Damage detection in offshore structures using neural networks

被引：71

作者：

Elshafey, Ahmed A. ^{[3
]}

Haddara, Mahmoud R. ^{[1
]}

Marzouk, H. ^{[2
]}

机构：

[1] Mem Univ Newfoundland, Fac Engn & Appl Sci, St John, NF A1B 3X5, Canada

[2] Ryerson Univ, Fac Engn Architecture & Sci, Toronto, ON, Canada

[3] Menoufia Univ, Fac Engn, Shebeen El Kam, Egypt

来源：

MARINE STRUCTURES | 2010年 / 23卷 / 01期

关键词：

Damage detection; Random decrement; Neural networks; Offshore jacket structures; IDENTIFICATION;

D O I：

10.1016/j.marstruc.2010.01.005

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

This paper discusses the damage detection in offshore jacket platforms subjected to random loads using a combined method of random decrement signature and neural networks. The random decrement technique is used to extract the free decay of the structure from its online response while the structure is in service. The free decay and its time derivative are used as input for a neural network. The output of the neural network is used as an index for damage detection. It has been shown that function N is effective in damage detection in the members of an offshore structure. Experimental studies conducted on a reduced model for a real jacket structure with geometrical scale of 1:30 are used. The applied loads were random loads. Two different load spectra were used: White noise, and Pierson-Moskowitz. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：131 / 145

页数：15

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