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

fYear

2011

fDate

28-28 Sept. 2011

Firstpage

1

Lastpage

7

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Environmental Energy and Structural Monitoring Systems (EESMS), 2011 IEEE Workshop on

Conference_Location

Milan

Print_ISBN

978-1-4577-0610-3

Type

conf

DOI

10.1109/EESMS.2011.6067047

Filename

6067047