IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v3y2011i2p159-177.html
   My bibliography  Save this article

Wavelet decomposition and support vector machine for fault diagnosis of monoblock centrifugal pump

Author

Listed:
  • V. Muralidharan
  • V. Sugumaran
  • N.R. Sakthivel

Abstract

Monoblock centrifugal pumps play a very critical role in a variety of applications and condition monitoring of the various mechanical components of centrifugal pump becomes essential which in turn increases the productivity and reduces the breakdowns. Vibration-based continuous monitoring and analysis using machine learning approaches are gaining momentum. Particularly, artificial neural networks fuzzy logic was employed for continuous monitoring and fault diagnosis. This paper presents the use of support vector machine (SVM) algorithm for fault diagnosis through discrete wavelet features extracted from vibration signals of good and faulty conditions of the components of centrifugal pump. The classification accuracies were computed for different types of classifiers such as artificial neural network (ANN), support vector machine (SVM) and J48 decision tree algorithm.

Suggested Citation

  • V. Muralidharan & V. Sugumaran & N.R. Sakthivel, 2011. "Wavelet decomposition and support vector machine for fault diagnosis of monoblock centrifugal pump," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 3(2), pages 159-177.
    • Handle: RePEc:ids:injdan:v:3:y:2011:i:2:p:159-177
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=39849
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:injdan:v:3:y:2011:i:2:p:159-177. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.