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 operators and crack morphology, 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 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 paper shows how to t a proper model to repeatedmeasures hit-miss data and considers estimation of 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 for these quantities using a Bayesian estimation approach.
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