Frequency Prediction Based on SVR-ARMA Combination Model Improved by Particle Swarm Optimization

被引：0
|
作者：
Liu Z. [1 ]
Ding Y. [1 ,2 ]
Yan J. [1 ,2 ]
机构：
[1] School of Civil Engineering, Tianjin University, Tianjin
[2] Key Laboratory of Coast Civil Structure Safety of Ministry of Education, Tianjin University, Tianjin
来源：
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2020年 / 40卷 / 02期
关键词：
Modal frequency; Particle swarm optimization; Structural damage warning; SVR-ARMA combinatorial model;
D O I：
10.16450/j.cnki.issn.1004-6801.2020.02.023
中图分类号：
学科分类号：
摘要：
In order to realize damage warning of complex steel structures under environmental conditions, SVR-ARMA combinatorial model based on particle swarm optimization (PSO) is proposed.The damage warning method of complex steel structure is established by mean control chart and the proposed model. The accuracy of the prediction model is verified by the monitoring data of the White-wave River Ferris wheel inWeifang city.The results show that compared with the SVR model, SVR-ARMA model and PSO-SVR model, the PSO-SVR-ARMA model has higher generalization ability and prediction accuracy.In the structural damagewarning, the PSO-SVR-ARMA model can detect the slight abnormal changes of the modal frequency caused by the damage, which greatly improves the accuracy of the damage warning. The results can provide reference for damage warning of complex steel structures under environmental conditions. © 2020, Editorial Department of JVMD. All right reserved.
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页码：374 / 380
页数：6
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