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    Distributed Modal Voltages of Nonlinear Paraboloidal Shells With Distributed Neurons

    Source: Journal of Vibration and Acoustics:;2004:;volume( 126 ):;issue: 001::page 47
    Author:
    H. S. Tzou
    ,
    J. H. Ding
    DOI: 10.1115/1.1640359
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Effective health monitoring and distributed control of advanced structures depends on accurate measurements of dynamic responses of elastic structures. Conventional sensors used for structural measurement are usually add-on “discrete” devices. Lightweight distributed thin-film piezoelectric neurons fully integrated (laminated or embedded) with structural components can serve as in-situ sensors monitoring structure’s dynamic state and health status. This study is to investigate modal voltages and detailed signal contributions of linear or nonlinear paraboloidal shells of revolution laminated with piezoelectric neurons. Signal generation of distributed neuron sensors laminated on paraboloidal shells is defined first, based on the open-voltage assumption and Maxwell’s principle. The neuron signal of a linear paraboloidal shell is composed of a linear membrane component and a linear bending component; the signal of a nonlinear paraboloidal shell is composed of nonlinear and linear membrane components and a linear bending component due to the von Karman geometric nonlinearity. Signal components and distributed modal voltages of linear and nonlinear paraboloidal shells with various curvatures and thickness are investigated.
    keyword(s): Shells , Signals , Sensors AND Membranes ,
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      Distributed Modal Voltages of Nonlinear Paraboloidal Shells With Distributed Neurons

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    http://yetl.yabesh.ir/yetl1/handle/yetl/131087
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    contributor authorH. S. Tzou
    contributor authorJ. H. Ding
    date accessioned2017-05-09T00:14:50Z
    date available2017-05-09T00:14:50Z
    date copyrightJanuary, 2004
    date issued2004
    identifier issn1048-9002
    identifier otherJVACEK-28868#47_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/131087
    description abstractEffective health monitoring and distributed control of advanced structures depends on accurate measurements of dynamic responses of elastic structures. Conventional sensors used for structural measurement are usually add-on “discrete” devices. Lightweight distributed thin-film piezoelectric neurons fully integrated (laminated or embedded) with structural components can serve as in-situ sensors monitoring structure’s dynamic state and health status. This study is to investigate modal voltages and detailed signal contributions of linear or nonlinear paraboloidal shells of revolution laminated with piezoelectric neurons. Signal generation of distributed neuron sensors laminated on paraboloidal shells is defined first, based on the open-voltage assumption and Maxwell’s principle. The neuron signal of a linear paraboloidal shell is composed of a linear membrane component and a linear bending component; the signal of a nonlinear paraboloidal shell is composed of nonlinear and linear membrane components and a linear bending component due to the von Karman geometric nonlinearity. Signal components and distributed modal voltages of linear and nonlinear paraboloidal shells with various curvatures and thickness are investigated.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDistributed Modal Voltages of Nonlinear Paraboloidal Shells With Distributed Neurons
    typeJournal Paper
    journal volume126
    journal issue1
    journal titleJournal of Vibration and Acoustics
    identifier doi10.1115/1.1640359
    journal fristpage47
    journal lastpage53
    identifier eissn1528-8927
    keywordsShells
    keywordsSignals
    keywordsSensors AND Membranes
    treeJournal of Vibration and Acoustics:;2004:;volume( 126 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian