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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Vydáno v:	Computer-aided civil and infrastructure engineering Ročník 40; číslo 4; s. 503 - 522
Hlavní autoři:	Wang, Yang, Xiao, Hong, Zhang, Zhihai, Guo, Xiaoxuan, Liu, Qiang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken Wiley Subscription Services, Inc 01.02.2025
Témata:	Artificial neural networks Clustering Data augmentation Embedding Fault detection Machine learning Modules Neural networks Noise reduction Representations Wavelet transforms
ISSN:	1093-9687, 1467-8667
On-line přístup:	Získat plný text
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