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Studies into Data-Driven Approaches for Nonlinear System
Identification, Condition Assessment, and Health Monitoring
by
Armen Derkevorkian
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements of the Degree
DOCTOR OF PHILOSOPHY
(Civil Engineering)
May 2014
Copyright 2014 Armen Derkevorkian
Object Description
| Title | Studies into data-driven approaches for nonlinear system identification, condition assessment, and health monitoring |
| Author | Derkevorkian, Armen |
| Author email | derkevor@gmail.com;derkevor@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Civil Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2014-03-02 |
| Date submitted | 2014-04-02 |
| Date approved | 2014-04-02 |
| Restricted until | 2014-04-02 |
| Date published | 2014-04-02 |
| Advisor (committee chair) | Masri, Sami F. |
| Advisor (committee member) |
Wellford, L. Carter Ioannou, Petros |
| Abstract | The recent advancements in computational capabilities and sensing technologies provide an excellent opportunity to develop, test, and validate data‐driven mathematical models for system identification, condition assessment, and health monitoring of structural systems that may be vibrating in linear and/or nonlinear ranges. In this study, measurements from various large‐scale, complex, experimental systems, as well as full‐scale real‐life multi‐input‐multi‐output (MIMO) structures are used to develop robust mathematical frameworks for response prediction, change detection, nonlinear damping estimation, in addition to displacement‐field and operating‐load estimation. The systems under consideration are the Yokohama Bay Bridge which was subjected to the 2011 Great East Japan Earthquake; large‐scale experimental soil‐foundation-superstructure interaction systems subjected to various earthquake excitations with systematically increasing levels of intensity; swept wing‐like experimental aluminum plates developed at the NASA Dryden Flight Research Center and instrumented with state‐of‐the‐art fiber‐optic sensors; and a four‐story experimental test‐bed designed, developed and fabricated at the University of Southern California. The vibration signatures from these systems are used to assess the viability of existing parametric and nonparametric identification approaches, and to propose new hybrid data-driven computational modeling methods that can accurately capture the correct physics of the underlying complex systems. This dissertation is a collection of analytical, computational, and experimental studies that capitalizes on the availability of large datasets to develop tools that can interpret these datasets, and to establish robust frameworks that can extract physically meaningful information, for an informed decision‐making. |
| Keyword | condition assessment; data‐driven approaches; large‐scale experiments; mathematical modeling; nonlinear systems; sensing technologies |
| Language | English |
| Format (imt) | application/pdf |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Derkevorkian, Armen |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Derkevorki-2314.pdf |
| Archival file | uscthesesreloadpub_Volume8/etd-Derkevorki-2314.pdf |
Description
| Title | Page 1 |
| Repository email | cisadmin@lib.usc.edu |
| Full text | Studies into Data-Driven Approaches for Nonlinear System Identification, Condition Assessment, and Health Monitoring by Armen Derkevorkian A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements of the Degree DOCTOR OF PHILOSOPHY (Civil Engineering) May 2014 Copyright 2014 Armen Derkevorkian |
