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    A Modal Parameter Identification Method Based on Improved Covariance-Driven Stochastic Subspace Identification

    Source: Journal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 006::page 061005-1
    Author:
    Wang, Chen
    ,
    Hu, Minghui
    ,
    Jiang, Zhinong
    ,
    Zuo, Yanfei
    ,
    Zhu, Zhenqiao
    DOI: 10.1115/1.4047111
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: For the quantitative dynamic analysis of aero gas turbines, accurate modal parameters must be identified. However, the complicated structure of thin-walled casings may cause false mode identification and mode absences if conventional methods are used, which makes it more difficult to identify the modal parameters. A modal parameter identification method based on improved covariance-driven stochastic subspace identification (covariance-driven SSI) is proposed. The ability to reduce the number of mode absences and the solving stability are improved by a covariance matrix dimension control method. Meanwhile, the number of false mode identification is reduced via a false mode elimination method. In addition, the real mode complementation and the excitation frequency mode screening can be realized by a multispeed excitation method. The numerical results of a typical rotor model and measured data of an aero gas turbine validated the proposed method.
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      A Modal Parameter Identification Method Based on Improved Covariance-Driven Stochastic Subspace Identification

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4274658
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorWang, Chen
    contributor authorHu, Minghui
    contributor authorJiang, Zhinong
    contributor authorZuo, Yanfei
    contributor authorZhu, Zhenqiao
    date accessioned2022-02-04T21:59:20Z
    date available2022-02-04T21:59:20Z
    date copyright5/28/2020 12:00:00 AM
    date issued2020
    identifier issn0742-4795
    identifier othergtp_142_06_061005.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274658
    description abstractFor the quantitative dynamic analysis of aero gas turbines, accurate modal parameters must be identified. However, the complicated structure of thin-walled casings may cause false mode identification and mode absences if conventional methods are used, which makes it more difficult to identify the modal parameters. A modal parameter identification method based on improved covariance-driven stochastic subspace identification (covariance-driven SSI) is proposed. The ability to reduce the number of mode absences and the solving stability are improved by a covariance matrix dimension control method. Meanwhile, the number of false mode identification is reduced via a false mode elimination method. In addition, the real mode complementation and the excitation frequency mode screening can be realized by a multispeed excitation method. The numerical results of a typical rotor model and measured data of an aero gas turbine validated the proposed method.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Modal Parameter Identification Method Based on Improved Covariance-Driven Stochastic Subspace Identification
    typeJournal Paper
    journal volume142
    journal issue6
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4047111
    journal fristpage061005-1
    journal lastpage061005-15
    page15
    treeJournal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 006
    contenttypeFulltext
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