COMPUTATIONAL APPROACH TO IMPROVE BEARINGS BY RESIDUAL STRESSES BASED ON THEIR REQUIRED BEARING FATIGUE LIFE
Price
Free (open access)
Volume
Volume 6 (2018), Issue 4
Pages
10
Page Range
656 - 666
Paper DOI
10.2495/CMEM-V6-N4-656-666
Copyright
WIT Press
Author(s)
F. PAPE, O. MAISS, B. DENKENA & G. POLL
Abstract
In drive systems and component technology a high reliability is very important for machines. Machine element dimensions are calculated for reliability. The properties for these elements are based on conventional manufacturing techniques. Very high stresses are applied on bearings in their operating time. To improve the endurance life, residual stresses can be induced into the subsurface zone. In contrast to a conventional grinding process, the mechanical surface modification process deep rolling is able to induce very high compressive residual stresses. A computational approach was developed to establish an appropriate residual stress depth profile matching the applied loads. Thus, the costs of manufacturing can be chosen in accordance to the required properties. The method to determine the residual stresses is based on an iterative reverse calculation of an existing bearing fatigue life model of Ioannides et al. The model originates from the approach of Lundberg and Palmgren (1947) including a stress fatigue limit tu. For the term ti, the fatigue criterion of Dang-Van is applied. The equation accounts for the maximum orthogonal shear stress and the local hydrostatic pressure phyd, corrected for residual and hoop stress. The inputs into the computational model are the stresses on the surface, which are simulated based on the load and geometry of the contact between roller and bearing surface. As an output the required residual stress profile underneath the bearings raceway is given to achieve a bearing fatigue life as required for the given application. In order to verify the model, the bearing fatigue life was experimentally determined for a given residual stress profile by experiments.
Keywords
bearing fatigue life, inverse computational model, residual stresses