A systematic survey reviews unsupervised deep learning techniques for structural health monitoring and predictive maintenance, highlighting challenges and future directions.
This paper presents a systematic survey of unsupervised deep learning techniques applied tostructural health monitoring (SHM) and predictive maintenance (PdM). The survey reviewsautoencoders, clustering-based approaches, anomaly detection models, commonly used datasets,evaluation metrics, challenges, and future research directions.
No takes yet. Share an insight, caveat, or question.
Nikhil S (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: