YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASME
    • Journal of Manufacturing Science and Engineering
    • View Item
    •   YE&T Library
    • ASME
    • Journal of Manufacturing Science and Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Bearing Localized Defect Detection by Bicoherence Analysis of Vibrations

    Source: Journal of Manufacturing Science and Engineering:;1995:;volume( 117 ):;issue: 004::page 625
    Author:
    C. James Li
    ,
    J. Ma
    ,
    B. Hwang
    DOI: 10.1115/1.2803542
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: For automatic detection and diagnosis of localized defects in rolling element bearings, bicoherence spectra are used to derive features that signify the condition of a bearing. These features quantitatively describe the degree of phase correlation among any three harmonics of bearing characteristic defect frequencies. In this paper, theory of bicoherence is explored to establish its utilization in the detection of bearing localized defects. Experimental results show that the proposed method is effective in bearing defect detection and sensitive to incipient defects.
    keyword(s): Bearings , Vibration , Flaw detection , Product quality , Spectra (Spectroscopy) , Frequency , Patient diagnosis AND Rolling bearings ,
    • Download: (583.8Kb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Bearing Localized Defect Detection by Bicoherence Analysis of Vibrations

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/115572
    Collections
    • Journal of Manufacturing Science and Engineering

    Show full item record

    contributor authorC. James Li
    contributor authorJ. Ma
    contributor authorB. Hwang
    date accessioned2017-05-08T23:47:39Z
    date available2017-05-08T23:47:39Z
    date copyrightNovember, 1995
    date issued1995
    identifier issn1087-1357
    identifier otherJMSEFK-27783#625_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/115572
    description abstractFor automatic detection and diagnosis of localized defects in rolling element bearings, bicoherence spectra are used to derive features that signify the condition of a bearing. These features quantitatively describe the degree of phase correlation among any three harmonics of bearing characteristic defect frequencies. In this paper, theory of bicoherence is explored to establish its utilization in the detection of bearing localized defects. Experimental results show that the proposed method is effective in bearing defect detection and sensitive to incipient defects.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleBearing Localized Defect Detection by Bicoherence Analysis of Vibrations
    typeJournal Paper
    journal volume117
    journal issue4
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2803542
    journal fristpage625
    journal lastpage629
    identifier eissn1528-8935
    keywordsBearings
    keywordsVibration
    keywordsFlaw detection
    keywordsProduct quality
    keywordsSpectra (Spectroscopy)
    keywordsFrequency
    keywordsPatient diagnosis AND Rolling bearings
    treeJournal of Manufacturing Science and Engineering:;1995:;volume( 117 ):;issue: 004
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian