Masters Theses

Abstract

“The interest in the ability to monitor a structure and detect damage at the earliest possible stage is pervasive throughout the civil, mechanical and aerospace engineering communities. Structural Health Monitoring is a new and promising technology that has attracted significant interest in recent years. The essence of this technology is to develop an autonomous system for continuous monitoring, inspection, and damage detection of structures.

The need for global damage detection methods that can be applied to complex structures has led to the development of methods that examine changes in the vibration characteristics of the structure. This thesis focuses on developing a collative model of damage detection in three different structures. The model is based on comparative study of four prime vibration-based damage detection algorithms applied to experimental and analytical data obtained from damaged and undamaged structures. The investigative work includes testing the sensitivity of each of the methods in assessing damage in the structures and identifying any shortcomings that are encountered in accurate detection. Modifications are made to some methods in an attempt to explore the possibilities of refining the techniques and examine any improvements in the estimation of damage more precisely.

The experimental validation of this research work is based on data obtained from a precise and reliable optical instrument, viz., the Scanning Laser Vibrometer. The numerical simulation is performed using the finite element software ANSYS.

Results obtained from the experimental and theoretical testing are summarized and compared. Based on the varying levels of success of each method when applied for monitoring the integrity of a structure, inferences about its potential and application to the relevant engineering application are drawn. The comparative study based on corroborative experiments and the solid conclusions made in this thesis would serve as a baseline and contribute to further investigations on damage detection in the structures"--Abstract, page iii.

Advisor(s)

Koval, Leslie Robert

Committee Member(s)

Rao, Vittal S.
Liou, Frank W.

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Research Center/Lab(s)

Intelligent Systems Center

Publisher

University of Missouri--Rolla

Publication Date

Fall 2000

Pagination

xiii, 121 pages

Note about bibliography

Includes bibliographical references (pages 119-120).

Rights

© 2000 Bhanumathi Tenneti, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 7839

Print OCLC #

45902087

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