Document Type

Conference Proceeding

Publication Date

2004

Journal or Book Title

AIP Conference Proceedings

Volume

700

First Page

605

Last Page

612

DOI

10.1063/1.1711677

Abstract

We propose a model for characterizing amplitude and phase probability distributions of eddy‐current signals. The squared amplitudes and phases of the potential defect signals are modeled as independent, identically distributed (i.i.d.) random variables following gamma and von Mises distributions, respectively. We derive a maximum likelihood (ML) method for estimating the amplitude and phase distribution parameters from measurements corrupted by additive complex white Gaussian noise. Newton‐Raphson iteration is utilized to compute the ML estimates of the unknown parameters. The obtained estimates can be used for flaw detection as well as efficient feature extractors in a defect classification scheme. Finally, we apply the proposed method to analyze rotating‐probe eddy‐current data from tube inspection of a steam generator in a nuclear power plant.

Comments

The following article appeared in AIP Conference Proceedings 700 (2004): 605 and may be found at doi:10.1063/1.1711677.

Rights

Copyright 2004 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.

Copyright Owner

American Institute of Physics

Language

en

File Format

application/pdf

Share

COinS