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• W2134788934 abstract "For an efficient maintenance of a diverse fleet of airand rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. In this dissertation, we present theory and applications of polyspectral signal processing techniques for condition based maintenance of critical components in the AH64D helicopter tail rotor drive train system. Currently available vibrationmonitoring tools are mostly built around autoand cross-power spectral analysis which have limited value in detecting frequency correlations higher than second order. Studying higher order correlations provides more information about the mechanical system which helps in building more accurate diagnostic models using the same collected vibration data. Based on bispectrum as higher order spectral analysis tools, different signal processing techniques are developed to assess health conditions of different critical rotating-components. Real-world vibration data are collected from a dedicated AH-64D helicopter drive-train research test bed at the CBM center, University of South Carolina, where experimental tests are conducted to simulate accelerated conditioning in the tail rotor drive-train components. First, cross-bispectral analysis is utilized to investigate quadratic nonlinear relationship between two vibration signals simultaneously collected from the forward and afterward hanger bearing positions in the AH-64D helicopter tail rotor drive train. Based on cross-bispectrum, quadratic nonlinear transfer function is presented to model second order nonlinearity in the drive shaft running between the two hanger bearings. Then, quadratic-nonlinearity coupling coefficient between frequency harmonics of the rotating shafts is used as condition metric to study different seeded shaft faults compared to baseline case, namely: 1)shaft misalignment, 2)shaft imbalance, and 3)combination of shaft misalignment and imbalance. Magnitude response of the proposed quadratic-nonlinearity coupling," @default.
• W2134788934 created "2016-06-24" @default.
• W2134788934 creator A5012913320 @default.
• W2134788934 creator A5066787830 @default.
• W2134788934 date "2013-01-01" @default.
• W2134788934 modified "2023-09-26" @default.
• W2134788934 title "Polyspectral signal analysis techniques for condition based maintenance of helicopter drive-train system" @default.
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