Time-Frequency Methods for Structural Health Monitoring
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/14/3/5147 |
| _version_ | 1811302414593032192 |
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| author | Alexander L. Pyayt Alexey P. Kozionov Ilya I. Mokhov Bernhard Lang Robert J. Meijer Valeria V. Krzhizhanovskaya Peter M. A. Sloot |
| author_facet | Alexander L. Pyayt Alexey P. Kozionov Ilya I. Mokhov Bernhard Lang Robert J. Meijer Valeria V. Krzhizhanovskaya Peter M. A. Sloot |
| author_sort | Alexander L. Pyayt |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-04-13T07:28:42Z |
| format | Article |
| id | doaj.art-0a6c2626f3d34a109ef77a19aae65535 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:28:42Z |
| publishDate | 2014-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0a6c2626f3d34a109ef77a19aae655352022-12-22T02:56:25ZengMDPI AGSensors1424-82202014-03-011435147517310.3390/s140305147s140305147Time-Frequency Methods for Structural Health MonitoringAlexander L. Pyayt0Alexey P. Kozionov1Ilya I. Mokhov2Bernhard Lang3Robert J. Meijer4Valeria V. Krzhizhanovskaya5Peter M. A. Sloot6Siemens LLC, Corporate Technology, Volynskiy lane 3A, St. Petersburg, 191186, RussiaSiemens LLC, Corporate Technology, Volynskiy lane 3A, St. Petersburg, 191186, RussiaSiemens LLC, Corporate Technology, Volynskiy lane 3A, St. Petersburg, 191186, RussiaSiemens AG, Corporate Technology, Muenchen, 80200, GermanyUniversity of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The NetherlandsUniversity of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The NetherlandsUniversity of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The NetherlandsDetection 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).http://www.mdpi.com/1424-8220/14/3/5147anomaly detectionstructural health monitoringtime-frequency analysissensorsflood protection systemslevee monitoringone-side classificationleakage detection |
| spellingShingle | Alexander L. Pyayt Alexey P. Kozionov Ilya I. Mokhov Bernhard Lang Robert J. Meijer Valeria V. Krzhizhanovskaya Peter M. A. Sloot Time-Frequency Methods for Structural Health Monitoring Sensors anomaly detection structural health monitoring time-frequency analysis sensors flood protection systems levee monitoring one-side classification leakage detection |
| title | Time-Frequency Methods for Structural Health Monitoring |
| title_full | Time-Frequency Methods for Structural Health Monitoring |
| title_fullStr | Time-Frequency Methods for Structural Health Monitoring |
| title_full_unstemmed | Time-Frequency Methods for Structural Health Monitoring |
| title_short | Time-Frequency Methods for Structural Health Monitoring |
| title_sort | time frequency methods for structural health monitoring |
| topic | anomaly detection structural health monitoring time-frequency analysis sensors flood protection systems levee monitoring one-side classification leakage detection |
| url | http://www.mdpi.com/1424-8220/14/3/5147 |
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