Structural damage identification methods based on improved generalized Kalman filter
Jianhua Chen
Abstract
Jianhua Chen
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.
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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