A Bearing Life Prediction Method for Utilizing Progressive Functional Surface Damage Analysis from a Debris Contaminated Lubrication Environment

1999-01-2793

09/13/1999

Event
International Off-Highway & Powerplant Congress & Exposition
Authors Abstract
Content
Many lubrication environments in various equipment applications are inherently contaminated with debris and require mechanical components that are, as much as possible, resistant to the potential detrimental effects of debris particles. Many design engineers and lubricant specialists often overlook potential relationships between the various component failure modes, lubricant debris contamination levels, and engineering solutions that are created to overcome them. In addition, design engineers are in need of an analysis tool that can combine the various amounts of cumulative bearing damage occurring over time. As an example, bearing functional surfaces in many cases are progressively damaged over the life of the equipment. A new surface analysis tool is available which allows surface damage analysis to be completed at various stages of equipment life. This new surface analysis tool is appropriately called Debris Signature Analysis(sm). Data from these surface analysis methods can be used to demonstrate a new bearing life prediction model. When the life model is combined with cumulative damage rules, it can lead to assessment of the progressive damage developing in a debris contaminated lubrication system over time. Results of assessments will be discussed and this method will be described in the context of a design tool.
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DOI
https://doi.org/10.4271/1999-01-2793
Pages
10
Citation
Fox, G., Martens, M., and Nixon, H., "A Bearing Life Prediction Method for Utilizing Progressive Functional Surface Damage Analysis from a Debris Contaminated Lubrication Environment," SAE Technical Paper 1999-01-2793, 1999, https://doi.org/10.4271/1999-01-2793.
Additional Details
Publisher
Published
Sep 13, 1999
Product Code
1999-01-2793
Content Type
Technical Paper
Language
English