A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction
The objective of the work is experimental validation and optimal experimental design for structural response reconstruction. A modal-based Kalman filter approach based on excitation identification Kalman filter is proposed for response reconstruction and excitation estimation of structures by using...
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2019-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2019/5475686 |
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doaj-4dcfe08aa6f946d6b146a42edcdcdb4c2020-11-25T01:09:25ZengHindawi LimitedShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/54756865475686A Modal-Based Kalman Filter Approach and OSP Method for Structural Response ReconstructionZhenrui Peng0Kangli Dong1Hong Yin2School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaSchool of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaSchool of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaThe objective of the work is experimental validation and optimal experimental design for structural response reconstruction. A modal-based Kalman filter approach based on excitation identification Kalman filter is proposed for response reconstruction and excitation estimation of structures by using noisy acceleration and strain measurements. Firstly, different filters are introduced and discussed. Secondly, to avoid single type sensors, a displacement reconstruction based on modal method is introduced into the proposed approach. Thirdly, the backward sequential algorithm is given to obtain the optimal sensor locations. It is shown that the proposed method can avoid the divergency in the estimated process of excitation and displacements as a result of incomplete measurements. Reasonable estimates of strains, displacements, velocities, accelerations, and excitations of structures can be accomplished with few acceleration sensors and strain gauges.http://dx.doi.org/10.1155/2019/5475686 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenrui Peng Kangli Dong Hong Yin |
spellingShingle |
Zhenrui Peng Kangli Dong Hong Yin A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction Shock and Vibration |
author_facet |
Zhenrui Peng Kangli Dong Hong Yin |
author_sort |
Zhenrui Peng |
title |
A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction |
title_short |
A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction |
title_full |
A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction |
title_fullStr |
A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction |
title_full_unstemmed |
A Modal-Based Kalman Filter Approach and OSP Method for Structural Response Reconstruction |
title_sort |
modal-based kalman filter approach and osp method for structural response reconstruction |
publisher |
Hindawi Limited |
series |
Shock and Vibration |
issn |
1070-9622 1875-9203 |
publishDate |
2019-01-01 |
description |
The objective of the work is experimental validation and optimal experimental design for structural response reconstruction. A modal-based Kalman filter approach based on excitation identification Kalman filter is proposed for response reconstruction and excitation estimation of structures by using noisy acceleration and strain measurements. Firstly, different filters are introduced and discussed. Secondly, to avoid single type sensors, a displacement reconstruction based on modal method is introduced into the proposed approach. Thirdly, the backward sequential algorithm is given to obtain the optimal sensor locations. It is shown that the proposed method can avoid the divergency in the estimated process of excitation and displacements as a result of incomplete measurements. Reasonable estimates of strains, displacements, velocities, accelerations, and excitations of structures can be accomplished with few acceleration sensors and strain gauges. |
url |
http://dx.doi.org/10.1155/2019/5475686 |
work_keys_str_mv |
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_version_ |
1725178993775214592 |