Probability of detection modelling in eddy current NDE of flaws integrating multiple correlated variables

Abstract A new method to model the probability of detection (PoD) of flaws that takes into consideration the correlation between the flaw features as a function of the correlated flaw dimensions, the length and depth, is proposed in this work. Boundary element method was used to efficiently obtain the required flaw features. The features used are the maximum change in the amplitudes of the three components of the scattered magnetic flux density ( B x , B y and B z ). Firstly, the magnetic-electric Green's function, for a finite thickness plate, is formulated. On knowing the distribution of the dipole density, the scattered fields at the axial center of the coil are computed. Experiments were conducted in a controlled environment to validate the predictions of the BEM. The features, from the BEM, computed for several flaw lengths and depths, were fit to a trivariate Gaussian distribution. The discrete form of the PoD was determined after identifying the sensor threshold. A continuous function is later obtained by linking the discrete PoD with a generalized logistic function.