Abstract

Real defects are essential for the evaluation of the reliability of non destructive testing (NDT) methods, especially in relation to the integrity of components. But in most of the cases the amount of available real defects is not sufficient to evaluate the system. Model-assisted and transfer functions are one way to handle that challenge. This study is focused on combination of different data pools to create sufficient amount of data for the reliability estimation. A widespread approach for calculating the Probability of Detection (POD) was used on radiographic testing (RT) method. The highest contrast to noise ratio (CNR) of each indication is usually selected as the signal in the â vs. a (signal-response) approach for RT. By combining real and artificial defects (flat bottom holes, side drill holes, flat bottom squares, notches, etc) in RT the highest signals are close to each other, but the process of creating and evaluating real defects is much more complex. The solution is seen in the combin...

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