Degree Type

Thesis

Date of Award

1996

Degree Name

Master of Science

Department

Aerospace Engineering

First Advisor

Lester W. Schmerr

Abstract

An important goal of nondestructive evaluation is the detection and classification of flaws in materials. This process of 'flaw classification' involves the transformation of the 'raw' data into other domains, the extraction of features in those domains, and the use of those features in a classification algorithm that determines the class to which the flaw belongs.

In this work, we describe a flaw classification software system, CLASS and the updates made to it. Both a hierarchical clustering algorithm and a backpropagation neural network algorithm were implemented -and integrated with CLASS. A fast Fourier transform routine was also added to CLASS in order to enable the use of frequency domain and cepstral domain features.

This extended version of CLASS is a very user friendly software, which requires the user to have little knowledge of the actual learning algorithms. CLASS can be easily extended further, if needed, in the future.

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu

Copyright Owner

Sriram Chavali

Language

en

Date Available

June 10, 2013

File Format

application/pdf

File Size

74 pages

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