Advances in early warning and active control of compressor instabilities for aerospace applications

This paper provides a comprehensive overview of the methods developed over the past 40 years for predicting stall and surge in gas turbine and aero-engine compressors. The review encompasses theoretical models, real-time signal analysis techniques for early stall and surge warning, and their integration into active control systems. For circumferentially propagating rotating stall, the Moore-Greitzer model and harmonic analysis of dynamic signals laid the foundation for predicting stall and enabling active control strategies. The discovery of two types of stall precursors and the recognition that stall typically precedes surge led to the development of early warning methods based on stall precursor detection, such as spatial Fourier transform and traveling wave energy analysis. A deeper understanding of stall mechanisms has revealed the unsteady behavior of tip leakage vortices as an earlier precursor disturbance. Concurrently, numerous stall warning techniques—including correlation analysis, wavelet analysis, modal decomposition, and deep learning—have been developed to improve the timeliness and reliability of warnings. The robustness of these methods under various operational factors, such as inlet distortion, tip clearance size, and rotor eccentricity, has been thoroughly analyzed, supporting their integration with active control strategies. In contrast, surge early warning remains more challenging due to the limited understanding of the surge-inducing mechanisms in axial fluctuations; current detection primarily relies on frequency monitoring of pressure, vibration, and acoustic signals. As modern engines operate under increasingly complex inlet conditions and higher load demands, the routes to instability and the nature of precursor disturbances have diversified. This presents significant challenges in developing early warning methods that comprehensively address the various instability pathways. The paper highlights the most influential contributions in this field and discusses prospects for future research directions.