The accurate and timely identification of system malfunctions is an important capability for helicopter flight crews. Recently, a large emphasis has been placed on the development of Health and Usage Monitoring Systems (HUMS) and the aircrew interfaces for these systems to aid the flight crew in performing this important task. HUMS systems generate much more information with better capability than existing fault detection systems, necessitating the development of new methods to effectively integrate and present the information in a timely, useful, and readily interpretable manner. As part of an effort to investigate aircrew information requirements for managing mechanical fault and damage situations, Pennsylvania State University Applied Research Laboratory (ARL) has analyzed transitional data sets using HUMS features and investigated diagnosis variables for an expert inference system. The correlation of statistical feature values with equipment health, torque levels, and operational speed is necessary for the development of such an inference system. Transitional data obtained from the ARL Mechanical Diagnostics Test Bed (MDTB) is used to develop these relations, which will provide more realistic outputs for HUMS simulation scenarios. The statistical features generated during gearbox transitional failure, feature correlation with failure mode, and torque/speed functional dependencies are discussed and the results are provided.


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    Title :

    Generation of HUMS diagnostic estimates using: transitional data


    Contributors:


    Publication date :

    2000


    Size :

    9 Seiten, 5 Bilder, 2 Tabellen, 12 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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