Rolling Bearing Life Prediction. Corrections for Material and Operating Conditions. Part II: The Correction Factors

1988 ◽  
Vol 110 (1) ◽  
pp. 7-12 ◽  
Author(s):  
T. E. Tallian

Computer based rolling bearing analysis programs exist which provide models for load and stress distribution, EHD conditions, heat balance and fatigue life prediction for rolling bearings and machine assemblies comprising such bearings. Fatigue life prediction is generally based on the ANSI standard. This two-part paper offers correction factors for refining the life prediction by modeling effects of material and operating variables. The corrections can be applied to the ANSI-predicted life of a complete bearing or to predicted lives of stressed volume elements in the bearing, with subsequent summation over the stressed volumes. Formulations are presented with a view to their incorporation into dynamic bearing analysis computer programs. This second part of the paper comprises the equations for the correction factors, the complete life correction, an Appendix showing logic flow for the calculations, and figures illustrating the behavior of the correction factors.

1988 ◽  
Vol 110 (1) ◽  
pp. 2-6 ◽  
Author(s):  
T. E. Tallian

Computer based rolling bearing analysis programs exist which provide models for load and stress distribution, EHD conditions, heat balance and fatigue life prediction for rolling bearings and machine assemblies comprising such bearings. Fatigue life prediction is generally based on the ANSI standard. This two-part paper offers correction factors for refining the life prediction by modeling effects of material and operating variables. The corrections can be applied to the ANSI-predicted life of a complete bearing or to predicted lives of stressed volume elements in the bearing, with subsequent summation over the stressed volumes. Formulations are presented with a view to their incorporation into dynamic bearing analysis computer programs. This first part of the paper comprises the general model, basic life calculation and the nomenclature for both parts of the paper.


2018 ◽  
Vol 157 ◽  
pp. 02024 ◽  
Author(s):  
Bohuš Leitner ◽  
Lucia Figuli

Problems of fatigue life prediction of materials and structures are discussed in the paper. Service loading is assumed as a continuous loading process with possible discontinuous events, which are caused by various operating conditions. The damage in a material is due to a cumulative degradation process. The damaging process is then represented either by rain-flow matrices or by a fatigue damage function which is derived using some hypothesis of a fatigue failure criterion. Presented theoretical procedure enables a very effective estimation of a service life and/or reliable evaluation of residual life of any structures under various types of loading and environmental conditions. This approach creates a good basis for powerful expert systems in structural and mechanical engineering. The aim of the paper is to present briefly some results of analysis of load-bearing steel structure loads of special railway crane PKP 25/20i which was utilized in some specific ad relatively hard operating conditions. Virtual models of the structure were being used in an analysis of acting working dynamics loads influence to be able to forecast fatigue life of load-bearing of the crane jib.


Author(s):  
D. GARY HARLOW

Probability analyses are increasingly being used for reliability and durability assessments for life prediction of engineered components and systems. Nevertheless, many of the current analyses are predominately statistical rather than probabilistic. Fatigue life prediction has historically been based on the safe-life or the crack growth approaches, both of which are empirically based. Consequently, they do not adequately reflect long-term operating conditions, or identify the sources and extent of their contributions to variability. A comparison between probability and statistical approaches for fatigue life prediction is developed herein. Using simple crack growth models, the variability inherent in S-N response can be related to key random variables that are readily identified in the models. The identification and quantification of these variables are paramount for predicting fatigue lives. The effectiveness of probability modeling compared to statistical methodologies is shown through the analysis of an extensive set of S-N data for 2024-T4 aluminum alloy. Subsequently, the probability approach is demonstrated with S-N data for SUJ2 steel, in which two distinct failure modes are operative. Variability associated with manufacturing and material variables are considered. The adoption of this technique to put life prediction on a sound scientific and probabilistic basis is recommended.


1990 ◽  
Vol 112 (1) ◽  
pp. 23-26 ◽  
Author(s):  
P. K. Gupta ◽  
T. E. Tallian

Models for the correction of classical fatigue life for material imperfections and severity of operating conditions in rolling bearings are implemented in a bearing dynamics computer code. The significance of life correction factors is then demonstrated for both ball and cylindrical roller bearings over a range of operating conditions.


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