压气机喘振模式识别与在线检测

推进技术 ›› 2011, Vol. 32 ›› Issue (3): 318-322.

压气机喘振模式识别与在线检测

李长征,韩伟,熊兵

西北工业大学动力与能源学院,陕西西安 710072;中国航空工业集团公司燃气涡轮研究院,四川江油 621703;中国航空工业集团公司燃气涡轮研究院,四川江油 621703;中国航空工业集团公司燃气涡轮研究院,四川江油 621703

发布日期:2021-08-15
作者简介:李长征(1978—),男,讲师,博士,研究领域为航空发动机计算机辅助试验技术。E-mail:lichangzheng@nwpu.edu.cn

Pattern recognition and on-line detection for compressor surge

School of Power and Energy, Northwestern Polytechnical Univ., Xian 710072, China; China Gas Turbine Establishment, Aviation Industry Corporation of China,Jiangyou 621703, China;China Gas Turbine Establishment, Aviation Industry Corporation of China,Jiangyou 621703, China;China Gas Turbine Establishment, Aviation Industry Corporation of China,Jiangyou 621703, China

Published:2021-08-15

摘要/Abstract

摘要： 为发展一种运算简单、性能可靠的喘振在线检测系统,分析了压气机出口总压信号的时域和频域特性。当压气机逐渐进入喘振时,时域内表现为压力脉动强度的增大,频域内表现为信号能量在低频成分集中。选用标准差σ_p表征压力脉动强度；平均频率f表征信号频域特性。考察了由σp和f构成的模式平面,提出了一种综合时域和频域特性的喘振检测判据,检测门限可根据置信度要求进行设置,给出了在线检测系统的流程图。采用压气机试验台实测数据验证,该方法可有效地进行喘振在线检测。

关键词: 压气机;喘振;模式识别;在线检测

Abstract: The compressor surge greatly threatens the safe operation of an aircraft engine. To develop a simple and reliable surge on-line detection system, the characteristics of time and frequency-domain of compressor outlet total pressure signals are analyzed. When entering into surge, the pressure pulsation intensity increases in time-domain and the signal energy concentrates in low frequency components in frequency-domain. The standard deviation σp was adopted to describe the pulsation intensity of pressure and the average frequency f for frequency-domain characteristics. A new criterion of surge detection, which integrated time and frequency-domain characteristics, was developed based on the research of the pattern plane of σp and f. The threshold can be set up on the demand of confidence levels. The flow chart of on-line detection system was provided. With compressor test rig measured data, it demonstrates that this method is effective for surge on-line detection.

Key words: Compressor; Surge; Pattern recognition; On-line detection

李长征,韩伟,熊兵. 压气机喘振模式识别与在线检测[J]. 推进技术, 2011, 32(3): 318-322.

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