Results 191 to 200 of about 12,721 (256)
Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation. [PDF]
PLoS OneNguyen VT, Diep QB.
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Intelligent diagnosis of gearbox in data heterogeneous environments based on federated supervised contrastive learning framework. [PDF]
Sci RepBai R +7 more
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Entropy-Aided Meshing-Order Modulation Analysis for Wind Turbine Planetary Gear Weak Fault Detection under Variable Rotational Speed. [PDF]
Entropy (Basel)Zhi S, Wu H, Shen H, Wang T, Fu H.
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Physics-informed self-supervised diagnosis of rotating machinery using latent ODEs and transformer encoders. [PDF]
PLoS OneAmin MA +4 more
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Fault Diagnosis Method for Shearer Arm Gear Based on Improved S-Transform and Depthwise Separable Convolution. [PDF]
Sensors (Basel)Wu H, Zhou H, Liu C, Cheng G, Pang Y.
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Reliability Model for Planetary Gear Trains
Journal of Mechanisms, Transmissions, and Automation in Design, 1983A reliability model is presented for planetary gear trains in which the ring gear is fixed, the sun gear is the input, and the planet arm is the output. The input and output shafts are coaxial and the input and output torques are assumed to be coaxial with these shafts. Thrust and side loading are neglected.
M. Savage, C. A. Paridon, J. J. Coy
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Topological Synthesis of Planetary Gear Trains
Applied Mechanics and Materials, 2010Application of topological graphs to analyze and synthesize planetary gear trains (PGTs) is an effective approach in searching for innovative planetary trains. Two topological graphs of basic structure and three fundamental units of PGTs are established as the basis of topological synthesis.
Ya Feng He, Qing Yu, You Ming Wang
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