An Approach for Real-time Levee Health Monitoring Using Signal Processing Methods
| Autor: | Alexey P. Kozionov, Peter M. A. Sloot, Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya |
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| Přispěvatelé: | Computational Science Lab (IVI, FNWI) |
| Rok vydání: | 2013 |
| Předmět: |
UrbanFlood project
geography Signal processing geography.geographical_feature_category Computer science 020208 electrical & electronic engineering 02 engineering and technology levee health monitoring signal analysis 6. Clean water Reliability engineering leakage detection 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Early warning system 020201 artificial intelligence & image processing one-side classification Levee General Environmental Science |
| Zdroj: | Procedia Computer Science ICCS Procedia Computer Science, 18, 2357-2366. Elsevier |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2013.05.407 |
| Popis: | We developed a levee health monitoring system within the UrbanFlood project funded under the EU 7th Framework Programme. A novel real-time levee health assessment Artificial Intelligence system is developed using data-driven methods. The system is implemented in the UrbanFlood early warning system. We present the application of dedicated signal processing methods for detection of leakage through the water retaining dam and subsequent analysis of the measurements collected from one of the UrbanFlood pilot levees at the Rhine river in Germany. |
| Databáze: | OpenAIRE |
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