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  • 1
    facet.materialart.
    Unknown
    Data Fusion Tool for Spiral Bevel Gear Condition Indicator Data (2014)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Tests 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.
    Keywords: Mechanical Engineering
    Type: GRC-E-DAA-TN12922 , E-18840 , Machinery Failure Prevention Technology (MFPT) 2014 Conference; Feb 03, 2014 - Feb 06, 2014; Virginia Beach, Virginia; United States
    Format: application/pdf
    Location Call Number Expected Availability
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    NASA TECHNICAL REPORTS
  • 2
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    Unknown
    Evaluation of Gear Condition Indicator Performance on Rotorcraft Fleet (2010)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The U.S. Army is currently expanding its fleet of Health Usage Monitoring Systems (HUMS) equipped aircraft at significant rates, to now include over 1,000 rotorcraft. Two different on-board HUMS, the Honeywell Modern Signal Processing Unit (MSPU) and the Goodrich Integrated Vehicle Health Management System (IVHMS), are collecting vibration health data on aircraft that include the Apache, Blackhawk, Chinook, and Kiowa Warrior. The objective of this paper is to recommend the most effective gear condition indicators for fleet use based on both a theoretical foundation and field data. Gear diagnostics with better performance will be recommended based on both a theoretical foundation and results of in-fleet use. In order to evaluate the gear condition indicator performance on rotorcraft fleets, results of more than five years of health monitoring for gear faults in the entire HUMS equipped Army helicopter fleet will be presented. More than ten examples of gear faults indicated by the gear CI have been compiled and each reviewed for accuracy. False alarms indications will also be discussed. Performance data from test rigs and seeded fault tests will also be presented. The results of the fleet analysis will be discussed, and a performance metric assigned to each of the competing algorithms. Gear fault diagnostic algorithms that are compliant with ADS-79A will be recommended for future use and development. The performance of gear algorithms used in the commercial units and the effectiveness of the gear CI as a fault identifier will be assessed using the criteria outlined in the standards in ADS-79A-HDBK, an Army handbook that outlines the conversion from Reliability Centered Maintenance to the On-Condition status of Condition Based Maintenance.
    Keywords: Aircraft Design, Testing and Performance
    Type: E-17255 , AHS 66th Annual Forum and Technology Display: Rising to New Heights in Vertical Lift Technology; May 11, 2010 - May 13, 2010; Phoenix, AZ; United States
    Format: application/pdf
    Location Call Number Expected Availability
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    NASA TECHNICAL REPORTS
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