Radio Frequency (RF) mass gauging is a technique for measuring an amount of fuel inside a cryogenic tank of a future spacecraft under a low gravity environment. In this paper, a method of predicting fuel amount from a given RF resonance tank frequency spectrum through a neurofuzzy inference engine is described. Raw RF resonance spectrum data is first smoothed out by a moving average filter. Then a set of RF resonance modes obtained from this processed data is used as the input for predicting the output value which is the fuel amount. The subtractive clustering method is used for creating the initial membership functions and rules of the neuro-fuzzy engine. The parameters of the engine are optimized by ANFIS (Adaptive-Network-Based Fuzzy Inference System). Computer simulations for a wide range of RF resonance frequencies and various fuel levels indicate that the proposed neuro-fuzzy method works accurately and robustly for predicting fuel amount within 10 % error based on the full tank capacity compared to pure mathematical means of interpolation such as the polynomial-fit with maximum error of 207 % and the cubic spline with maximum error of 22 %.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Radio frequency fuel gauging with neuro-fuzzy inference engine for future spacecrafts


    Beteiligte:
    Kumagai, Akihiko (Autor:in) / Liu, Tien-I. (Autor:in) / Sul, Dongun (Autor:in)


    Erscheinungsdatum :

    2010


    Format / Umfang :

    5 Seiten, 5 Bilder, 1 Tabelle, 10 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Novel Material for Future Spacecrafts

    Sen, Subbayu / Cothran, Ernestine | NTRS | 2005



    Radio Frequency Mass Gauging of Propellants

    Zimmerli, Gregory / Vaden, Karl / Herlacher, Michael et al. | AIAA | 2007