Model based Inverse Methods for Sizing Cracks of Varying Shape and Location in Bolt hole Eddy Current (BHEC) Inspections (Postprint)

Abstract

A comprehensive approach is presented to perform model-based inversion of crack characteristics using bolt hole eddy current (BHEC) techniques. Data was acquired for a wide range of crack sizes and shapes, including mid-bore, corner and through-thickness crack types, and from both standard eddy current hardware and a prototype BHEC system with z-axis position encoding. Signal processing algorithms were developed to process and extract features from the 2D data sets, and inversion algorithms using VIC-3D generated surrogate models were used for inverting crack size. New model results are presented, which now address the effect of having a corner crack at an edge and a through crack adjacent to two edges. A two-step inversion process was implemented that first evaluates the material layer thickness, crack type and location, in order to select the most appropriate VIC-3D surrogate model for subsequent crack sizing inversion step. Inversion results for select mid-bore, through and corner crack specimens are presented where sizing performance was found to be satisfactory in general, but also depend on the size and location of the flaw.

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Document Details

Document Type
Technical Report
Publication Date
Feb 10, 2016
Accession Number
AD1030928

Entities

People

  • David Forsyth
  • Doyle Motes
  • Elias Sabbagh
  • Eric A. Lindgren
  • Harold A. Sabbagh
  • Jennifer Flores-lamb
  • John C. Aldrin
  • Liming Zhao
  • Mark Keiser
  • R. K. Murphy
  • Ryan Mooers

Organizations

  • Air Force Research Laboratory Materials and Manufacturing Directorate

Tags

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Algorithms
  • Coding
  • Data Sets
  • Eddy Currents
  • Feature Extraction
  • Governments
  • Inspection
  • Inversion
  • Materials
  • Military Research
  • Models
  • Signal Processing
  • Standards
  • Thickness

Readers

  • Image Processing and Computer Vision.
  • Regression Analysis.
  • Structural Health Monitoring of Composite Structures.