Physical Model Assisted Probability of Detection in Nondestructive Evaluation

Nondestructive evaluation is used widely in many engineering and industrial areas to detect defects or flaws such as cracks inside parts or structures during manufacturing or for products in service. The standard statistical model is a simple empirical linear regression between the (possibly transformed) signal response variables and the (possibly transformed) explanatory variables. For some applications, such a simple empirical approach is inadequate. An important alternative approach is to use knowledge of the physics of the inspection process to provide information about the underlying relationship between the response and explanatory variables. Use of such knowledge can greatly increase the power and accuracy of the statistical analysis and enable, when needed, proper extrapolation outside the range of the observed explanatory variables. This paper describes a set of physical model‐assisted analyses to study the capability of two different ultrasonic testing inspection methods to detect synthetic hard alpha inclusion and flat‐bottom hole defects in a titanium forging disk.