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Data Fusion Tool for Spiral Bevel Gear Condition Indicator DataTests were performed on two spiral bevel gear sets in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig to simulate the fielded failures of spiral bevel gears installed in a helicopter. Gear sets were tested until damage initiated and progressed on two or more gear or pinion teeth. During testing, gear health monitoring data was collected with two different health monitoring systems. Operational parameters were measured with a third data acquisition system. Tooth damage progression was documented with photographs taken at inspection intervals throughout the test. A software tool was developed for fusing the operational data and the vibration based gear condition indicator (CI) data collected from the two health monitoring systems. Results of this study illustrate the benefits of combining the data from all three systems to indicate progression of damage for spiral bevel gears. The tool also enabled evaluation of the effectiveness of each CI with respect to operational conditions and fault mode.
Document ID
20140008623
Acquisition Source
Glenn Research Center
Document Type
Conference Paper
Authors
Dempsey, Paula J.
(NASA Glenn Research Center Cleveland, OH United States)
Antolick, Lance J.
(RMCI, Inc. Huntsville, AL, United States)
Branning, Jeremy S.
(RMCI, Inc. Huntsville, AL, United States)
Thomas, Josiah
(RMCI, Inc. Huntsville, AL, United States)
Date Acquired
June 30, 2014
Publication Date
February 3, 2014
Subject Category
Mechanical Engineering
Report/Patent Number
E-18840
GRC-E-DAA-TN12922
Report Number: E-18840
Report Number: GRC-E-DAA-TN12922
Meeting Information
Meeting: Machinery Failure Prevention Technology (MFPT) 2014 Conference
Location: Virginia Beach, Virginia
Country: United States
Start Date: February 3, 2014
End Date: February 6, 2014
Sponsors: Society for Machinery Failure Prevention Technology
Funding Number(s)
WBS: WBS 380046.02.03.02.02.03
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
health monitoring
gears
data fusion
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