IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8049516.html
   My bibliography  Save this article

Application of Adaptive Local Iterative Filtering and Permutation Entropy in Gear Fault Recognition

Author

Listed:
  • Wenbin Zhang
  • Yun Wang
  • Yushuo Tan
  • Dewei Guo
  • Yasong Pu

Abstract

In this paper, a fault identification method combining adaptive local iterative filtering and permutation entropy is proposed. The adaptive local iterative filtering can decompose the nonstationary signal into a finite number of stationary intrinsic mode functions. And the experiment gear fault data are decomposed into several intrinsic mode functions by this method. Then, using the permutation entropy to calculate each intrinsic mode function, it is found that the permutation entropy of the first several intrinsic mode functions can represent the characteristics of different fault types, and the permutation entropy of the intrinsic mode function corresponding to the rotating frequency signal of the gear system could be the boundary. Finally, the fault type of gear is identified by calculating the gray correlation degree of permutation entropy of essential mode function of vibration signal decomposition under different working conditions. The example analysis results show that the proposed method can be effectively applied to the fault diagnosis of the gear system.

Suggested Citation

  • Wenbin Zhang & Yun Wang & Yushuo Tan & Dewei Guo & Yasong Pu, 2021. "Application of Adaptive Local Iterative Filtering and Permutation Entropy in Gear Fault Recognition," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, October.
  • Handle: RePEc:hin:jnlmpe:8049516
    DOI: 10.1155/2021/8049516
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/8049516.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2021/8049516.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2021/8049516?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:8049516. 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.