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    Preemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis

    Source: Journal of Manufacturing Science and Engineering:;1994:;volume( 116 ):;issue: 001::page 130
    Author:
    S. Y. Hong
    ,
    J. Ni
    ,
    S. M. Wu
    DOI: 10.1115/1.2901803
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A preemptive diagnostic system has been developed to detect minor machine failures before machine breakdown for a computer controlled robotic drilling end-effector. By using the Dynamic Data System (DDS) approach, a set of discrete time series data taken from the continuous vibration signal of the machine is analyzed to detect machine failure and to distinguish failures due to the spindle, gears, air motors, and ball bearings of the machine drive system. Experiments validate that the proposed diagnostic method can identify spindle, air motors, gear, and bearing defects in the Robotic Drilling Unit.
    keyword(s): Machinery , Failure , Patient diagnosis , Emission spectroscopy , Motors , Drilling , Spindles (Textile machinery) , Gears , Robotics , Vibration , Computers , Ball bearings , End effectors , Product quality , Bearings , Signals AND Time series ,
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      Preemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/113972
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    contributor authorS. Y. Hong
    contributor authorJ. Ni
    contributor authorS. M. Wu
    date accessioned2017-05-08T23:44:52Z
    date available2017-05-08T23:44:52Z
    date copyrightFebruary, 1994
    date issued1994
    identifier issn1087-1357
    identifier otherJMSEFK-27769#130_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/113972
    description abstractA preemptive diagnostic system has been developed to detect minor machine failures before machine breakdown for a computer controlled robotic drilling end-effector. By using the Dynamic Data System (DDS) approach, a set of discrete time series data taken from the continuous vibration signal of the machine is analyzed to detect machine failure and to distinguish failures due to the spindle, gears, air motors, and ball bearings of the machine drive system. Experiments validate that the proposed diagnostic method can identify spindle, air motors, gear, and bearing defects in the Robotic Drilling Unit.
    publisherThe American Society of Mechanical Engineers (ASME)
    titlePreemptive Diagnosis of Minor Machine Failure by DDS Spectrum Analysis
    typeJournal Paper
    journal volume116
    journal issue1
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2901803
    journal fristpage130
    journal lastpage133
    identifier eissn1528-8935
    keywordsMachinery
    keywordsFailure
    keywordsPatient diagnosis
    keywordsEmission spectroscopy
    keywordsMotors
    keywordsDrilling
    keywordsSpindles (Textile machinery)
    keywordsGears
    keywordsRobotics
    keywordsVibration
    keywordsComputers
    keywordsBall bearings
    keywordsEnd effectors
    keywordsProduct quality
    keywordsBearings
    keywordsSignals AND Time series
    treeJournal of Manufacturing Science and Engineering:;1994:;volume( 116 ):;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
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