Demonstration of flutter stability over the design envelope and identification of a safe flight envelope is a prerequisite for operational clearance of any new aircraft design. Generally, in all the flight flutter-testing programs, frequency and modal damping ratios are estimated at each flight-test point, and the trend of variation of frequency and damping is established. Frequencies and damping value estimations have to be as accurate as possible to define the aircraft flutter margin at each test point. In this study, stability parameters are estimated directly from the flight flutter-test time response data using an autoregressive (AR) model, which in turn is used to estimate the frequency and damping. In this paper, the focus is on determining an optimized AR model to ensure the accuracy of the model so that the estimation of stability parameters as well as frequency and damping parameters will be more accurate. Toward that, model order estimation techniques such as Akaike’s information criteria and final prediction error were used to predict the model order efficiently. Studies have been presented for different data lengths to prove the capability of this method to produce an accurate spectral estimate even with short data records. This will enable a quick evaluation of spectral estimate and flutter stability parameter using the same AR model, facilitating a quick flight envelope expansion.


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    Titel :

    Frequency, Damping, and Flutter Prediction from Aircraft Flight Data Using Autoregressive Model


    Beteiligte:

    Erschienen in:

    Journal of Aircraft ; 55 , 6 ; 2179-2190


    Erscheinungsdatum :

    2018-06-28


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch