Campus Units

Statistics, Center for Nondestructive Evaluation (CNDE)

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

3-1-2019

Journal or Book Title

Research in Nondestructive Evaluation

Volume

30

Issue

2

First Page

89

Last Page

111

DOI

10.1080/09349847.2017.1374493

Abstract

Probability of detection (POD) is commonly used to measure a nondestructive evaluation (NDE) inspection procedure’s performance. Due to inherent variability in the inspection procedure caused by variability in factors such as crack morphology and operators, it is important, for some purposes, to model POD as a random function. Traditionally, inspection variabilities are pooled and an estimate of the mean POD (averaged over all sources of variability) is reported. In some applications it is important to know how poor typical inspections might be, and this question is answered by estimating a quantile of the POD distribution. This article shows how to fit and compare different models to repeated-measures hit--miss data with multiple inspections with different operators for each crack and shows how to estimate the mean POD as well as quantiles of the POD distribution for binary (hit--miss) NDE data. We also show how to compute credible intervals (quantifying uncertainty due to limited data) for these quantities using a Bayesian estimation approach. We use NDE for the detection of fatigue cracks as the motivating example, but the concepts apply more generally to other NDE applications areas.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis in Research in Nondestructive Evaluation on March 1, 2019, available online: http://www.tandfonline.com/10.1080/09349847.2017.1374493. Posted with permission.

Copyright Owner

American Society for Nondestructive Testing

Language

en

File Format

application/pdf

Published Version

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