Structural Damage Identification Based on AR Model and PSO-SVM

被引：0

作者：

Wang Yumei ^{[1
]}

Diao Yansong ^{[1
]}

Liu Guodong ^{[1
]}

Sui Zongzhen ^{[1
]}

Guo Dang ^{[1
]}

机构：

[1] Qingdao Univ Technol, Sch Civil Engn, Qingdao, Shandong, Peoples R China

来源：

2019 IEEE INTERNATIONAL WORKSHOP ON ELECTROMAGNETICS: APPLICATIONS AND STUDENT INNOVATION COMPETITION (IWEM2019) | 2019年

关键词：

damage identification; AR model; PSO-SVM; damage location; offshore platform;

D O I：

暂无

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

In this paper, we put forward a structural damage identification method based on autoregressive (AR) model and particle swarm optimization support vector machine (PSO-SVM). Firstly, AR model is established for acceleration response signal, and the model coefficients are extracted. Secondly, the difference of AR model coefficients under damaged and undamaged conditions is selected as the damage feature. Finally, PSO-SVM is used to distinguish the damage location of a structure. The validity and noise resistance of the method are verified by numerical simulation and analysis results of a five-floor steel offshore platform.

引用

页数：2

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