Title :
Artificial intelligence and finite element modelling for monitoring flood defence structures
Author :
Pyayt, A.L. ; Mokhov, I.I. ; Kozionov, A. ; Kusherbaeva, V. ; Melnikova, N.B. ; Krzhizhanovskaya, V.V. ; Meijer, Robert J.
Author_Institution :
Corp. Technol., Siemens LLC, St. Petersburg, Russia
Abstract :
We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the UrbanFlood early warning system and successfully tested on a large-scale sea dike during a simulated strong storm with very high water level. The artificial intelligence module detects the onset of dike instability after being trained on the data from the Virtual Dike finite element simulation.
Keywords :
alarm systems; artificial intelligence; condition monitoring; finite element analysis; floods; geotechnical engineering; structural engineering computing; virtual reality; UrbanFlood early warning system; anomaly detection; artificial intelligence module; finite element modelling; flood defence structure stability monitoring; large-scale sea dike; real-time signal processing; virtual dike finite element simulation; Alarm systems; Artificial intelligence; Computational modeling; Floods; Levee; Numerical models; Sensors; UrbanFlood project; Virtual Dike; anomaly detection; machine learning methods;
Conference_Titel :
Environmental Energy and Structural Monitoring Systems (EESMS), 2011 IEEE Workshop on
Conference_Location :
Milan
Print_ISBN :
978-1-4577-0610-3
DOI :
10.1109/EESMS.2011.6067047
