Acoustic Emission Bearing Fault Diagnostics System

Project Summary

Proposal Number:
Project Title:Acoustic Emission Bearing Fault Diagnostics System
Small Business Concern: AI Signal Research, Inc. 3322 South Memorial Parkway Suite 67 Huntsville, AL 35801
Research Institution: Georgia Institute of Technology School of Aerospace Engineering Atlanta, GA 30332-0150
Principal Investigator/Project Manager: Dr. Jen-Yi Jong
Technical Abstract: AI Signal Research (ASRI) and Georgia Institute of Technology (GIT) propose to develop an Acoustic Emission Bearing Fault Diagnostics System (AEBFDS) which utilizes state-of-the-art high frequency acoustic emission (AE) sensor technology coupled with an innovative nonlinear bi-spectral analysis technique for bearing fault detection. The high frequency AE signal can provide immunity from structural and rotordynamic vibration noise within a turbomachinery system, therefore focusing the diagnostic assessment on the local bearing condition. The proposed AEBFDS system utilizes AE sensors to capture the release of energy in the kilohertz to megahertz range emanating from the bearing defect region which can provide meaningful diagnostic signatures through envelope analysis. In addition, the AEBFDS system utilizes innovative nonlinear bi-spectral analysis to identify characteristic bearing modulation/sideband fault pattern associated with bearing fault mechanisms. Such an AEBFDS system can provide an earlier and more reliable warning of bearing degradation than can be achieved with a low frequency vibration monitoring system. Phase I objectives are to define system requirements and demonstrate the relative benefits of the AEBFDS system. The overall objective of this STTR study will be to build a prototype hardware/software system for demonstration in Phase II and a commercial system for industrial application in Phase III.
Potential Commecial Applications: A low-cost acoustic emission based bearing fault diagnostics system has strong commercial application. In particular, in the commercial transportation and power generation industries, along with the manufacturing sectors utilizing critical bearings in their machinery drive train systems. An effective Acoustic Emission Bearing Fault Diagnostics System in these applications would reduce risks of catastrophic hardware losses and plant down-time.