Time-Frequency Methods for Structural Health Monitoring. Sensors. 2014; 14(3):5147-5173. https://doi.org/10.3390/s140305147

Chicago/Turabian Style

Pyayt, Alexander L.; Kozionov, Alexey P.; Mokhov, Ilya I.; Lang, Bernhard; Meijer, Robert J.; Krzhizhanovskaya, Valeria V.; Sloot, Peter M.A. 2014. "Time-Frequency Methods for Structural Health Monitoring" Sensors 14, no. 3: 5147-5173. https://doi.org/10.3390/s140305147

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