RESEARCH ON STRUCTURAL DAMAGE IDENTIFICATION USING GREY NETWORK

Li Hairui; Li Juelong; Xing Jianchun

doi:10.13204/j.gyjz201212027

Volume 42 Issue 12

Dec. 2014

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Abstract

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Citation:

Li Hairui, Li Juelong, Xing Jianchun. RESEARCH ON STRUCTURAL DAMAGE IDENTIFICATION USING GREY NETWORK[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(12): 126-128,138. doi: 10.13204/j.gyjz201212027

Citation:

Li Hairui, Li Juelong, Xing Jianchun. RESEARCH ON STRUCTURAL DAMAGE IDENTIFICATION USING GREY NETWORK[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(12): 126-128,138. doi: 10.13204/j.gyjz201212027

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RESEARCH ON STRUCTURAL DAMAGE IDENTIFICATION USING GREY NETWORK

doi: 10.13204/j.gyjz201212027

1.
1. Institute of National Defense Engineering,PLA University of Science &Technology,Nanjing 210007,China;
2.
2. The Center for Coast Defense Engineering Research of Navy,Beijing 100841,China

Received Date: 2012-01-17
Publish Date: 2012-12-20

Abstract

Abstract

Combining the static displacement curvature assurance coefficient used for damage identification with artificial neural network technology,the system of structural damage identification based on the grey network was set up.Using the system to judge the location and extent of structural damage on cantilever beam,it can be seen that this method is very effective,and the calculation on the static displacement curvature assurance coefficient is simple,the accuracy is high,and it also has a highly parallel computing power and good fault tolerance.
- damage identification,
- static displacement curvature assurance coefficient,
- artificial neural networks,
- grey network

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References(7)

References

[2] Chen Xiaozhen,Zhu Hongping,Chen Chuanyao.Structural Damage Identification Using Test Static Data Based on Grey System Theory[J].Journal of Zhejiang University:Science,2005,6A(80):790-796.

陈长征,罗跃纲,白秉三,等.结构损伤检测与智能诊断[M].北京:科学出版社,2001:15-17.

[3] 陈孝珍,朱宏平,陈传尧.灰色相关性分析结构静力损伤识别中的应用[J].力学与实践,2005,27(3):60-64.

[4] 禹丹江,陈淮.桥梁损伤检测的曲率模态法探讨[J].郑州大学学报,2002,23(3):104-106.

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