Structural Damage Detection Based on curvature mode shapes and Neural Network Technique

被引：0

作者：

Du Guangqian ^{[1
]}

Zhu Changzhi ^{[1
]}

Long Lijuan ^{[2
]}

Zhang Meng ^{[2
]}

机构：

[1] Agr Univ Hebei, Shijiazhuang 071001, Hebei, Peoples R China

[2] Yixian Urban & Rural Planning Author, Yixian 074200, Peoples R China

来源：

PROGRESS IN INDUSTRIAL AND CIVIL ENGINEERING, PTS. 1-5 | 2012年 / 204-208卷

关键词：

Curvature mode shapes; Grey theory; Neural network; Damage detection;

D O I：

10.4028/www.scientific.net/AMM.204-208.2907

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

On the basis of the theory that natural frequency changes and curvature mode shapes can be employed to determine the locations and degrees of damage of structures, a BP neural network technique with an improved input structure was developed. The two networks were used for diagnosis of structural damage, and structural damages were predicted using gray theory. The results showed that the gray theory to predict the structural damage neural network was applicable to irregular objects such injury problem diagnosis.

引用

页码：2907 / +

页数：2

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