The reliability and safety of liquid rocket engine (LRE) are important assessment metrics; the rocket will inevitably deviate from the rated operating conditions in the actual working situation, so in the event of a nonfatal fault, we must make a timely judgment on the trend of the failure's development and take appropriate action. For this reason, based on the typical fault models established, we develop a health management system that comprises forecasting, detection, and mitigation, which can be encapsulated as a standalone module for future integration into controllers. The main innovations are outlined as follows. First, we assess the engine health level and forecast typical fault tendencies in real time using LSTM and fuzzy membership. Second, when a nonhealthy state arises during real-time evaluation, thrust recovery control with mixture ratio limitations is designed to prevent the engine from further destabilizing and to mitigate engine performance degradation. Experimental results show that, for typical fault mode, the system's real-time anticipated MAE of less than 4.3% enables it to give a thorough and efficient evaluation of health levels. The mitigation phase can stabilize engine performance within the mixture ratio limiting threshold and minimize both transient and steady-state thrust losses from failures.


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    Title :

    LSTM–Fuzzy Logic for Fault Forecasting and Mitigation in Propulsion System


    Contributors:
    Yu, Bingqiang (author) / Peng, Yi (author) / Huang, Jinquan (author) / Lu, Feng (author)


    Publication date :

    2024-12-01


    Size :

    5765861 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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