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An Online Modeling Method for Real-time Thermal Error Compensation on High-speed Machines Based on RBF Neural Network Theory

机译:基于RBF神经网络理论的高速机器实时热误差补偿在线建模方法

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摘要

This paper studies the modeling method based on RBF (Radial-Basis Function) neural network according to its learning ability, and a new neural network online model has been set up. The comparison and analysis result of the case studies shows that, when changing the working condition, the compensation effect of online modeling method is better than offline modeling method and the online model can better reflect the thermal characteristics of High-speed machine tool.
机译:本文研究了根据其学习能力的基于RBF(径向基函数)神经网络的建模方法,并建立了一种新的神经网络在线模型。案例研究的比较和分析结果表明,在改变工作条件时,在线建模方法的补偿效果优于离线建模方法,并且在线模型可以更好地反映高速机床的热特性。

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