IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3847049.html
   My bibliography  Save this article

Thermal Error Modeling of the CNC Machine Tool Based on Data Fusion Method of Kalman Filter

Author

Listed:
  • Haitong Wang
  • Tiemin Li
  • Yonglin Cai
  • Heng Wang

Abstract

This paper presents a modeling methodology for the thermal error of machine tool. The temperatures predicted by modified lumped-mass method and the temperatures measured by sensors are fused by the data fusion method of Kalman filter. The fused temperatures, instead of the measured temperatures used in traditional methods, are applied to predict the thermal error. The genetic algorithm is implemented to optimize the parameters in modified lumped-mass method and the covariances in Kalman filter. The simulations indicate that the proposed method performs much better compared with the traditional method of MRA, in terms of prediction accuracy and robustness under a variety of operating conditions. A compensation system is developed based on the controlling system of Siemens 840D. Validated by the compensation experiment, the thermal error after compensation has been reduced dramatically.

Suggested Citation

  • Haitong Wang & Tiemin Li & Yonglin Cai & Heng Wang, 2017. "Thermal Error Modeling of the CNC Machine Tool Based on Data Fusion Method of Kalman Filter," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, June.
    • Handle: RePEc:hin:jnlmpe:3847049
    DOI: 10.1155/2017/3847049
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2017/3847049.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2017/3847049.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/3847049?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:3847049. 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.