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

摘要

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.