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失速和喘振是航空发动机试验中常遇的两类气动失稳现象,为保障发动机零部件试验安全运转,必须对失速喘振信号进行在线检测控制。根据零部件试车台架的需求,设计了失速喘振辨识算法并对影响辨识算法的关键因素进行了分析,通过小型嵌入式系统为硬件平台实现了失稳辨识系统在线检测功能。该失稳辨识系统具有体积小、实时性强、抗干扰能力强的特点。在多个型号零部件试验件的应用表明,该系统能有效识别发动机深度失速和喘振状态,满足航空发动机风扇/压气机对失速喘振在线检测控制的要求,具有较高的工程应用价值。
Stall and surge are two types of aerodynamic instability encountered in the test of aeroengine. To ensure the safe operation of engine parts test, online detection and control of stalled surge signal must be carried out. According to the demand of parts test bench, a stalled surge identification algorithm is designed and the key factors affecting the identification algorithm are analyzed. The on-line detection function of the system for instability identification is realized by the small embedded system as the hardware platform. The instability identification system has the characteristics of small size, strong real-time performance and strong anti-interference ability. The application of the test parts on several models indicates that the system can effectively recognize the deep stall and surge condition of the engine and meet the requirements of aero-engine fan / compressor for on-line detection and control of stalling surge, which has high engineering application value.