Term of Award
Fall 2024
Degree Name
Master of Science, Electrical and Computer Engineering
Document Type and Release Option
Thesis (open access)
Copyright Statement / License for Reuse
Digital Commons@Georgia Southern License
Department
Department of Electrical and Computer Engineering
Committee Chair
Rami Haddad
Committee Member 1
Fernando Rios
Committee Member 2
Mohammad Ahad
Abstract
This work proposes a method of detecting physical damage to bearing races in a rotational assembly by means of magnetic reluctance sensors generating a signal from a rotating gear-tooth wheel. A nominally sinusoidal signal is generated based on the rotation of a gearwheel with regularly spaced voids and lands. Detection is based on the time variance of the signal periodically in relation to the gearwheel and the bearing damage. The purpose of this work is to propose a process to detect and classify bearing race defects using existing sensors and neural networks for hazardous area equipment applications.
Recommended Citation
Daly, Collin, "Detecting Bearing Race Defects with Inductive Magnetic Reluctance Sensors and Artificial Neural Networks" (2024). Electronic Theses and Dissertations. 2883.
https://digitalcommons.georgiasouthern.edu/etd/2883
Research Data and Supplementary Material
No
