Model Assisted Probability of Detection curves: New statistical tools and progressive methodology

TL;DR

This paper introduces a new, progressive statistical methodology for Model Assisted Probability of Detection (MAPOD) curves, enhancing NDT performance evaluation through metamodel-based sensitivity analysis and applications to Eddy Current data.

Contribution

It proposes a generic, progressive MAPOD methodology with new metamodel-based techniques, addressing limitations of classical methods and improving analysis of NDT procedures.

Findings

New MAPOD methodology with metamodels and sensitivity analysis

Application to Eddy Current NDT data demonstrating effectiveness

Enhanced understanding of NDT performance evaluation

Abstract

The Probability Of Detection (POD) curve is a standard tool in several industries to evaluate the performance of Non Destructive Testing (NDT) procedures for the detection of harmful defects for the inspected structure. Due to new capabilities of NDT process numerical simulation , Model Assisted Probability of Detection (MAPOD) approaches have also been recently developed. In this paper, a generic and progressive MAPOD methodology is proposed. Limits and assumptions of the classical methods are enlightened, while new metamodel-based methods are proposed. They allow to access to relevant information based on sensitivity analysis of MAPOD inputs. Applications are performed on Eddy Current Non Destructive Examination numerical data.