Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2014(Vol.8, Issue:16)
Article Information:

A Hybrid Technique for the Detection of Broken Rotor Bar of Induction Motor

I. Kathir, S. Balakrishnan and B.V. Manikandan
Corresponding Author:  I. Kathir 
Submitted: ‎June ‎17, ‎2014
Accepted: July ‎19, ‎2014
Published: October 25, 2014
Abstract:
A hybrid technique for diagnosing broken rotor bar fault of induction motor using Multi-Wavelet Transform (MWT) and radial basis neural network is presented. The stator currents of induction motor are preprocessed using multi-wavelet transform and the decomposed components are obtained. Then, these features are given as input to the neural network to identify fault. This paper compares the proposed hybrid technique with MWT-Feed Forward Neural Network (FFNN) and Discrete Wavelet Transform-FFNN techniques. These techniques are compared using the concept of classifier performance. From the simulation results, it is evident that the proposed method is superior to other methods with regard to objective proposed.

Key words:  Broken rotor bar, classifier performance, multiwavelet transform , radial basis neural network, , ,
Abstract PDF HTML
Cite this Reference:
I. Kathir, S. Balakrishnan and B.V. Manikandan, . A Hybrid Technique for the Detection of Broken Rotor Bar of Induction Motor. Research Journal of Applied Sciences, Engineering and Technology, (16): 1824-1832.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved