عنوان مقاله [English]
نویسندگان [English]چکیده [English]
This paper investigates the use of the Hilbert-Huang transform to identify airplane flight modes and their characteristics. This study shows that the Hilbert-Huang transform, as a new powerful tool in the signal analysis field, has good potential capabilities to improve the airplane flying quality analysis and to overcome some drawbacks of the classical method in flight dynamics. To utilize these capabilities, some improvements such as online implementation of the empirical mode decomposition algorithm are presented. The new online-local algorithm can estimate the signal trend by the Savitzky-Golay filter and eliminate it from the signal in the EMD algorithm. A performance comparison of the new and traditional algorithms is also presented. Then, a new method is proposed based on the online-local EMD algorithm and Hilbert transform to determine the airplane modes and their characteristics. The new method is able to extract some airplane modes, including natural and non-standard modes, directly from measurements of flight parameters during the flight tests in the time domain. The results indicate the ability of the proposed method to extract the airplane modes with small damping ratios. Also, the consistency of the results obtained from the simulated output signals of the linear perturbed model verifies the new method performance. Finally, an example of applying the proposed method to the real flight test data is presented. It reveals the existence of some non-standard modes with small damping ratios at nonlinear flight regions and confirms the new method performance.
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