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Showing 1 to 2 of 2 for “"Unsupervised SHM"”.
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Toward a General Novelty Detection Framework in Structural Health Monitoring; Challenges and Opportunities in Deep Learning
Structural health monitoring (SHM) is an anomaly detection process. Data-driven SHM has gained much attention compared to the model-based strategy, specifically with the current state-of-the-art machine learning routines. Model-based methods require structural information, time-consuming model …
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On the Effectiveness of Dimensionality Reduction for Unsupervised Structural Health Monitoring Anomaly Detection
… prevalent in the Structural Health Monitoring (SHM) anomaly detection literature. While DR is favorable in supervised anomaly detection, where possible novelties are known a priori, the efficacy is less clear in unsupervised detection. In this work, we perform a detailed assessment of the DR …