Wavelet-based acoustic emission detection method with adaptive thresholding

Sunil Menon; Jeffrey N. Schoess; Rida Hamza; Darryl Busch

doi:10.1117/12.388093

12 June 2000 Wavelet-based acoustic emission detection method with adaptive thresholding

Sunil Menon, Jeffrey N. Schoess, Rida Hamza, Darryl Busch

Proceedings Volume 3986, Smart Structures and Materials 2000: Sensory Phenomena and Measurement Instrumentation for Smart Structures and Materials; (2000) https://doi.org/10.1117/12.388093
Event: SPIE's 7th Annual International Symposium on Smart Structures and Materials, 2000, Newport Beach, CA, United States

Abstract

Reductions in Navy maintenance budgets and available personnel have dictated the need to transition from time-based to 'condition-based' maintenance. Achieving this will require new enabling diagnostic technologies. One such technology, the use of acoustic emission for the early detection of helicopter rotor head dynamic component faults, has been investigated by Honeywell Technology Center for its rotor acoustic monitoring system (RAMS). This ambitious, 38-month, proof-of-concept effort, which was a part of the Naval Surface Warfare Center Air Vehicle Diagnostics System program, culminated in a successful three-week flight test of the RAMS system at Patuxent River Flight Test Center in September 1997. The flight test results demonstrated that stress-wave acoustic emission technology can detect signals equivalent to small fatigue cracks in rotor head components and can do so across the rotating articulated rotor head joints and in the presence of other background acoustic noise generated during flight operation. This paper presents the results of stress wave data analysis of the flight-test dataset using wavelet-based techniques to assess background operational noise vs. machinery failure detection results.

Citation Download Citation

Sunil Menon, Jeffrey N. Schoess, Rida Hamza, and Darryl Busch "Wavelet-based acoustic emission detection method with adaptive thresholding", Proc. SPIE 3986, Smart Structures and Materials 2000: Sensory Phenomena and Measurement Instrumentation for Smart Structures and Materials, (12 June 2000); https://doi.org/10.1117/12.388093

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