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 <i>Multi-Scale Mixed Modality Microstructure Titanium Assessment Characterization </i>(M4TAC) challenge dataset. Example results are presented with current motivations of enhancements.
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