A Robust Deep Learning-Based Damage Identification Approach for SHM Considering Missing Data

Data-driven methods have shown promising results in structural health monitoring (SHM) applications. However, most of these approaches rely on the ideal dataset assumption and do not account for missing data, which can significantly impact their real-world performance. Missing data is a frequently e...

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Bibliografische Detailangaben

Hauptverfasser:	Fan Deng, Xiaoming Tao, Pengxiang Wei, Shiyin Wei
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2023-04-01
Schriftenreihe:	Applied Sciences
Schlagworte:	structural health monitoring missing data damage identification deep learning
Online-Zugang:	https://www.mdpi.com/2076-3417/13/9/5421
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