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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 预览 被引量:2

Modeling and detection of rotating stall in axial flow compressors, Ⅱ: Experimental study for a low-speed compressor in Beihang University
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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0.3 s~1 s实现对旋转失速的实时在线检测. Early detection of rotating stall and surge in axial flow compressors is of great importance for improvingthe working efficiency and stability of the compressor. Based on deterministic learning (DL) theory and dynamical patternrecognition, this paper presents experimental research for approximately accurate modeling and rapid detection of stallprecursors, and then employs a low-speed axial flow compressor test rig of Beihang University for online experimentalverification. Firstly, by installing high response dynamic pressure transducers arranged circumferentially around the casingof the axial compressor, the dynamic pressure data are collected. Based on deterministic learning theory, the systemdynamics underlying prestall and stall inception pattems are identified. Secondly, based on modeling results, rapid detectionof small oscillation faults is used to perform the detection of stall precursors. Sufficient online experiments are conductedto investigate the efficiency of the approach. Results show that, in different working speeds, this approach successfullydetects inception signal of aerodynamic instability of the compressor 0.3 s-l s in advance to the start of rotating stalls.
作者 王聪 司文杰 文彬鹤 张明明 王勇 侯安平 WANG Congi, SI Wen-jie, WEN Bin-he, ZHANG Ming-ming, WANG Yong, HOU An-ping(1. College of Automation Science and Technology, South China University of Technology, Guangzhou Guangdong 510640, China; 2. Institute of AVIC Aviation Motor Control System, Wnxi Jiangsu 214063, China; 3. Department of Mechanics and Engineering Science, Peking University, Beijing 100871, China; 4. School of Energy and Power Engineering, BeiHang University, Beijing 100191, China)
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2014年第10期1414-1422,共9页 Control Theory & Applications
基金 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).
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 axial compressor rotating stall surge fault detection deterministic learning theory pattern recognition online experiment
作者简介 王聪(1968-),男,教授,博士生导师,主要研究方向为确定学习等,E—mail:wangcong@scut.edu.cn 司文杰(1985-),男,博士研究生,主要研究方向为确定学习、轴流压气机不稳定流动等,E—mail:siwenjie@gmail.com 文彬鹤(1987-),男,工程师,主要研究方向为航空发动机动力控制系统研究,E—mail:bhwen5516521@126.com 张明明(1982-),男,在做博士后研究工作,主要研究方向为流体力学及流固祸合研究,E—mail:simonzhang@sjp.buaa.edu.cn 王勇(1968-),男,教授,博士生导师,主要研究方向为非线性动力学建模与分析,E—mail:yongwang@mech.pku.edu.cn 侯安平(1975-),男,副教授,主要研究方向为叶轮机械气动弹性研究、风扇、压气机气动设计、气浮高速电机研究、微型燃机、风光互补等分布式能源系统研究,E-mail:houap@buaa.edu.cn.
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