By Topic

Scale Invariant Feature Extraction Algorithm for the Automatic Diagnosis of Rotor Asymmetries in Induction Motors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Jose Antonino-Daviu ; Instituto de Ingeniería Energética, Universidad Politécnica de Valencia, Valencia, SPAIN ; Selin Aviyente ; Elias G. Strangas ; Martin Riera-Guasp

The development of portable devices that make the reliable diagnosis of faults in electric motors possible has become a challenge for many researchers and maintenance enterprises. These machines intervene in a huge amount of processes and applications and their eventual failure may imply important costs in terms of time and money. However, the aforementioned issue remains unsolved because most of the developed fault diagnosis techniques rely on the user expertise, since they are based on a qualitative interpretation of the results. This complicates the implementation of these methodologies in condition monitoring systems or devices. The objective of this paper is to propose an integral methodology that is able to diagnose the presence of rotor bar failures in an automatic way. The proposed algorithm combines the Discrete Wavelet Transform with the scale transform for feature extraction and correlation coefficient for pattern recognition. The algorithm is applied to both small and large motors operating in a wide range of conditions. The results illustrate the validity and generality of the approach for automatic condition monitoring of electric motors.

Published in:

IEEE Transactions on Industrial Informatics  (Volume:9 ,  Issue: 1 )