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作 者:吴蔚 赵博[1] 薛翔 竺晓程[1] 王彤[1] 杜朝辉[1] WU Wei;ZHAO Bo;XUE Xiang;ZHU Xiaocheng;WANG Tong;DU Zhaohui(School of Mechanical Engineering,Shanghai Jiaotong University,Shanghai 200240,China)
机构地区:[1]上海交通大学机械与动力工程学院,上海200240
出 处:《航空动力学报》2020年第8期1768-1776,共9页Journal of Aerospace Power
摘 要:离心压气机失稳过程是一个非常复杂的动态过程,提高离心压气机运行的可靠性需要准确获取失稳过程的时频特征。针对带无叶扩压器的高速离心压气机失稳过程中叶轮出口的动态压力数据,采用时空本征模态分解(STIMD)算法和经验模态分解(EMD)算法进行分解,得到了多个本征模态函数(IMF),并结合Hilbert变换对不稳定流动的动态特征进行分析。结果表明,STIMD算法得到了深喘和浅喘的时频信息,观察到了频率在150 Hz附近持续波动的失速现象,并捕捉到了浅喘先兆的频率曲线由抖动向恒定的过渡过程。STIMD算法改善了EMD的模态混叠问题,为压气机失稳分析提供了一种工具。Improving the reliability of centrifugal compressor operation requires accurate acquisition of time-frequency characteristics. Based on the dynamic pressure data acquired at the impeller outlet when the high-speed centrifugal compressor with vaneless diffuser approached the unsteady condition, spatiotemporal intrinsic mode decomposition(STIMD) and empirical mode decomposition(EMD) were used to obtain the intrinsic mode functions(IMF). Combining Hilbert transform, the dynamic characteristics of unsteady flow were analyzed. By STIMD algorithm, the time-frequency information of deep surge and mild surge was obtained. The phenomenon of stall with continuous fluctuation frequency around 150 Hz was observed, whilst the transition of frequency curve of mild surge precursor from oscillating to constant state was found. STIMD algorithm has improved the modal aliasing problem of EMD, thus providing a tool for compressor stability analysis.
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