Presentation + Paper
8 June 2022 Methods of scanning acoustic microscopy and eddy current fusion for materials analysis
John Wertz, Erik Blasch, Matthew Cherry, Sean O'Rourke, Theresa Scarnati, Nicholas Lorenzo, Laura Homa, Nathan Gaw
Author Affiliations +
Abstract
Sensor data fusion has significant potential for advancing discovery, processing, and inspection of engineering materials. The paper reviews recent developments in data fusion with respect to materials inspection, highlights potential areas for materials growth, and shows results from application of matching component analysis (MCA). The main contributions of the paper include analysis of current fusion methods to uncover challenges and opportunities with respect to two inspection modalities (scanning acoustic microscopy and eddy current testing); and presenting an extension of MCA which has previously developed for other image modalities. Presenting MCA highlights the benefits towards a baseline method of SAM-EC fusion using the Multi-Scale Mixed Modality Microstructure Titanium Assessment Characterization (M4TAC) challenge dataset. Example results are presented with current motivations of enhancements.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John Wertz, Erik Blasch, Matthew Cherry, Sean O'Rourke, Theresa Scarnati, Nicholas Lorenzo, Laura Homa, and Nathan Gaw "Methods of scanning acoustic microscopy and eddy current fusion for materials analysis", Proc. SPIE 12122, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI, 121220S (8 June 2022); https://doi.org/10.1117/12.2622255
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KEYWORDS
Data fusion

Sensors

Nondestructive evaluation

Inspection

Microscopy

Acoustics

Metals

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