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    Application of Possibilistic C Means for Fault Detection in Nuclear Power Plant Data

    Source: Journal of Engineering for Gas Turbines and Power:;2015:;volume( 137 ):;issue: 006::page 62901
    Author:
    Perasso, Annalisa
    ,
    Campi, Cristina
    ,
    Toraci, Cristian
    ,
    Benvenuto, Francesco
    ,
    Piana, Michele
    ,
    Massone, Anna Maria
    DOI: 10.1115/1.4028809
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper describes a classification method for automatic fault detection in nuclear power plant (NPP) data. The method takes as input time series associated to specific parameters and realizes signal classification by using a clustering algorithm based on possibilistic Cmeans (PCM). This approach is applied to time series recorded in a CANDUآ® power plant and is validated by comparison with results provided by a classification method based on principal component analysis (PCA).
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      Application of Possibilistic C Means for Fault Detection in Nuclear Power Plant Data

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/157975
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorPerasso, Annalisa
    contributor authorCampi, Cristina
    contributor authorToraci, Cristian
    contributor authorBenvenuto, Francesco
    contributor authorPiana, Michele
    contributor authorMassone, Anna Maria
    date accessioned2017-05-09T01:17:56Z
    date available2017-05-09T01:17:56Z
    date issued2015
    identifier issn1528-8919
    identifier othergtp_137_06_062901.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/157975
    description abstractThis paper describes a classification method for automatic fault detection in nuclear power plant (NPP) data. The method takes as input time series associated to specific parameters and realizes signal classification by using a clustering algorithm based on possibilistic Cmeans (PCM). This approach is applied to time series recorded in a CANDUآ® power plant and is validated by comparison with results provided by a classification method based on principal component analysis (PCA).
    publisherThe American Society of Mechanical Engineers (ASME)
    titleApplication of Possibilistic C Means for Fault Detection in Nuclear Power Plant Data
    typeJournal Paper
    journal volume137
    journal issue6
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4028809
    journal fristpage62901
    journal lastpage62901
    identifier eissn0742-4795
    treeJournal of Engineering for Gas Turbines and Power:;2015:;volume( 137 ):;issue: 006
    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
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