CLOUT
发表于 2025-3-28 17:36:26
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TOM
发表于 2025-3-28 19:54:08
SpringerBriefs in Plant Sciencef the actuator model only, so that it reduces substantially the complexity and difficult uncertainties related to the model of a full rail vehicle. The performance and robustness assessments of the state estimator integrated active control system are carried out with the use of a full bogie vehicle model.
含糊
发表于 2025-3-29 01:16:30
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谎言
发表于 2025-3-29 06:57:28
Condition Monitoring of Rail Vehicle Suspension Elements: A Machine Learning Approachd help readers reflect on their own relationship to touch...This book is an invaluable resource for students in undergraduate and graduate courses in healthcare, nursing, education and social work, and to practitioners looking for guidance on this topic..978-981-99-4869-7978-981-99-4870-3
Fulsome
发表于 2025-3-29 09:12:14
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Acquired
发表于 2025-3-29 14:58:42
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NADIR
发表于 2025-3-29 15:48:55
F. Strubelt,B. Münzenberger,R. F. Hüttl influence of the stiffness-adjustable anti-yaw damper, a roller rig test is further performed to compare the FSS yaw damper with other two conventional yaw dampers. The numerical and experimental results suggested that the FSS damper can achieve better adaptive to both low and high wheel/rail conic
致敬
发表于 2025-3-29 21:30:35
S. Rust,D. Lüttschwager,R. F. Hüttlrealistic operation conditions. Thus, the traditional control techniques can be used to assess the tilting system dynamics and to design the control algorithm so that proper tilting performance is ensured. The control algorithm and the tilting performance are tested on a curved and tangent track wit
PON
发表于 2025-3-30 03:54:02
Changes of Problem Representationn gauge bridges..The systems of measuring the forces in the wheel-roller contacts and the axle-box forces have been calibrated, implemented on the rollers and the experimental bogie and successfully tested. The new roller rig mainframe and components of the tilting mechanism are currently in the pro
手势
发表于 2025-3-30 06:30:51
Changes of Problem Representationfeatures of measured vehicle response quantities to classify new and worn wheel profiles with machine learning algorithms. In the third step, the accuracy of classification results is analysed for different states of available track information like track irregularities or rail profile conditions..T