Intelligence modeling of the transient asperity temperatures in meshing spur gears

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.