2010•Dizhen gongcheng yu gongcheng zhendongRequires access

Structural damage identification methods based on improved generalized Kalman filter

Jianhua Chen

Open publisher page 0 citations

Abstract

Considering that the traditional generalized Kalman filter algorithm can not effectively track the changes in stiffness,based on the traditional Kalman filter,this paper works out the formulas of the fading Kalman filter.This paper uses the algorithm to analyze the responses of the earthquake signals to extract the characteristics of the structure,to identify the structural parameters,and determine the time,location and extent of the structural damage.The algorithm improves the generalized Kalman filtering effect.But fading Kalman filter algorithm can only determine the time when the structural parameters change,and may be prone to oscillation.This paper uses a new adaptive tracking technology,with an adaptive factor matrix instead of the original forgetting factor.The technology can effectively track the changes in structural parameters of time,location and extent,and thus applies to on-line identification.

About this research paper

What this paper is about

Considering that the traditional generalized Kalman filter algorithm can not effectively track the changes in stiffness,based on the traditional Kalman filter,this paper works out the formulas of the fading Kalman filter.This paper uses the algorithm to analyze the responses of the earthquake signals to extract the characteristics of the structure,to identify the structural parameters,and determine the time,location and extent of the structural damage.The algorithm improves the generalized Kalman filtering effect.But fading Kalman filter algorithm can only determine the time when the structural parameters change,and may be prone to oscillation.This paper uses a new adaptive tracking technology,with an adaptive factor matrix instead of the original forgetting factor.The technology can effectively track the changes in structural parameters of time,location and extent,and thus applies to on-line identification.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Considering that the traditional generalized Kalman filter algorithm can not effectively track the changes in stiffness,based on the traditional Kalman filter,this paper works out the formulas of the fading Kalman filter.This paper uses the algorithm to analyze the responses of the earthquake signals to extract the characteristics of the structure,to identify the structural parameters,and determine the time,location and extent of the structural damage.The algorithm improves the generalized Kalman filtering effect.But fading Kalman filter algorithm can only determine the time when the structural parameters change,and may be prone to oscillation.This paper uses a new adaptive tracking technology,with an adaptive factor matrix instead of the original forgetting factor.The technology can effectively track the changes in structural parameters of time,location and extent,and thus applies to on-line identification.

Key concepts: Kalman filter, Fast Kalman filter, Invariant extended Kalman filter, Alpha beta filter, Fading, Extended Kalman filter, Computer science, Algorithm

Related papers

Back to paper searchBrowse research topicsOriginal source
Structural damage identification methods based on improved generalized Kalman filter — Research Paper | ScholarLens