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Single Parameter Fault Identification Technique for DC Motor through Wavelet Analysis and Fuzzy Logic
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 Title & Authors
Single Parameter Fault Identification Technique for DC Motor through Wavelet Analysis and Fuzzy Logic
Winston, D.Prince; Saravanan, M.;
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 Abstract
DC motors are widely used in industries like cement, paper manufacturing, etc., even today. Early fault identification in dc motors significantly improves its life time and reduces power consumption. Many conventional and soft computing techniques for fault identification in DC motors including a recent work using model based analysis with the help of fuzzy logic are available in literature. In this paper fuzzy logic and norm based wavelet analysis of startup transient current are proposed to identify and quantify the armature winding fault and bearing fault in DC motors, respectively. Results obtained by simulation using Matlab and Simulink are presented in this paper to validate the proposed work.
 Keywords
Discrete wavelet transform;Fuzzy logic;Fault identification;DC motor;Norm analysis;
 Language
English
 Cited by
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2.
Identification of Shearer Cutting Patterns Using Vibration Signals Based on a Least Squares Support Vector Machine with an Improved Fruit Fly Optimization Algorithm, Sensors, 2016, 16, 1, 90  crossref(new windwow)
3.
Intelligent fault diagnosis of rotating machinery using support vector machine with ant colony algorithm for synchronous feature selection and parameter optimization, Neurocomputing, 2015, 167, 260  crossref(new windwow)
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