A probability of detection model for a sensor-based monitoring method against local wall thinning

Abstract

In this study, a multivariable probability of detection (POD) model is developed to quantify the detection capability of a low frequency electromagnetic (LFEM) testing method with permanently installed sensors to monitor the thinning of pipe walls. Numerical simulations are utilized to predict the signal response by modeling LFEM testing against local wall thinning with different profiles. By probabilistically calibrating the simulated signal response with a limited number of experimental samples, signal response distributions due to various flaw profiles are inferred. Subsequently, a model is developed using Monte Carlo simulation to determine the distribution of the signal response affected by sensor placement and to calculate the POD. The resultant POD contours reflect the effect of multiple flaw parameters and sensor placement on the detection capability of the LFEM testing method.