Improved decentralized structural identification with output-only measurements

© 2017 Elsevier Ltd. This paper proposes an improved decentralized structural identification approach with output-only measurements. The improved approach can be used for system identification of both linear and nonlinear structures. A large-scale structure is divided into a number of smaller zones...

Full description

Bibliographic Details
Main Authors: Ni, P., Xia, Y., Li, Jun, Hao, Hong
Format: Journal Article
Published: Elsevier 2017
Online Access:http://purl.org/au-research/grants/arc/LP160100528
http://hdl.handle.net/20.500.11937/57274
_version_ 1848760039849852928
author Ni, P.
Xia, Y.
Li, Jun
Hao, Hong
author_facet Ni, P.
Xia, Y.
Li, Jun
Hao, Hong
author_sort Ni, P.
building Curtin Institutional Repository
collection Online Access
description © 2017 Elsevier Ltd. This paper proposes an improved decentralized structural identification approach with output-only measurements. The improved approach can be used for system identification of both linear and nonlinear structures. A large-scale structure is divided into a number of smaller zones according to its finite element configuration. Each zone is dynamically tested in sequence with its own set of sensor placement. The external excitation forces in each zone are identified using the Kalman filter technique. Structural parameters of the whole structure are divided into several subsets and then updated by using the Newton-SOR method. Both the external excitations and structural parameters are iteratively updated until a defined convergence criterion is met. The proposed technique is then applied to two numerical examples: a six floor building and a planar truss structure. The nonlinear system parameters of the building are correctly identified. The unknown excitation force, damage location, and damage severity in the plane truss structure are successfully identified. The effect of measurement noise on the identified results is also studied. An eight floor shear type structure is finally tested in the laboratory. The experimental results further verify the effectiveness and efficiency of the proposed technique in damage identification using output-only measurements.
first_indexed 2025-11-14T10:09:27Z
format Journal Article
id curtin-20.500.11937-57274
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:09:27Z
publishDate 2017
publisher Elsevier
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-572742023-02-02T03:24:11Z Improved decentralized structural identification with output-only measurements Ni, P. Xia, Y. Li, Jun Hao, Hong © 2017 Elsevier Ltd. This paper proposes an improved decentralized structural identification approach with output-only measurements. The improved approach can be used for system identification of both linear and nonlinear structures. A large-scale structure is divided into a number of smaller zones according to its finite element configuration. Each zone is dynamically tested in sequence with its own set of sensor placement. The external excitation forces in each zone are identified using the Kalman filter technique. Structural parameters of the whole structure are divided into several subsets and then updated by using the Newton-SOR method. Both the external excitations and structural parameters are iteratively updated until a defined convergence criterion is met. The proposed technique is then applied to two numerical examples: a six floor building and a planar truss structure. The nonlinear system parameters of the building are correctly identified. The unknown excitation force, damage location, and damage severity in the plane truss structure are successfully identified. The effect of measurement noise on the identified results is also studied. An eight floor shear type structure is finally tested in the laboratory. The experimental results further verify the effectiveness and efficiency of the proposed technique in damage identification using output-only measurements. 2017 Journal Article http://hdl.handle.net/20.500.11937/57274 10.1016/j.measurement.2017.09.029 http://purl.org/au-research/grants/arc/LP160100528 Elsevier restricted
spellingShingle Ni, P.
Xia, Y.
Li, Jun
Hao, Hong
Improved decentralized structural identification with output-only measurements
title Improved decentralized structural identification with output-only measurements
title_full Improved decentralized structural identification with output-only measurements
title_fullStr Improved decentralized structural identification with output-only measurements
title_full_unstemmed Improved decentralized structural identification with output-only measurements
title_short Improved decentralized structural identification with output-only measurements
title_sort improved decentralized structural identification with output-only measurements
url http://purl.org/au-research/grants/arc/LP160100528
http://hdl.handle.net/20.500.11937/57274