IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/735485.html
   My bibliography  Save this article

Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method

Author

Listed:
  • Meng-Hui Wang
  • Pi-Chu Wu

Abstract

Due to the passenger’s security, the recognized hidden faults in car engines are the most important work for a maintenance engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel fault recognition method based on the genetic algorithm (GA) and the extension theory and also apply this method to the fault recognition of a practical car engine. The proposed recognition method has been tested on the Nissan Cefiro 2.0 engine and has also been compared to other traditional classification methods. Experimental results are of great effect regarding the hidden fault recognition of car engines, and the proposed method can also be applied to other industrial apparatus.

Suggested Citation

  • Meng-Hui Wang & Pi-Chu Wu, 2014. "Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, March.
    • Handle: RePEc:hin:jnlmpe:735485
    DOI: 10.1155/2014/735485
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2014/735485.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2014/735485.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/735485?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:735485. 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.