Generalised NARX shunting neural network modelling of friction

C.X. Wong; K. Worden

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Generalised NARX shunting neural network modelling of friction

机译：摩擦的广义NARX分流神经网络建模

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摘要

This paper describes the modelling of dry friction using a NARX (Nonlinear AutoRegressive with eXogeneous inputs) type shunting neural network model. An ensemble model is then constructed by combining the shunting neural network model with the physics based DNLR (dynamic nonlinear regression) Maxwell slip model.

机译：本文描述了使用NARX（带有异质输入的非线性自回归）类型的并联神经网络模型对干摩擦进行建模。然后，通过将分流神经网络模型与基于物理的DNLR（动态非线性回归）麦克斯韦滑移模型相结合，构建整体模型。

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来源
《Mechanical systems and signal processing》 |2007年第1期|p.553-572|共20页
作者
C.X. Wong; K. Worden;
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作者单位

Dynamics Research Group, Department of Mechanical Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom;

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原文格式 PDF
正文语种 eng
中图分类机械制造工艺;
关键词
NARX; neural networks; dry friction; maxwell slip;

机译：NARX;神经网络;干摩擦;麦克斯韦滑移;

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Generalised NARX shunting neural network modelling of friction

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