Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2005
Title: Intelligence modeling of the transient asperity temperatures in meshing spur gears
Authors: Atan, Ebubekir
Özdemir, Serhan
Keywords: Genetic algorithms
Surface failure neural networks
Transient temperature rise
Spur gears
Issue Date: Jan-2005
Publisher: Elsevier Ltd.
Source: Atan, E., and Özdemir, S. (2005). Intelligence modeling of the transient asperity temperatures in meshing spur gears. Mechanism and Machine Theory, 40(1), 119-127. doi:10.1016/j.mechmachtheory.2004.06.006
Abstract: Temperature rise in the contact zone of meshing gears is a serious problem in gear design. The temperature rise on lubricated surfaces may result in the significant decrease on the material strength and lubricant viscosity which reduces the film thickness, causing solid to solid contact. The equations and the evaluations of the rise in temperature were given in [Proc. VDI Berichte 2 (1665) (2002) 615-626] and reiterated in this paper briefly. The data from [Proc. VDI Berichte 2 (1665) (2002) 615-626] are used to establish an artificial intelligence model where a multi layer feedforward neural network has been employed. The model accepts surface roughness, gear ratio, horsepower and the number of teeth as input variables, and outputs calculated pinion surface asperity temperatures. The aim of the present work is to provide a straightforward and simple way to compute the asperity temperature rise for a given set of variables, R-square value for the computed temperature values proves the method satisfactory.
URI: https://doi.org/10.1016/j.mechmachtheory.2004.06.006
http://hdl.handle.net/11147/2005
ISSN: 0094-114X
0094-114X
1873-3999
Appears in Collections:Mechanical Engineering / Makina Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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