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Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors
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 Title & Authors
Robust Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors
Hwang, Don-Ha; Youn, Young-Woo; Sun, Jong-Ho; Kim, Yong-Hwa;
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 Abstract
This paper proposes a new diagnosis algorithm to detect broken rotor bars (BRBs) faults in induction motors. The proposed algorithm is composed of a frequency signal dimension order (FSDO) estimator and a fault decision module. The FSDO estimator finds a number of fault-related frequencies in the stator current signature. In the fault decision module, the fault diagnostic index from the FSDO estimator is used depending on the load conditions of the induction motors. Experimental results obtained in a 75 kW three-phase squirrel-cage induction motor show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to a zoom multiple signal classification (ZMUSIC) and a zoom estimation of signal parameters via rotational invariance techniques (ZESPRIT).
 Keywords
Broken rotor bar;Induction motor;Fault diagnosis;Current signal;
 Language
English
 Cited by
1.
유도전동기 온라인 감시진단 시스템 개발,김기범;윤영우;황돈하;선종호;정태욱;

조명전기설비학회논문지, 2014. vol.28. 5, pp.23-30 crossref(new window)
1.
Development of Online Monitoring System for Induction Motors, Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 2014, 28, 5, 23  crossref(new windwow)
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