Effects of shaft surface texture on journal bearing pressure distribution

This paper presents an analysis of the pressure development of journal bearing in a various shaft surface texture and velocity variations using a proposed neural network. The effects of the parameters, which act on performances of journal bearing, on the pressure development and load-carriage capacity have been examined such as the number of revolution and shaft surface texture. The data from the experiments are used as learning information for the neural network to establish a reliable prediction model that can be applied to journal bearings and the modelʹs performance is verified.