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    Stall Warning Strategy Based on Fast Wavelet Analysis in a Multistage Axial Flow Compressor

    Source: Journal of Engineering for Gas Turbines and Power:;2022:;volume( 144 ):;issue: 004::page 44501-1
    Author:
    Liu, Yang
    ,
    Li, Jichao
    ,
    Du, Juan
    ,
    Zhang, Hongwu
    ,
    Nie, Chaoqun
    DOI: 10.1115/1.4053104
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As a reliable stall warning strategy, the fast wavelet method was introduced to successfully predict the aerodynamic instability of a multistage axial flow compressor. One single sensor installed at each stage is proved to be sufficient to predict the stability status in a three-stage axial flow compressor. The whole prediction strategy includes the dynamic pressure signal capture, disturbance extraction using decomposition and reconstruction via fast wavelet transform, and stall warning index calculation based on statistical probability distribution. On this premise, the first occurrence of the stall in this three-stage axial flow compressor is predicted to be within the first stage, which is consistent with the stall route captured by the eight transducers around the casing wall. Thereafter, the stall warning index is used to monitor the stability status during the continuous throttling process. Furthermore, the validation using tip air injection and inlet radial distortion indicated that the stall warning index decreases as the compressor's stability improves. Conversely, the deterioration of stability causes the increase of the stall warning index. Thus, experimental results demonstrate that the stall warning method based on fast wavelet analysis can predict the aerodynamic instability in actual application.
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      Stall Warning Strategy Based on Fast Wavelet Analysis in a Multistage Axial Flow Compressor

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4285009
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorLiu, Yang
    contributor authorLi, Jichao
    contributor authorDu, Juan
    contributor authorZhang, Hongwu
    contributor authorNie, Chaoqun
    date accessioned2022-05-08T09:20:10Z
    date available2022-05-08T09:20:10Z
    date copyright1/4/2022 12:00:00 AM
    date issued2022
    identifier issn0742-4795
    identifier othergtp_144_04_044501.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285009
    description abstractAs a reliable stall warning strategy, the fast wavelet method was introduced to successfully predict the aerodynamic instability of a multistage axial flow compressor. One single sensor installed at each stage is proved to be sufficient to predict the stability status in a three-stage axial flow compressor. The whole prediction strategy includes the dynamic pressure signal capture, disturbance extraction using decomposition and reconstruction via fast wavelet transform, and stall warning index calculation based on statistical probability distribution. On this premise, the first occurrence of the stall in this three-stage axial flow compressor is predicted to be within the first stage, which is consistent with the stall route captured by the eight transducers around the casing wall. Thereafter, the stall warning index is used to monitor the stability status during the continuous throttling process. Furthermore, the validation using tip air injection and inlet radial distortion indicated that the stall warning index decreases as the compressor's stability improves. Conversely, the deterioration of stability causes the increase of the stall warning index. Thus, experimental results demonstrate that the stall warning method based on fast wavelet analysis can predict the aerodynamic instability in actual application.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleStall Warning Strategy Based on Fast Wavelet Analysis in a Multistage Axial Flow Compressor
    typeJournal Paper
    journal volume144
    journal issue4
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4053104
    journal fristpage44501-1
    journal lastpage44501-6
    page6
    treeJournal of Engineering for Gas Turbines and Power:;2022:;volume( 144 ):;issue: 004
    contenttypeFulltext
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