Structural Damage Detection using Improved Modal Strain Energy Index and Cloud Model

被引：0

作者：

Guo, Huiyong ^{[1
]}

Zhang, Xin ^{[1
]}

Wang, Yushan ^{[2
]}

机构：

[1] Chongqing Univ, Sch Civil Engn, Chongqing 400045, Peoples R China

[2] Shihezi Univ, Sch Water Conservancy & Architectural Engn, Shihezi 832003, Peoples R China

来源：

2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD) | 2017年

基金：

中国国家自然科学基金;

关键词：

damage detection; strain energy; cloud theory; dissipation ration; generator;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to solve structural damage identification problem, a damage assessment approach based on improved modal strain energy dissipation ration index and cloud model is presented. First, structural modal strain energy is considered as information source and an improved modal strain energy dissipation ration index (IMSEDRI) is proposed to identify suspected damage elements. Then, cloud model theory is introduced and a backward cloud generator is proposed to analyze noisy modal data. The simulation results demonstrate that the damage detection method can analyze damage problem with random noise, and the calculated results of the proposed IMSEDRI are better than those of the basic modal strain energy dissipation ration index.

引用

页码：722 / 726

页数：5

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