Doctoral Dissertations

Title

Structural condition assessment of the Bill Emerson Memorial Cable-Stayed Bridge using neural networks

Author

Wenjian Wang

Abstract

"Structural health monitoring is a challenging task that has recently received great attention from research communities. Due to its ability for predication and classification, neural network has become a promising tool for the identification of structural damages. In this dissertation, two backpropagation neural networks are introduced to predict the structural responses and to quantify the structural damages. The proposed methodology differs from many existing technologies in that it can be used to detect damages directly from the measured time signals without requiring modal characteristics"--Abstract, leaf iii.

Advisor(s)

Chen, Genda

Committee Member(s)

LaBoube, Roger A.
Belarbi, Abdeldjelil
Ge, Yu-Ning (Louis)
Liu, Xiaoqing Frank

Department(s)

Civil, Architectural and Environmental Engineering

Degree Name

Ph. D. in Civil Engineering

Sponsor(s)

Missouri Transportation Institute
United States. Department of Transportation

Publisher

University of Missouri--Rolla

Publication Date

Spring 2007

Pagination

xii, 168 leaves

Note about bibliography

Includes bibliographical references (leaves 155-167).

Geographic Coverage

Bill Emerson Memorial Bridge (East Cape Girardeau, Ill., and Cape Girardeau, Mo.)

Rights

© 2007 Wenjian Wang, All rights reserved.

Document Type

Dissertation - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Cable-stayed bridges -- Testing
Neural networks (Computer science)
Structural analysis (Engineering) -- Mathematical models

Thesis Number

T 9196

Print OCLC #

180773759

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b6126416~S5

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