Improved Classification by Non Iterative and Ensemble Classifiers in Motor Fault Diagnosis

Improved Classification by Non Iterative and Ensemble Classifiers in Motor Fault Diagnosis

Data driven approach for multi-class fault diagnosis of induction motor using MCSA at steady state condition is a complex pattern classification problem. This investigation has exploited the built-in ensemble process of non-iterative classifiers to resolve the most challenging issues in this area,...

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Bibliographic Details
Main Authors: PANIGRAHY, P. S., CHATTOPADHYAY, P.
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2018-02-01
Series:Advances in Electrical and Computer Engineering
Subjects:
discrete wavelet transforms
fault diagnosis
feature extraction
induction motors
machine learning
Online Access:http://dx.doi.org/10.4316/AECE.2018.01012

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