NDLI: Calculation method of convective heat transfer coefficients for thermal simulation of a spindle system based on RBF neural network

Content Provider	Springer Nature Link
Author	Li, Dianxin Feng, Pingfa Zhang, Jianfu Wu, Zhijun Yu, Dingwen
Copyright Year	2013
Abstract	Results from the temperature field and thermal deformation simulation of a spindle system are greatly affected by the accuracy of convective heat transfer coefficients (CHTCs). This paper presents a new method based on radial basis function (RBF) neural network to calculate CHTCs. First, the temperature field and thermal deformations of a spindle system were obtained by experimental and finite-element (FE) methods. However, the simulation results are significantly different from the experimental results because boundary conditions used for the FE model were derived empirically. Second, the relationship between the simulated temperature values and CHTCs were established by a RBF neural network. Using the experimental temperature values as an input vector of the RBF neural network, CHTCs of the spindle system can be predicted through an iterative calculation taking 14 cycles. Finally, the effectiveness of the proposed method was proved using steady-state and transient-state analyses of the spindle system. Results from the steady-state simulation show that temperature errors were less than 4 % at the seven thermal-critical points and deformation errors in the three directions were less than 6 %. Results from the transient-state simulation of the spindle system show that the variations for each of the thermal characteristics are in good agreement with the experimental results. The method provides guidance for modifying boundary conditions of a FE model.
Starting Page	1445
Ending Page	1454
Page Count	10
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	70
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2013-10-23
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Convective heat transfer coefficient (CHTC) FE simulation Thermal characteristic RBF neural network Spindle system Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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