Distinguishing Cracks and Non-metallic Inclusions Using Eddy Current Nondestructive Evaluation and Model-based Inversion (Postprint)

Abstract

Recent work has demonstrated the capability of applying inverse methods to automated eddy current (EC) data of surface breaking cracks and notches of various sizes, orientations and aspect ratios. However, not all eddy current indications in turbine engine component inspections originate from cracks, which can result in the unnecessary removal of engine components from service. For powder metallurgy nickel-based superalloys, non-metallic inclusions (NMIs) and non-metallic particles are frequently present. If an EC inspection can reliably classify NMI indications from crack indications, there would be great payoff for the USAF. In this work, simulated results are presented to highlight differences in eddy current signals from cracks and NMIs. Progress is presented on the development of a new model-based inversion scheme highlighting enhancements to the numerical model VIC-3D (registered trademark), improved indication registration in noisy scans, and the fitting and evaluation of multiple surrogate model classes. Lastly, inversion results demonstrate the ability to distinguish cracks and NMIs, and the potential to characterize the approximate dimensions and depth of NMIs.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 08, 2019
Accession Number
AD1072741

Entities

People

  • Allisha L Hutson
  • Elias Sabbagh
  • Eric B Shell
  • Erin K Oneida
  • Harold A. Sabbagh
  • John C. Aldrin
  • Matthew Cherry
  • R. K. Murphy
  • Siamack Mazdiyasni

Organizations

  • Air Force Research Laboratory Materials and Manufacturing Directorate

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Eddy Currents
  • Engine Components
  • Engines
  • Governments
  • Inclusions
  • Inspection
  • Inversion
  • Materials
  • Metallurgy
  • Military Research
  • Particles
  • Powder Metallurgy
  • Powders
  • Test And Evaluation
  • Turbines

Readers

  • Computational Modeling and Simulation
  • Materials Science and Engineering.
  • Sensor Fusion and Tracking Systems.