【摘要】 基于声学原理和声学信号进行压气机气动失稳故障诊断具有重要的研究价值，对基于声学信号的压气机失稳监测和预警技术开展了回顾与总结。首先介绍了常见的气动失稳故障，包括失速、喘振和旋转不稳定性的发声机理与信号特征，然后介绍和总结了国内外关于基于声学信号开展压气机气动失稳故障监测、诊断和预警方法的最新研究进展。结果表明：进入气动失稳状态的压气机，在声音特征上通常表现为低频能量增加、周期性破坏和特定模态分量幅值变化。通过对声信号的深入研究分析，建立机理与信号特征的联系，有望设计出更加准确、灵敏的压气机失稳故障检测方法。未来一段时间内，研究如何在包含噪声与混响的信号中提取出用于失稳诊断的信号特征以及发展相应数据集以支撑数据驱动的失稳检测方法将是声学失稳检测技术面临的重大问题。更多还原

【Abstract】 The diagnosis of compressor aerodynamic instability faults based on acoustic principles and acoustic signals has important research value.A review and summary of compressor instability monitoring and warning technologies based on acoustic signals are conducted.Firstly, common aerodynamic instability faults are introduced, including the sound generation mechanism and signal characteristics of stall, surge, and rotational instability.Then, the latest research progress on monitoring, diagnosing, and warning methods for compressor aerodynamic instability faults based on acoustic signals at home and abroad is introduced and summarized.The results indicate that compressors entering an aerodynamic instability state typically exhibit low-frequency energy increase, periodic failure, and specific modal component amplitude changes in sound characteristics.Through in-depth research and analysis of acoustic signals, establishing the connection between mechanism and signal characteristics, it is expected to design more accurate and sensitive methods for detecting compressor instability faults.In the future, researching how to extract signal features for instability diagnosis from signals containing noise and reverberation, and developing corresponding datasets to support data-driven instability detection methods will be a major challenge for acoustic instability detection technology.更多还原