Abstract Ring die granulator is a high energy consumption and complex system. Conventional method for improvement the quality of pellets is detected by human sense offline. Aimed to lowness of efficiency and bigness of error, a novel strategy is present for the intelligence quality classification. By means of machine vision, after extract the feature, the pellet edge images are captured based canny algorithm, and the quality classification can be accuracy got by FSVM. Real pellet images are conducted to prove the effect. Compared with other methods by the simulation, the present approach has apparent advantages. The result of the present work implied that, the present method can be applied to auto quality detection and the classification results can be used as the feedback signals in controller to update the parameters to control the ring die granulator well.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Novel Quality Classification for Ring Die Pellet


    Beteiligte:
    Zhang, Kun (Autor:in) / Fei, Minrui (Autor:in) / Wu, Jianguo (Autor:in) / Zhang, Peijian (Autor:in)


    Erscheinungsdatum :

    2014-01-01


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    An Novel Quality Classification for Ring Die Pellet

    Zhang, K. / Fei, M. / Wu, J. et al. | British Library Conference Proceedings | 2014


    PELLET TRANSFER SYSTEM

    CHENARD ROBERT JOSEPH | Europäisches Patentamt | 2021

    Freier Zugriff

    Pellet transfer system

    CHENARD ROBERT JOSEPH | Europäisches Patentamt | 2022

    Freier Zugriff

    PELLET TRANSFER SYSTEM

    CHENARD ROBERT JOSEPH | Europäisches Patentamt | 2022

    Freier Zugriff

    Wind–pellet shear sailing

    Greason, Jeffrey K. / Yakymenko, Dmytro / Larrouturou, Mathias N. et al. | Elsevier | 2022