Accession Number:

ADA464672

Title:

Case Study for New Feature Extraction Algorithms, Automated Data Classification, and Model-Assisted Probability of Detection Evaluation (Preprint)

Descriptive Note:

Conference paper

Corporate Author:

COMPUTATIONAL TOOLS INC GURNEE IL

Personal Author(s):

Report Date:

2006-09-01

Pagination or Media Count:

10.0

Abstract:

This paper explores feature extraction algorithms for crack characterization in eddy current inspection of fastener sites. A novel feature extraction method fitting approximate models to data associated with geometric part features addressing adjacent fastener sites and panel edges are developed. Data classification methods in the circumferential direction around fastener sites are developed to better characterize fatigue cracks with improved noise invariance. Model-assisted probability of detection results are presented highlighting the benefit of automation in NDE.

Subject Categories:

  • Computer Programming and Software
  • Cybernetics
  • Electricity and Magnetism
  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE