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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders
《Railway Engineering Science》2024年第4期421-443,共23页Jorge Magalhães Tomás Jorge Rúben Silva António Guedes Diogo Ribeiro Andreia Meixedo Araliya Mosleh Cecília Vale Pedro Montenegro Alexandre Cury 
a result of project WAY4SafeRail—Wayside monitoring system FOR SAFE RAIL transportation, with reference NORTE-01-0247-FEDER-069595;co-funded by the European Regional Development Fund (ERDF), through the North Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement;financially supported by Base Funding-UIDB/04708/2020;Programmatic Funding-UIDP/04708/2020 of the CONSTRUCT—Instituto de Estruturas e Constru??es;funded by national funds through the FCT/ MCTES (PIDDAC);Grant No. 2021.04272. CEECIND from the Stimulus of Scientific Employment, Individual Support (CEECIND) - 4th Edition provided by “FCT – Funda??o para a Ciência, DOI : https:// doi. org/ 10. 54499/ 2021. 04272. CEECI ND/ CP1679/ CT0003”。
Wayside monitoring is a promising cost-effective alternative to predict damage in the rolling stock. The main goal of this work is to present an unsupervised methodology to identify out-of-roundness(OOR) damage wheels...
关键词：OOR wheel damage Damage identification Sparse autoencoder Passenger trains Wayside condition monitoring 
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