Unsupervised Structural Damage Detection Technique Based on a Deep Convolutional Autoencoder

Structural health monitoring (SHM) is a hot research topic with the main purpose of damage detection in a structure and assessing its health state. The major focus of SHM studies in recent years has been on developing vibration-based damage detection algorithms and using machine learning, especially...

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Veröffentlicht in:	Shock and vibration Jg. 2021; H. 1
Hauptverfasser:	Rastin, Zahra, Ghodrati Amiri, Gholamreza, Darvishan, Ehsan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cairo Hindawi 2021 John Wiley & Sons, Inc Wiley
Schlagworte:	Algorithms Analysis Concrete Convolution Damage detection Data collection Deep learning Fault diagnosis Feature extraction Fuzzy logic Localization Machine learning Methods Neural networks Numerical models Prestressed concrete Principal components analysis Public health Structural damage Structural health monitoring Support vector machines Training Vibration Wavelet transforms
ISSN:	1070-9622, 1875-9203
Online-Zugang:	Volltext
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