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    Image Processing Approach for Estimating the Degree of Surface Eroded by Slurry at Different Impact Velocities

    Source: Journal of Tribology:;2022:;volume( 144 ):;issue: 010::page 101707-1
    Author:
    Al-Bukhaiti
    ,
    M. A.;Abouel-Kasem
    ,
    A.;Abdelrhman
    ,
    Y.;Heshmat
    ,
    M.;Ahmed
    ,
    S. M.
    DOI: 10.1115/1.4054540
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this research, we utilize image processing to analyze surfaces acquired from slurry-erosion tests carried out on AISI 5117 steel at various velocities and impact angles of 30 deg and 90 deg. The fractal and wavelet decomposition transform are two analysis tools that are particularly promising in this regard. These can be used to extract metrics that characterize slurry erosion in the same way that erosion rate is characterized. The study found that for a higher velocity of 15 m/s and a 30-deg impact angle, the fractal value was larger, irrespective of magnification. The fractal value is also in a positive linear regression with magnification. The extracted features of wavelet analysis were not distinctive for slurry-erosion behavior. The role of impact velocity in creating erosion damage is related to the variety of erosion mechanisms that are dependent on the particles’ kinetic energy. Microscopic examinations of damaged surfaces revealed that extruded lips indentation was the major mechanism of erosion, which occurred at 5 m/s speed and 30-deg impingement angle. Ploughing was proved that it was the predominant erosion mechanism at high velocity. Hence, the impact velocity determines the length of the wear tracks created by the ploughing mechanism.
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      Image Processing Approach for Estimating the Degree of Surface Eroded by Slurry at Different Impact Velocities

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4287457
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    contributor authorAl-Bukhaiti
    contributor authorM. A.;Abouel-Kasem
    contributor authorA.;Abdelrhman
    contributor authorY.;Heshmat
    contributor authorM.;Ahmed
    contributor authorS. M.
    date accessioned2022-08-18T13:06:53Z
    date available2022-08-18T13:06:53Z
    date copyright6/6/2022 12:00:00 AM
    date issued2022
    identifier issn0742-4787
    identifier othertrib_144_10_101707.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4287457
    description abstractIn this research, we utilize image processing to analyze surfaces acquired from slurry-erosion tests carried out on AISI 5117 steel at various velocities and impact angles of 30 deg and 90 deg. The fractal and wavelet decomposition transform are two analysis tools that are particularly promising in this regard. These can be used to extract metrics that characterize slurry erosion in the same way that erosion rate is characterized. The study found that for a higher velocity of 15 m/s and a 30-deg impact angle, the fractal value was larger, irrespective of magnification. The fractal value is also in a positive linear regression with magnification. The extracted features of wavelet analysis were not distinctive for slurry-erosion behavior. The role of impact velocity in creating erosion damage is related to the variety of erosion mechanisms that are dependent on the particles’ kinetic energy. Microscopic examinations of damaged surfaces revealed that extruded lips indentation was the major mechanism of erosion, which occurred at 5 m/s speed and 30-deg impingement angle. Ploughing was proved that it was the predominant erosion mechanism at high velocity. Hence, the impact velocity determines the length of the wear tracks created by the ploughing mechanism.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleImage Processing Approach for Estimating the Degree of Surface Eroded by Slurry at Different Impact Velocities
    typeJournal Paper
    journal volume144
    journal issue10
    journal titleJournal of Tribology
    identifier doi10.1115/1.4054540
    journal fristpage101707-1
    journal lastpage101707-11
    page11
    treeJournal of Tribology:;2022:;volume( 144 ):;issue: 010
    contenttypeFulltext
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