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

2016/01/22 by Loïc Le Gratiet, Gratiet, Loïc Le, Bertrand Iooss +9
Decision Sciences · Engineering · #FOS: Computer and information sciences #Methodology (stat.ME) #Non-Destructive Testing Techniques #Probabilistic and Robust Engineering Design #Structural Health Monitoring Techniques

paper · doi:10.48550/arxiv.1601.05914

openalex publication_date 2016/01/22 · openalex created_date 2022/10/16 · openalex updated_date 2026/07/28

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.

Related

• Efficient generation of realistic guided wave signals for reliability estimation
• Investigations of different likelihood functions for the use in Bayesian model updating in structural applications
• Curve registration by nonparametric goodness-of-fit testing
• Towards end-to-end pulsed eddy current classification and regression with CNN
• A Unified Inference Method for FROC-type Curves and Related Summary Indices