Nonlinear Flight Mode Identification by Applying Modified Ensemble Empirical Mode Decomposition and Hilbert–Huang Transformation

Abstract

Identification of the “aircraft dynamic modes” is one of the researchers’ favorite subjects in the flight mechanics field to study the behavior of airplane in maneuvers and nonlinear regime. Technically, by measuring the flight test parameters, the flight dynamic modes could be estimated. Although several approaches calculate precisely the linear flight dynamic modes, there is not a known standard procedure to calculate the nonlinear flight dynamic modes. In this paper, identification of the flight dynamic modes in highly nonlinear maneuver conditions and particularly in the coupled dynamic spin maneuvers is investigated. A new approach based on Hilbert–Huang Transform (HTT) for identification of the flight dynamic modes is presented in this paper. To overcome the mode mixing problem during decomposition which leads to imprecise results in the estimation of the flight dynamic modes, a Modified Ensemble Empirical Mode Decomposition (MEEMD) algorithm for processing of the complex signals that originate from FDR is presented in this research. This new algorithm is able to make a precise reconstruction of the original signal and it performs the task of signal decomposition with fewer iterations and so with less complexity order rather than the competitor approaches. An innovative algorithm for calculating flight dynamic modes natural frequencies and the damping ratios which uses the IMFs produced by MEEMD is presented. The obtained approach was applied to flight data, which belong to spin maneuvers. The results show the correct performance of the presented technique in the nonlinear flight regime.