Theses and Dissertations - UTB/UTPA

Date of Award


Document Type


Degree Name

Master of Science (MS)


Mechanical Engineering

First Advisor

Dr. Constantine Tarawneh

Second Advisor

Dr. Javier Kypuros

Third Advisor

Dr. Arturo Fuentes


Derailments can often lead to great damage, loss of lives, and massive costs associated with the railroad infrastructure. A significant cause of derailments is premature bearing failure, and therefore bearing condition-monitoring systems that can detect developing defects are of great importance. Based on an investigation conducted at the University of Texas-Pan American on the development of a vibration and temperature monitoring system, an algorithm is devised utilizing various vibration analysis techniques. The proposed algorithm determines whether a bearing is defective, the type of defect present, the defective component (i.e. cup, cone, or roller), and the size of the defect. Speed-dependent thresholds based on the root-mean-square (RMS) of the vibration signal are used to differentiate between a defective bearing and a healthy (defect-free) bearing; the type and location (component) of the defect is determined by tracking the magnitude of the fundamental defect frequencies. Finally, correlations of RMS vs. size are utilized to estimate the area and perimeter.


Copyright 2012 Iris Lizeth Alvarado. All Rights Reserved.

Granting Institution

University of Texas-Pan American