Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index

被引：0

作者：

Guo H. ^{[1
,2
]}

Wang Z. ^{[1
,2
]}

Li Z. ^{[1
,2
]}

机构：

[1] Key Laboratory of New Technology for Construction of Cities in Mountain Area of the Ministry of Education, Chongqing University, Chongqing

[2] School of Civil Engineering, Chongqing University, Chongqing

来源：

Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2020年 / 55卷 / 03期

关键词：

Acceleration response; Autoregressive conditional heteroskedasticity (ARCH) model; Damage identification; Maximum likelihood estimation; Nonlinear;

D O I：

10.3969/j.issn.0258-2724.20180316

中图分类号：

学科分类号：

摘要：

To solve the identification problem of time-domain nonlinear damage, the incorporation of an autoregressive conditional heteroskedasticity (ARCH) model with damage detection was proposed. First, the basic theory of ARCH model was described, and the order estimation and maximum likelihood parameter estimation of ARCH model were proposed. Then, the characteristics of nonlinear damage were analyzed, and a damage detection theory based on ARCH model was presented. Finally, it is difficult for the damage index based on degree of freedom to identify damage locations, an autoregressive conditional heteroskedasticity conversion index (ARCHCI) was proposed. A three-storey frame experiment was used to verify the effectiveness of the ARCHCI, the effect of measurement error and model error was also considered in the experiment. The results show that the ARCHCI value of the damaged third storey is at least 21.7% higher than that of the cepstrum metric conversion index when the nonlinear gap distances are 0.05 mm and 0.10 mm; the ARCHCI value of the third storey is 3.7% higher than that of the cepstrum metric conversion index when the gap distance is 0.20 mm. © 2020, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.

引用

页码：459 / 466and517

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