Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie
Timely detection and efficient recognition of fault are challenging for the bogie of high-speed train (HST), owing to the fact that different types of fault signals have similar characteristics in the same frequency range. Notice that convolutional neural networks (CNNs) are powerful in extracting h...
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Main Authors: | Kaiwei Liang, Na Qin, Deqing Huang, Yuanzhe Fu |
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Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/4501952 |
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