Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index

GUO Huiyong; WANG Zhihua; LI Zhengliang

doi:10.3969/j.issn.0258-2724.20180316

Volume 55 Issue 3

Jun. 2020

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Journal of Southwest Jiaotong University > 2020 > 55(3): 459-466, 517.

GUO Huiyong, WANG Zhihua, LI Zhengliang. Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index[J]. Journal of Southwest Jiaotong University, 2020, 55(3): 459-466, 517. doi: 10.3969/j.issn.0258-2724.20180316

Citation:

GUO Huiyong, WANG Zhihua, LI Zhengliang. Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index[J]. Journal of Southwest Jiaotong University, 2020, 55(3): 459-466, 517. doi: 10.3969/j.issn.0258-2724.20180316

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Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index

doi: 10.3969/j.issn.0258-2724.20180316

Received Date: 22 May 2018
Rev Recd Date: 31 Aug 2018

Available Online: 05 Sep 2018

Publish Date: 01 Jun 2020

Abstract

Abstract

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.
- damage identification,
- autoregressive conditional heteroskedasticity (ARCH) model,
- nonlinear,
- acceleration response,
- maximum likelihood estimation

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Structural Nonlinear Damage Identification Based on Autoregressive Conditional Heteroskedasticity Conversion Index

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