Development of Prognostics Techniques for Surface Defect Growth in Railroad Bearing Rolling Elements

Author

Nancy De Los Santos, The University of Texas Rio Grande Valley

Date of Award

7-2019

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical Engineering

First Advisor

Dr. Constantine Tarawneh

Second Advisor

Dr. Robert Jones

Third Advisor

Dr. Arturo Fuentes

Abstract

One of the major causes of failure in railroad bearings used in freight service is rolling contact fatigue (RCF). RCF is due to subsurface inclusions which are a result from impurities in the steel that is used to fabricate the bearings. Once the bearings initiate subsurface fatigue cracks, they will then propagate upward and initiate spalling of the rolling surfaces. These spalls will begin small and continuously propagate with operation as this induces additional crack forming and spalling. Studies have indicated that bearing temperature is not a good indicator of spall initiation. In many cases, the temperature of the bearing increases markedly once the spall has propagated across major portions of the raceway. However, vibration signatures can be used to detect spall initiation and can track spall deterioration. No monitoring system technique can indicate the growth rate of a spall nor can it determine the bearing residual useful life. Therefore, the principle objective of this study is to develop reliable prognostic models for spall growth within railroad bearings that are based on actual service life testing rather than theoretical simulations. The data used to develop the models presented in this study have been acquired from laboratory and field testing that initiated in 2010. The growth models in this study are for spalls that initiated on the bearing inner (cone) and outer (cup) rings. Coupling these prognostic

models with a vibration-based bearing condition-monitoring algorithm previously developed, will provide the rail industry with an efficient tool that can be used to propose proactive maintenance schedules that will reduce unnecessary and costly train stoppages and delays and will prevent catastrophic derailments.

Comments

Copyright 2019 Nancy De Los Santos. All Rights Reserved.

https://go.openathens.net/redirector/utrgv.edu?url=https://www.proquest.com/dissertations-theses/development-prognostics-techniques-surface-defect/docview/2304960892/se-2?accountid=7119

Recommended Citation

De Los Santos, Nancy, "Development of Prognostics Techniques for Surface Defect Growth in Railroad Bearing Rolling Elements" (2019). Theses and Dissertations. 445.
https://scholarworks.utrgv.edu/etd/445