An approach for real-time levee health monitoring using signal processing methods

被引：12

作者：

Pyayt, Alexander L. ^{[1
,2
]}

Kozionov, Alexey P. ^{[1
,3
]}

Mokhov, Ilya I. ^{[1
]}

Lang, Bernhard ^{[4
]}

Krzhizhanovskaya, Valeria V. ^{[2
,5
]}

Sloot, Peter M. A. ^{[2
,5
,6
]}

机构：

[1] Siemens LLC, Corp Technol, Volynskiy Lane 3, St Petersburg 191186, Russia

[2] Univ Amsterdam, NL-1098 XH Amsterdam, Netherlands

[3] St Petersburg State Univ, Aerosp Instrumentat, St Petersburg 190000, Russia

[4] Siemens AG, D-91050 Erlangen, Germany

[5] Natl Res Univ, ITMO, St Petersburg, Russia

[6] Nanyang Technol Univ, Singapore 639798, Singapore

来源：

2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE | 2013年 / 18卷

关键词：

signal analysis; levee health monitoring; UrbanFlood project; leakage detection; one-side classification;

D O I：

10.1016/j.procs.2013.05.407

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

引用

页码：2357 / 2366

页数：10

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