Damage detection based on wavelet transform and artificial intelligence for underwater metallic structures

被引：0

作者：

Yaya, Sidibe ^{[1
]}

Dimitri, Lefebvre ^{[1
]}

Fabrice, Druaux ^{[1
]}

Gerard, Maze ^{[2
]}

Fernand, Leon ^{[2
]}

机构：

[1] Univ Le Havre, Normandie Univ, GREAH, F-76058 Le Havre, France

[2] Univ Le Havre, Normandie Univ, CNRS, LOMC,UMR 6294, F-76058 Le Havre, France

来源：

2014 EUROPEAN CONTROL CONFERENCE (ECC) | 2014年

关键词：

Damage detection; signal processing; gaussian neural network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Health monitoring is investigated for immersed structures. The environment of these structures makes their monitoring and diagnosis very difficult. In this paper, the major challenge is to make easy and efficient the monitoring of this kind of structures. The proposed detection method is based on non contact measurements with acoustic scattering. It uses artificial intelligence, with gaussian neural networks and signal processing with wavelets transformation and principal component analysis. The method is validated with experimental measurements collected from immersed plates including surface cracks with different orientations. Such plates represent a simplified model of underwater turbine blades.

引用

页码：2992 / 2997

页数：6

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