Accurate estimation of scramjet inlet parameters (including Mach number and air mass flow rate) is essential for hypersonic flight control. These critical scramjet inlet parameters could be obtained by estimating the air data parameters through the inertial navigation system, but they have large errors. The flush air data sensing system is mainly used for post-flight analysis. This paper proposes an estimation method for scramjet inlet parameters based on deep learning. Accurate estimations of air data are not needed. Instead, the measurements of the transducers on the inlet wall are directly used as the input of the artificial neural network, and then the scramjet inlet parameter (Mach number or air mass flow rate) is output. The results show that the estimation accuracy of the scramjet inlet parameters has been greatly improved. This work provides a new idea for the estimation of the scramjet inlet parameters.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Estimation Method for Scramjet Inlet Mach Number and Mass Flow Rate Based on Deep Learning


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wu, Meiping (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Cheng, Jin (Herausgeber:in) / Kong, Chen (Autor:in) / Liu, Hao (Autor:in) / Xu, Cheng (Autor:in) / Chang, Juntao (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Erscheinungsdatum :

    2022-03-18


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Mach 4 testing of scramjet inlet models

    KANDA, TEKASHI / KOMURO, TOMOYUKI / MASUYA, GORO et al. | AIAA | 1991


    Mach 4 testing of scramjet inlet models

    KANDA, TAKESHI / KOMURO, TOMOYUKI / MASUYA, GORO et al. | AIAA | 1989



    Predictor–Corrector Method for Scramjet Inlet Air Mass Flow Rate Measurement

    Jiao, Xiaoliang / Wang, Zhongqi / Yu, Daren | AIAA | 2017