(Dr. Tom Kurfess, advisor)
"Open-celled Microcellular Thermoplastic Foams"
Bearings are paramount components of rotating machinery and are widely used in industrial mechanical machinery. Bearing failure is one of the main causes of breakdowns in machinery and can result in costly downtime. Preventive maintenance and statistical replacement of bearings are common practices in industry. Machine vibration has been a popular technique to monitor the condition of bearings, and recently an attempt to include different sensors has received considerable attention.
Georgia Tech has been developing techniques to improve condition monitoring of machinery. Previous work has acquired accelerometer and acoustic emission data from tapered roller bearings to developed signal analysis, diagnostics, and prognostic techniques. This work has concentrated in the areas of instrumentation and system optimization. The aim of this thesis was to enhance the existing experimental setup with multiple sensors to test ball bearings. The instrumented sensors monitor vibrations, elastic strain waves, bearing temperature, lubricant temperature, lubricant flow, rotational speed, and changes of electrostatic field nearby rolling elements.
This research employed the test equipment to initiate and propagate cracks in ball bearings. Capabilities of High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) to detect bearing defect have successfully extended to ball bearings. In the presence of inner raceways defects, the increase in accelerometer and acoustic emission Root-Mean-Square complements spectral analysis.