有特色
发表于 2025-3-23 11:43:15
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medium
发表于 2025-3-23 14:53:34
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都相信我的话
发表于 2025-3-23 19:39:19
https://doi.org/10.1007/978-3-030-46263-5Data-driven Methods; Fault Detection and Diagnosis; Traction Systems; High-speed Trains; Principal Compo
V洗浴
发表于 2025-3-24 00:41:30
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GULLY
发表于 2025-3-24 02:40:14
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DUCE
发表于 2025-3-24 09:49:00
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Keshan-disease
发表于 2025-3-24 11:10:26
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Charade
发表于 2025-3-24 18:41:21
Deep PCA-Based FDD MethodsThis chapter develops a real-time incipient FDD method named deep PCA (DPCA) for traction systems in high-speed trains. This scheme adopting multivariate statistics is composed of multiple data processing layers to extract more accurate signal features of traction systems.
不整齐
发表于 2025-3-24 19:11:05
PCA and Kullback-Leibler Divergence-Based FDD MethodsThis chapter presents an improved incipient FD method based on Kullback-Leibler divergence (KLD) under multivariate statistical analysis frame. Different from the traditional MVA-based FD methods, this methodology can detect slight anomalous behaviors by comparing the PDF online with the reference PDF obtained from large scale off-line datasets.
确定
发表于 2025-3-24 23:47:41
PCA and Hellinger Distance-Based FDD MethodsIncipient faults in high-speed trains are usually masked by noises and disturbances from both process and sensors, which severely increases the difficulty of incipient FDD tasks.