IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/9296720.html
   My bibliography  Save this article

Research on the Fault Feature Extraction Method of Rotor Systems Based on GAW-PSO

Author

Listed:
  • Feng Miao
  • Rongzhen Zhao
  • Xianli Wang

Abstract

In order to solve the problem of blind separation of signals from dynamic hybrid rotor systems, this paper proposed an improved adaptive inertial weight particle swarm optimization method based on genetic mechanism. The method takes the negative entropy of separated signal as the objective function and adaptively adjusts the inertia weight according to the difference of particle fitness, thus reducing the number of invalid iterations. At the same time, genetic hybridization mechanism was introduced to increase population diversity and facilitate the processing of dynamic mixed signals. The orthogonal matrix is expressed as a parameterized form, which can reduce the complexity of the algorithm. The simulation results showed that the performance of the proposed method is better than that of the traditional method for blind separation of dynamic hybrid analog mechanical signals. It can separate the actual dynamic rotor system signals and achieve the purpose of fault feature extraction.

Suggested Citation

  • Feng Miao & Rongzhen Zhao & Xianli Wang, 2020. "Research on the Fault Feature Extraction Method of Rotor Systems Based on GAW-PSO," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, March.
    • Handle: RePEc:hin:jnlmpe:9296720
    DOI: 10.1155/2020/9296720
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2020/9296720.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2020/9296720.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2020/9296720?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:9296720. 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.