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Semi-supervised and unsupervised learning for health indicator extraction from guided waves in aerospace composite structures

arXiv — cs.LG•Wednesday, October 29, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
A recent study highlights advancements in extracting health indicators from aerospace composite structures using semi-supervised and unsupervised learning techniques. This is significant because reliable health indicators are crucial for diagnosing and predicting the condition of these structures, which can lead to improved maintenance practices and enhanced operational safety. By addressing challenges like material variability and damage evolution, this research could pave the way for more efficient monitoring and maintenance strategies in the aerospace industry.
— via World Pulse Now AI Editorial System
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