多级高速压气机喘振失稳的确定学习建模与预警OA

Aerodynamic instability warning and safe operation monitoring of compressors are important and challeng-ing problems in high-performance aero-engine research.For issues such as weak characteristics,complex mechanisms,and the difficult-to-predict nature of multistage high-speed compressor surges,this paper presents a unified learning and warning method based on single-sensor data.Firstly,a sampled-data observer-based deterministic learning algorithm is used to identify the compressor dynamics,forming a pattern library that characterizes the dynamic information of surge evolution.Subsequently,this library is used to design dynamical estimators,which utilize real-time input from single-sensor data to achieve surge warning.Finally,offline and online warning experiments at different speeds are carried out on a five-stage high-speed compressor test rig.Preliminary experimental results show that based on the single-sensor data,the proposed method can achieve a technological breakthrough from millisecond-level detection after the surge occurs to second-level warning before the surge occurs.In summary,the proposed learning method can utilize compressor data of the multistage high-speed compressor to obtain the essential and comprehensive dynamic characteristics of the compressor surge,which has favorable interpretability.The warning method developed on this basis only uses single-sensor data to achieve online early detection of sudden surges.It is expected to provide a real-time monitoring method for the safe and stable operation of high-performance aero-engines,which has a certain application value.