Jaeyong Kang1, Chul-Su Kim2, Jeong Won Kang3, Jeonghwan Gwak1,4,5,6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1-14, 2022, DOI:10.32604/cmc.2022.023641
Abstract The anomaly detection of the brake operating unit (BOU) in the brake systems on metro vehicle is critical for the safety and reliability of the trains. On the other hand, current periodic inspection and maintenance are unable to detect anomalies in an early stage. Also, building an accurate and stable system for detecting anomalies is extremely difficult. Therefore, we present an efficient model that use an ensemble of recurrent autoencoders to accurately detect the BOU abnormalities of metro trains. This is the first proposal to employ an ensemble deep learning technique to detect BOU abnormalities in metro train braking systems.… More >
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