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The International Journal of Advanced Manufacturing Technology

Erschienen in:

20.11.2019 | ORIGINAL ARTICLE

Thermal error modelling for a high-precision feed system in varying conditions based on an improved Elman network

verfasst von: Haojin Yang, Renpeng Xing, Fuxin Du

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 1-2/2020

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Abstract

A two-axis differential micro-feed system (TDMS) can overcome the accuracy limitation of the conventional drive feed system (CDFS). However, the heat induced by friction in the ball screw, bearings, and motors will lead to axial thermal deformation of the screw, with the deformation being the primary factor restricting the high precision micro-feed. Elman neural networks (ENs) are employed to carry out the thermal error modelling in this paper. To improve the performance of ENs, the differential evolution (DE) algorithm is used to optimize the initial weights and thresholds of the ENs. Complex operating conditions of the TDMS are also considered in the model. The experimental results show that the thermal error residual decreased from 1.73 to 0.88 μm for the DE-ELMAN model. Moreover, the proposed method of thermal error modelling proved to be accurate and robust when used in the varying conditions.

Vorheriger Artikel Influence of manufacturing parameters on the mechanical properties of projection stereolithography–manufactured specimens

Nächster Artikel Development of actuators for ultrasonically assisted grinding of hard brittle materials

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Titel: Thermal error modelling for a high-precision feed system in varying conditions based on an improved Elman network
verfasst von: Haojin Yang
Renpeng Xing
Fuxin Du
Publikationsdatum: 20.11.2019
Verlag: Springer London
Erschienen in: The International Journal of Advanced Manufacturing Technology / Ausgabe 1-2/2020
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI: https://doi.org/10.1007/s00170-019-04605-1

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