Health Assessment of Three Dimensional Large Structural Systems Using Limited Uncertain Dynamic Response Information

Persistent Link:
http://hdl.handle.net/10150/268597
Title:
Health Assessment of Three Dimensional Large Structural Systems Using Limited Uncertain Dynamic Response Information
Author:
Das, Ajoy Kumar
Issue Date:
2012
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Embargo:
Release after 02-Jul-2013
Abstract:
A novel system identification (SI)-based structural health assessment (SHA) procedure has been developed integrating several theoretical and implementation aspects. The procedure assesses health of structures using limited noise-contaminated dynamic responses and without using input excitation information. Since most practical structures are three dimensional (3D), the procedure has been developed for general 3D structures, represented by finite elements (FEs). The procedure identifies defects by tracking the changes in the stiffness of the elements in the FE representation. Once a defective element is identified, defect spot can be identified accurately within the defective element. The procedure is denoted as 3D Generalized Iterative Least-Squares Extended Kalman Filter with Unknown Input (3D GILS-EKF-UI) and implemented in two stages. In Stage 1, based on the available responses, substructure(s) are selected and the 3D GILS-UI procedure is used to generate the unknown input excitation, stiffness parameters of the elements in the substructure, and two Rayleigh damping coefficients. Using information from Stage 1, stiffness parameters for the whole structure are identified using EKF with Weighted Global Iteration (EKF-WGI) in Stage 2. The procedure accurately identified defect-free and defective states of various 3D structures using only analytically generated limited responses. To increase the robustness, 3D GILS-EKF-UI has been extended to develop an integrated structural health assessment strategy, denoted as Iterative Least-Squares Extended Kalman Filter with Unknown Input and Advanced Digital Integration Technique (ILS-EKF-UI-ADIT). The procedure has been implemented in three stages. In Stage 1, an advanced digital integration technique (ADIT) is implemented for post-processing of noise-contaminated acceleration time-histories, addressing all major challenges of digital integration. It also overcomes non-convergence issue in Stage 2 that arises due to phase-shift and amplitude errors. In Stage 2, substructure(s) are identified using the least-squares procedure. In Stage 3, stiffness parameters for the whole structure are identified using the EKF-WGI procedure. ILS-EKF-UI-ADIT has been verified in presence of relatively large noise in the acceleration time-histories, measured at small part(s) of defect-free and defective structures, without using excitation information. The SHA procedure is robust and has the potential to be applied for the health assessment, maintenance, retrofitting, and life extension of existing structural systems.
Type:
text; Electronic Dissertation
Keywords:
Health assessment; System identification; Time-domain; Unknown input excitation; Civil Engineering; Defects; Finite elements
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Civil Engineering
Degree Grantor:
University of Arizona
Advisor:
Haldar, Achintya

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleHealth Assessment of Three Dimensional Large Structural Systems Using Limited Uncertain Dynamic Response Informationen_US
dc.creatorDas, Ajoy Kumaren_US
dc.contributor.authorDas, Ajoy Kumaren_US
dc.date.issued2012-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.releaseRelease after 02-Jul-2013en_US
dc.description.abstractA novel system identification (SI)-based structural health assessment (SHA) procedure has been developed integrating several theoretical and implementation aspects. The procedure assesses health of structures using limited noise-contaminated dynamic responses and without using input excitation information. Since most practical structures are three dimensional (3D), the procedure has been developed for general 3D structures, represented by finite elements (FEs). The procedure identifies defects by tracking the changes in the stiffness of the elements in the FE representation. Once a defective element is identified, defect spot can be identified accurately within the defective element. The procedure is denoted as 3D Generalized Iterative Least-Squares Extended Kalman Filter with Unknown Input (3D GILS-EKF-UI) and implemented in two stages. In Stage 1, based on the available responses, substructure(s) are selected and the 3D GILS-UI procedure is used to generate the unknown input excitation, stiffness parameters of the elements in the substructure, and two Rayleigh damping coefficients. Using information from Stage 1, stiffness parameters for the whole structure are identified using EKF with Weighted Global Iteration (EKF-WGI) in Stage 2. The procedure accurately identified defect-free and defective states of various 3D structures using only analytically generated limited responses. To increase the robustness, 3D GILS-EKF-UI has been extended to develop an integrated structural health assessment strategy, denoted as Iterative Least-Squares Extended Kalman Filter with Unknown Input and Advanced Digital Integration Technique (ILS-EKF-UI-ADIT). The procedure has been implemented in three stages. In Stage 1, an advanced digital integration technique (ADIT) is implemented for post-processing of noise-contaminated acceleration time-histories, addressing all major challenges of digital integration. It also overcomes non-convergence issue in Stage 2 that arises due to phase-shift and amplitude errors. In Stage 2, substructure(s) are identified using the least-squares procedure. In Stage 3, stiffness parameters for the whole structure are identified using the EKF-WGI procedure. ILS-EKF-UI-ADIT has been verified in presence of relatively large noise in the acceleration time-histories, measured at small part(s) of defect-free and defective structures, without using excitation information. The SHA procedure is robust and has the potential to be applied for the health assessment, maintenance, retrofitting, and life extension of existing structural systems.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectHealth assessmenten_US
dc.subjectSystem identificationen_US
dc.subjectTime-domainen_US
dc.subjectUnknown input excitationen_US
dc.subjectCivil Engineeringen_US
dc.subjectDefectsen_US
dc.subjectFinite elementsen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineCivil Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHaldar, Achintyaen_US
dc.contributor.committeememberKundu, Tribikramen_US
dc.contributor.committeememberDesai, Chandrakanten_US
dc.contributor.committeememberHaldar, Achintyaen_US
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