Implementation of a robust methodology to obtain the Probability Of Detection (POD) curves in NDT: integration of human and environmental factors for Eddy Currents (EC)

Speaker:
Reseco Bato, Miguel; Airbus France; France

Authors:
Reseco Bato, M.; Airbus Operations S.A.S.; France
Hor, A.; Université de Toulouse; France
Rautureau, A.; Airbus Operations S.A.S.; France
Bes, C.; Université de Toulouse; France

ID: ECNDT-0576-2018
Download: PDF
Session: NDT Reliablity 2
Room: J2
Date: 2018-06-14
Time: 10:50 - 11:10

In aeronautics, the evaluation of the Non-Destructive Testing (NDT) methods is a key step in the aircraft’s maintenance program. Nowadays, this calculation is performed by a statistical study taking into consideration the sources of uncertainty inherent in the applied NDT method. These uncertainties are due to human and environmental factors during In-Service maintenance tasks. The POD curve is carried out by an experimental process, where a wide range of inspector skills, defect types and locations, material types and procedures are included. At this moment, this experimental process evidences high costs and time consuming for the aircraft manufacturer.
The objective of this paper is to define a methodology of building POD from numerical modelling. The POD robustness is ensured by the integration of the uncertainties through statistical distributions issued from experimental data or engineering judgments. Applications are provided on titanium beta using High Frequency Eddy Currents (HFEC) NDT technique.
First, an experimental database will be created from three environments: laboratory, A321 and A400M aircrafts. A representative sample of operators, with different certification levels in NDT technique, will be employed. Multiple inspection scenarios will be carried out to analyse these human and environmental factors.
This database is used, subsequently, to build statistical distributions. These distributions are the input data of the simulation model. A POD module, based on the Monte Carlo method, is integrated to draw a sampling. This module will be applied to address human influences on POD. Additionally, this module will help us to state the device impact in POD curves.
Finally, the simulation POD model will be compared and validated with the experimental results. Numerical results encourage to replace or complete experimental campaigns in future works.