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

    Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

    Source: Journal of Manufacturing Science and Engineering:;2011:;volume( 133 ):;issue: 004::page 41013
    Author:
    ZhenZhou Wang
    ,
    YuMing Zhang
    ,
    XiaoJi Ma
    DOI: 10.1115/1.4004498
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The reflection of projected laser lines may be used to determine the three-dimensional geometry of the reflecting weld pool surface. However, for gas metal arc welding (GMAW), the transfer of the droplets into the weld pool makes the weld pool surface highly dynamic and fluctuating. The position and geometry of the local reflecting surface, which intercepts and reflects the projected laser changes rapidly. As a result, the reflection rays change their trajectories rapidly. The contrast of laser reflection with the background is much reduced and methods are needed to extract laser reflection from low contrast images. To this end, an image quality measurement method is proposed based on the number of the edge points to determine if an image may be further processed. The image to be processed is then modeled as a superposition of the laser reflection and arc radiation background. Methods have been proposed to remove the uneven distribution of the arc radiation background from the image, such that a global threshold is possible to segment the laser reflection lines. The set of the laser line points are then clustered to form separate laser lines. These laser lines are then modeled and the parameters in the models are used to validate each modeled line. Processing results verified the effectiveness of the proposed methods/algorithms in providing laser lines from low contrast images that are formed by laser reflection from a high dynamic gas metal arc weld pool surface.
    keyword(s): Lasers , Reflection , Metals AND Structural frames ,
    • Download: (4.124Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Machine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/146866
    Collections
    • Journal of Manufacturing Science and Engineering

    Show full item record

    contributor authorZhenZhou Wang
    contributor authorYuMing Zhang
    contributor authorXiaoJi Ma
    date accessioned2017-05-09T00:45:26Z
    date available2017-05-09T00:45:26Z
    date copyrightAugust, 2011
    date issued2011
    identifier issn1087-1357
    identifier otherJMSEFK-28479#041013_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/146866
    description abstractThe reflection of projected laser lines may be used to determine the three-dimensional geometry of the reflecting weld pool surface. However, for gas metal arc welding (GMAW), the transfer of the droplets into the weld pool makes the weld pool surface highly dynamic and fluctuating. The position and geometry of the local reflecting surface, which intercepts and reflects the projected laser changes rapidly. As a result, the reflection rays change their trajectories rapidly. The contrast of laser reflection with the background is much reduced and methods are needed to extract laser reflection from low contrast images. To this end, an image quality measurement method is proposed based on the number of the edge points to determine if an image may be further processed. The image to be processed is then modeled as a superposition of the laser reflection and arc radiation background. Methods have been proposed to remove the uneven distribution of the arc radiation background from the image, such that a global threshold is possible to segment the laser reflection lines. The set of the laser line points are then clustered to form separate laser lines. These laser lines are then modeled and the parameters in the models are used to validate each modeled line. Processing results verified the effectiveness of the proposed methods/algorithms in providing laser lines from low contrast images that are formed by laser reflection from a high dynamic gas metal arc weld pool surface.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMachine Recognition of Laser Reflection From Gas Metal Arc Weld Pool Surfaces
    typeJournal Paper
    journal volume133
    journal issue4
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4004498
    journal fristpage41013
    identifier eissn1528-8935
    keywordsLasers
    keywordsReflection
    keywordsMetals AND Structural frames
    treeJournal of Manufacturing Science and Engineering:;2011:;volume( 133 ):;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