Paula J. Dempsey

Spiral bevel gear damage detection using decision fusion analysis

A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.

Current Status of Hybrid Bearing Damage Detection

Advances in material development and processing have led to the introduction of ceramic hybrid bearings for many applications. The introduction of silicon nitride hybrid bearings into the high-pressure oxidizer turbopump on the space shuttle main engine led NASA to solve a highly persistent and troublesome bearing problem. Hybrid bearings consist of ceramic balls and steel races. The majority of hybrid bearings utilize Si3N4 balls. The aerospace industry is currently studying the use of hybrid bearings and, naturally, the failure modes of these bearings become an issue in light of the limited data available. In todays turbine engines and helicopter transmissions, the health of the bearings is detected by the properties of the debris found in the lubrication line when damage begins to occur. Current oil debris sensor technology relies on the magnetic properties of the debris to detect damage. Because the ceramic rolling elements of hybrid bearings have no metallic properties, a new sensing system must be developed to indicate the system health if ceramic components are to be safely implemented in aerospace applications. The ceramic oil debris sensor must be capable of detecting ceramic and metallic component damage with sufficient reliability and forewarning to prevent a catastrophic failure. The objective of this research is to provide a background summary on what is currently known about hybrid bearing failure modes and to report preliminary results on the detection of silicon nitride debris in oil using a commercial particle counter.

Decision fusion analysis detects spiral bevel gear damage

A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies - oil debris analysis and vibration were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.