引用本文: | 王聪,司文杰,文彬鹤,张明明,王勇,侯安平.轴流压气机旋转失速建模与检测II: 基于北航低速压气机试验台的实验研究[J].控制理论与应用,2014,31(10):1414~1422.[点击复制] |
WANG Cong,SI Wen-jie,WEN Bin-he,ZHANG Ming-ming,WANG Yong,HOU An-ping.Modeling and detection of rotating stall in axial flow compressors, II: Experimental study for low-speed compressor in Beihang University[J].Control Theory and Technology,2014,31(10):1414~1422.[点击复制] |
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轴流压气机旋转失速建模与检测II: 基于北航低速压气机试验台的实验研究 |
Modeling and detection of rotating stall in axial flow compressors, II: Experimental study for low-speed compressor in Beihang University |
摘要点击 3793 全文点击 1165 投稿时间:2014-02-19 修订日期:2014-07-20 |
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DOI编号 10.7641/CTA.2014.40115 |
2014,31(10):1414-1422 |
中文关键词 轴流压气机 旋转失速 喘振 故障检测 确定学习 模式识别 在线实验 |
英文关键词 axial compressor rotating stall surge fault detection deterministic learning theory pattern recognition online experiment |
基金项目 国家杰出青年科学基金资助项目(61225014); 国家自然青年科学基金资助项目(51306003); 国家自然科学基金重点项目(60934001). |
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中文摘要 |
轴流压气机旋转失速和喘振的提前检测对于提高压气机工作效率和稳定性具有重要的意义. 本文以北京航空航天大学航空发动机重点实验室的低速轴流压气机实验台为研究对象,
基于确定学习理论及动态模式识别方法, 开展旋转失速初始扰动近似准确建模和快速检测研究. 首先, 在压气机机匣壁面周向布置多个动态压力传感器, 获取压气机失速前和失速先兆的动态压力信号, 基于确定学习理论对旋转失速初始扰动的内部系统动态进行 建模; 其次, 基于以上建模, 利用微小振动故障检测方法 实现对旋转失速的 离线和在线提前检测. 实验结果表明, 本文所提方法能够在不同 转速情况下, 提前0.3s--1s实现对旋转失速的实时在线检测. |
英文摘要 |
Early detection of rotating stall and surge in axial flow compressors is of great importance for improving
the working efficiency and stability of the compressor. Based on deterministic learning (DL) theory and dynamical pattern
recognition, this paper presents experimental research for approximately accurate modeling and rapid detection of stall
precursors, and then employs a low-speed axial flow compressor test rig of Beihang University for online experimental
verification. Firstly, by installing high response dynamic pressure transducers arranged circumferentially around the casing
of the axial compressor, the dynamic pressure data are collected. Based on deterministic learning theory, the system
dynamics underlying prestall and stall inception patterns are identified. Secondly, based on modeling results, rapid detection
of small oscillation faults is used to perform the detection of stall precursors. Sufficient online experiments are conducted
to investigate the efficiency of the approach. Results show that, in different working speeds, this approach successfully
detects inception signal of aerodynamic instability of the compressor 0:3 s – 1 s in advance to the start of rotating stalls. |
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