Self‐supervised representation learning of metro interior noise based on variational autoencoder and deep embedding clustering

The noise within train is a paradox; while harmful to passenger health, it is useful to operators as it provides insights into the working status of vehicles and tracks. Recently, methods for identifying defects based on interior noise signals are emerging, among which representation learning is the...

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Veröffentlicht in:	Computer-aided civil and infrastructure engineering 2024-09
Hauptverfasser:	Wang, Yang, Xiao, Hong, Zhang, Zhihai, Guo, Xiaoxuan, Liu, Qiang
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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