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Sound Sensor Placement Strategy for Condition Monitoring of Induction Motor Bearing

  • Iradiratu Diah Prahmana Karyatanti*
  • , Istiyo Winarno
  • , Ardik Wijayanto
  • , Dwisetiono
  • , Nuddin Harahab
  • , Ratno Bagus Edy Wibowo
  • , Agus Budiarto
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Damage to the bearing elements will affect the rotation of the rotor and lead to the cessation of motor operation. Therefore, it is imperative to monitor the condition of the bearings to provide information on timely maintenance actions, improve reliability, and prevent serious damage. One of the important keys to an effective and accurate monitoring system is the placement of sensors and proper signal processing. Sound signal issued by the motor during operation capable of describing its elements’ condition. Therefore, this study aims to develop a sound sensor placement strategy appropriate for monitoring the condition of induction motor bearing components. This study was carried out on three-phase induction motors’ outer-race, inner-race, and ball-bearing sections with the signal processing method using the spectrum analysis. Furthermore, the effect of sound sensor placement on condition monitoring accuracy was determined using the One-Way Analysis of Variance (One-Way ANOVA) approach. This process tests the null hypothesis and determines whether the average of all groups is the same (H0) or different (H1). Furthermore, Tukey’s test was applied to obtain effective sound sensor placement, with voice-based condition monitoring used for effective identification. The test found that the accuracy of monitoring the bearing condition was 92.66% by placing the sound sensor at 100 cm from the motor body.

Original languageEnglish
Pages (from-to)3093-3106
Number of pages14
JournalPertanika Journal of Science and Technology
Volume31
Issue number6
DOIs
Publication statusPublished - Oct 2023

Keywords

  • Bearing
  • condition monitoring
  • placement strategy
  • sound signal
  • spectrum analysis

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