Identification and Damage Detection of Trusses Using Digital Processing of Vibration Signatures

被引:0
|
作者
Niu, Lin [1 ,2 ]
Ye, Liaoyuan [2 ]
机构
[1] Honghe Univ, Coll Engn, Mengzi, Yunnan, Peoples R China
[2] Kunming Univ Sci & Technol, Coll Land & Resource Engn, Kunming, Peoples R China
来源
关键词
structural health monitoring; damage detection; time-delay neural networks; vibration signature analysis; bridge truss; STRUCTURAL DAMAGE;
D O I
10.4028/www.scientific.net/AMR.255-260.659
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Knowledge of the economic and social effects of aging, deterioration and extreme events on civil infrastructure have been accompanied by recognition of the need for advanced structural health monitoring and damage detection tools. In this paper the time-delay neural networks (TDNNs) have been implemented in detecting the damage in bridge structure using vibration signature analysis. A simulation study has been carried out for the incomplete measurement data. It has been observed that TDNNs have performed better than traditional neural networks in this application and the arithmetic of the TDNNs is simple.
引用
收藏
页码:659 / +
页数:2
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