An optimized thermal network model to estimate thermal performances on a pair of angular contact ball bearings under oil-air lubrication. (25th February 2018)

• Record Type: Journal Article
• Authors: De-xing, Zheng; Weifang, Chen; Miaomiao, Li
• Is Part Of: Applied thermal engineering. Volume 131(2018)
• Page Start: 328
• Page End: 339
• Publication Date: 2018-02-25
• Subjects: Angular contact ball bearing -- Thermal resistance network -- Temperature rise; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.12.019
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Ball loads with centrifugal force, gyroscopic moment and thermal expansion. Structure and assembly constraints effects on bearing temperature. An optimized nodes planning scheme for angular contact ball bearings. A more precise prediction model with less data overhead. Abstract: To estimate thermal performances of angular contact ball bearings is essential for operating precision and service life of angular contact ball bearings. However, a simple and accurate model estimating the bearing temperature is needed but absent so far. Considering the centrifugal force, gyroscopic moment and thermal expansion, ball loads equilibrium model was first established to analyze the bearing loads. The radial and axial heat transfer, especially the effect of structural constraints on bearings temperature was well characterized as well as the bearing mounting arrangement, and then an enhanced node planning scheme was proposed. With their surroundings considered, an optimized thermal grid model for a pair of front bearings mounted in the high-speed spindle was developed by using this scheme. Next Newton-Raphson method was employed to obtain the numerical solution by Matlab. The bearing temperature variation, moreover, was tested to validate the developed model. The results indicate that both series of results agree well. Compared with the presented models, the deviation between the calculation results and the test values is reduced to less than 9%. As a result, the bearing temperature rise can be better forecasted, which may be beneficial to improve bearing operating accuracy as well as bearing service life.