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dc.contributor.authorKhodabandeloo, Babak
dc.contributor.authorMelvin, Dyan
dc.contributor.authorJo, Hongki
dc.date.accessioned2018-01-31T18:20:58Z
dc.date.available2018-01-31T18:20:58Z
dc.date.issued2017-11-17
dc.identifier.citationModel-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties 2017, 17 (11):2656 Sensorsen
dc.identifier.issn1424-8220
dc.identifier.doi10.3390/s17112656
dc.identifier.urihttp://hdl.handle.net/10150/626477
dc.description.abstractDirect measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well.
dc.language.isoenen
dc.publisherMDPI AGen
dc.relation.urlhttp://www.mdpi.com/1424-8220/17/11/2656en
dc.rights© 2017 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license.en
dc.subjectforce estimationen
dc.subjectheterogeneous sensor networken
dc.subjectKalman filteringen
dc.subjectmulti-metric measurementsen
dc.subjectstructural dynamicsen
dc.titleModel-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertaintiesen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Civil Engn & Engn Mechen
dc.identifier.journalSensorsen
dc.description.noteOpen access journal.en
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-15T23:04:23Z
html.description.abstractDirect measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well.


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