Abstract
This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Examples are given using aeroelastic flight test data from the F/A-18 Active Aeroelastic Wing aircraft and Aerostructures Test Wing.
This work was prepared as part of the first author’s official duties as an employee of the U. S. Government and in accordance with 17 U.S.C. 105, is not available for copyright protection in the United States. NASA is the owner of any foreign copyright that can be asserted for the work. Copyright@2005 by NASA.
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Brenner, M.J., Kukreja, S.L., Prazenica, R.J. (2006). Signal-Adaptive Aeroelastic Flight Data Analysis with HHT. In: Qian, T., Vai, M.I., Xu, Y. (eds) Wavelet Analysis and Applications. Applied and Numerical Harmonic Analysis. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7778-6_24
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