IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/7362705.html
   My bibliography  Save this article

Statistical Analysis of Industrial Grinding Brush Force Characteristics Based on Finite Element Approach

Author

Listed:
  • Chong Wang
  • Hongqiang Guo
  • Ying Zhao
  • Qun Sun
  • Ling Zhao

Abstract

This paper presents an in-depth study of the helical grinding brush force characteristics aiming at developing a mobile robot system to perform rust removal and other surface processing tasks. Based on an off-line Finite Element model that can calculate brush filament deformation and force behaviors, a mathematical regression model has been developed to summarize brush force changes subjected to varying conditions into a series of mathematical equations. The predictions of the mathematical model are well converged with the Finite Element modeled results and the R-squared value is up to 0.95. The paper presents the model form and calibrated coefficients, which may provide an advantageous tool to predict the grinding brush force changes in real time and contribute well to an automatic grinding control application.

Suggested Citation

  • Chong Wang & Hongqiang Guo & Ying Zhao & Qun Sun & Ling Zhao, 2018. "Statistical Analysis of Industrial Grinding Brush Force Characteristics Based on Finite Element Approach," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, November.
  • Handle: RePEc:hin:jnlmpe:7362705
    DOI: 10.1155/2018/7362705
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2018/7362705.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2018/7362705.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2018/7362705?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:7362705. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.