Lampoon 发表于 2025-3-21 19:57:56
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Statistical Evaluation of Machine Learning for Vibration Data,om large quantities of data collected under varying conditions to make predictions, such as detection, identification, and characterization. Current ML implementation consists of training a model for narrow, task-specific needs, such as training a neural network to detect the presence of structural肉体 发表于 2025-3-22 02:16:28
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Optimal Modeling of Deep Groove Ball Bearings for Application in Multibody Dynamics Simulations,e normal contact force between the rolling elements and the two bearing races are established, including the effects of raceway surface roughness. Various contact force models with different hysteresis damping formulations are examined in order to select the best suited for the application. The bearMatrimony 发表于 2025-3-22 16:38:50
Utilization of Bridge Acceleration Response for Indirect Strain Sensing,onse under daily traffic loading. However, deploying and maintaining strain sensors is costly and labor-intensive compared to acceleration sensors. To address this issue, we propose a neural network architecture that can perform indirect sensing by estimating strain from measured acceleration responMatrimony 发表于 2025-3-22 19:25:27
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Physics-Informed Machine Learning Part II: Applications in Structural Response Forecasting,interpretability of predictive models. By incorporating physical laws and constraints into the learning process, physics-informed machine learning enables more robust predictions and reduces the need for large amounts of training data. In part II of this two-part series, the authors present structur使迷惑 发表于 2025-3-23 05:03:15
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Understanding High-Frequency Modes in Electromechanical Impedance Measurement Using Noncontact Vibr measurements are recorded via a bonded piezoelectric transducer, at a high-frequency range, typically 30 kHz and above. Because EMI measurements are single input single output, the peaks in these measurements can be related to either mechanical, electrical, or coupled electromechanical modes, espec