Electronic Theses and Dissertations





Date of Award


Document Type


Degree Name

Master of Science


Mechanical Engineering


Design and Mechanical Systems

Committee Chair

Gary Qi

Committee Member

Steve Wayne

Committee Member

Teong Tan


Muthireddy, Rajesh. M. S. The University of Memphis. May/2010. Condition Monitoring of electric motors using Motor Current Signature Analysis and Acoustic Emission. Gary Qi. Electric motors are critical components in industrial processes and rolling element bearings are an essential part of them. Studies show that most of the motors fail due to the failure of bearings inside them. The bearings are by nature subjected to various kinds of loads including eccentric forces due to the attachment of power transmission units such as gears, pulleys and fans, and as such bearing life depends on the load type, magnitude and operating conditions. Monitoring the bearing condition can greatly reduce manufacturing down-time and improve maintenance costs. In this thesis, I compare two non-invasive, online condition monitoring techniques for electric motors independently subjected to eccentric loading, bearing contamination and elevated temperatures. A test rig was built for the study. Results indicate that early electric motor bearing failure detection is best captured by Acoustic Emission (AE) where as Motor Current Signature Analysis (MCSA) can be used to assess and interpret the overall electrical condition of the motor.


Data is provided by the student.

Library Comment

dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.