Induction motor bearing fault detection using hybrid kurtosis-based method

Mohd Sufian Othman, Mohd. Zaki Nuawi, Ramizi Mohamed

Research output: Contribution to journalArticle

Abstract

Wide usage of induction motors in industries and domestics demand a fast and reliable condition monitoring method to make sure no interruption in operation and also to prevent catastrophic damages which are costly and time consuming. Bearing, the most fragile part in induction motor has becomea prominent subject recently.Vibration and AE measurement are popular methods in bearing fault detection. However,the combination of both signals in an analysis still very few in the literature.Hence, in the present study, a hybrid kurtosis-based method was proposed to analyse simultaneous vibration and AE signal for identification of bearing faults, i.e. inner race, and outer race. Comparison with classical methods, i.e. kurtosis and envelope spectrum analysis also discussed. The results show that the proposed system able to detect inner race and outer race defectedbearings in4 poles and 2 poles induction motor.

Original languageEnglish
Pages (from-to)33453-33456
Number of pages4
JournalInternational Journal of Applied Engineering Research
Volume10
Issue number13
Publication statusPublished - 24 Aug 2015

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Bearings (structural)
Fault detection
Induction motors
Poles
Condition monitoring
Spectrum analysis
Industry

Keywords

  • Condition monitoring
  • Hybrid I-kaz
  • Kurtosis
  • Statistical analysis

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Induction motor bearing fault detection using hybrid kurtosis-based method. / Othman, Mohd Sufian; Nuawi, Mohd. Zaki; Mohamed, Ramizi.

In: International Journal of Applied Engineering Research, Vol. 10, No. 13, 24.08.2015, p. 33453-33456.

Research output: Contribution to journalArticle

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