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contributor authorTian, Jie
contributor authorSun, Zonghan
contributor authorZhang, Xiaopu
contributor authorOuyang, Hua
date accessioned2022-02-05T22:08:32Z
date available2022-02-05T22:08:32Z
date copyright4/8/2021 12:00:00 AM
date issued2021
identifier issn0889-504X
identifier otherturbo_143_6_061004.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4276997
description abstractA signal reconstruction algorithm based on the compressed sensing (CS) theory with dual-uniform sampling point (DUSP) distribution is developed and applied to identify the azimuthal mode of axial compressor. A regular failure signal pattern is found, and the corresponding explanation is presented with validation. Azimuthal mode analysis is applied to both numerical and experimental pressure fluctuation signals of rotating instability (RI) in the axial compressor tip region. For numerical calculations, the signal in the azimuthal mode domain is reconstructed by the CS with random measurement points and DUSP, respectively. The success rates and reconstruction errors are discussed in detail. It is shown that the azimuthal mode reconstruction method based on CS combined with DUSP is capable of identifying the complex flow modes in the tip region of the axial compressor. For the experimental results, high azimuthal mode orders are reconstructed based on dynamic pressure signals measured by DUSP. Azimuthal mode analysis efficiency is thereby significantly improved. The time-resolved characteristics of the RI are discussed. Moreover, a robustness analysis is conducted, demonstrating the ability of the CS-based method with DUSP to address sensor failure problems.
publisherThe American Society of Mechanical Engineers (ASME)
titleAzimuthal Mode Characteristics of Rotating Instability in Axial Compressor Using Compressed Sensing Method
typeJournal Paper
journal volume143
journal issue6
journal titleJournal of Turbomachinery
identifier doi10.1115/1.4050109
journal fristpage061004-1
journal lastpage061004-13
page13
treeJournal of Turbomachinery:;2021:;volume( 143 ):;issue: 006
contenttypeFulltext


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