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Identification of pre-sliding and sliding friction dynamics: Grey box and black-box models

机译:识别预滑动和滑动摩擦动力学:灰箱和黑箱模型

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摘要

The non-linear dependence of pre-sliding and sliding friction forces on displacement and velocity is modelled using different physics-based and black-box approaches including various Maxwell-Slip models, neural networks, non-parametric (local) models and recurrent networks. The efficiency and accuracy of these identification methods is compared for an experimental time series where the observed friction force is predicted from the measured displacement and estimated velocity. All models, although varying in their degree of accuracy, show good prediction capability of friction. Finally, it is shown that better results can be achieved by using an ensemble of the best models for prediction.
机译:预滑动和滑动摩擦力对位移和速度的非线性依赖性是使用不同的基于物理学的方法和黑匣子方法建模的,其中包括各种Maxwell-Slip模型,神经网络,非参数(局部)模型和递归网络。在实验时间序列中比较了这些识别方法的效率和准确性,在该时间序列中,根据测量的位移和估计的速度预测了观察到的摩擦力。所有模型尽管准确性不同,但都显示出良好的摩擦预测能力。最后,结果表明,通过使用最佳模型的组合进行预测可以实现更好的结果。

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