Vibration signature analysis for monitoring rotor broken bar in double squirrel cage induction motors based on wavelet analysis

Antonino Oscar Di Tommaso, Rosario Miceli, Yasser Gritli, Fiorenzo Filippetti, Claudio Rossi

Risultato della ricerca: Article

10 Citazioni (Scopus)

Abstract

Purpose - The purpose of this paper is to present a diagnosis technique, for rotor broken bar in double cage induction motor, based on advanced use of Wavelet Transform Analysis. The proposed technique is experimentally validated.Design/methodology/approach - The proposed approach is based on a combined use of Frequency Sliding (FS) and Wavelet Transform (WT) analysis, to isolate the contribution of the rotor fault components issued from vibration signals in a single frequency band.Findings - The proposed technique is reliable for tracking the rotor fault components over time-frequency domain. The quantitative analysis results based on this technique are the proof of its robustness.Research limitations/implications - The validity of the proposed diagnosis approach is not limitted to the analysis under steady-state operating conditions, but also for time-verying conditions where rotor fault components are spread in a wide frequency range.Practical implications - The developed approach is best suited for automotive or high power traction systems, in which safe-operating and availability are mandatory.Originality/value - The paper presents a diagnosis technique for rotor broken bar in double cage induction motor base on advanced use of Wavelet Transform which allows the extraction of the most relevant rotor fault component issued from axial vibration signal and clamping it in a single frequency bandwidth, avoiding confusions with other components and false interpretations.
Lingua originaleEnglish
pagine (da-a)1625-1641
Numero di pagine17
RivistaCOMPEL
Volume33
Stato di pubblicazionePublished - 2014

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Squirrel cage motors
Cage
Wavelet analysis
Induction Motor
Wavelet Analysis
Induction motors
Rotor
Signature
Rotors
Vibration
Monitoring
Fault
Wavelet transforms
Wavelet Transform
Vibration Signal
Quantitative Analysis
Power System
High Power
Frequency bands
Design Methodology

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cita questo

Vibration signature analysis for monitoring rotor broken bar in double squirrel cage induction motors based on wavelet analysis. / Di Tommaso, Antonino Oscar; Miceli, Rosario; Gritli, Yasser; Filippetti, Fiorenzo; Rossi, Claudio.

In: COMPEL, Vol. 33, 2014, pag. 1625-1641.

Risultato della ricerca: Article

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AU - Di Tommaso, Antonino Oscar

AU - Miceli, Rosario

AU - Gritli, Yasser

AU - Filippetti, Fiorenzo

AU - Rossi, Claudio

PY - 2014

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AB - Purpose - The purpose of this paper is to present a diagnosis technique, for rotor broken bar in double cage induction motor, based on advanced use of Wavelet Transform Analysis. The proposed technique is experimentally validated.Design/methodology/approach - The proposed approach is based on a combined use of Frequency Sliding (FS) and Wavelet Transform (WT) analysis, to isolate the contribution of the rotor fault components issued from vibration signals in a single frequency band.Findings - The proposed technique is reliable for tracking the rotor fault components over time-frequency domain. The quantitative analysis results based on this technique are the proof of its robustness.Research limitations/implications - The validity of the proposed diagnosis approach is not limitted to the analysis under steady-state operating conditions, but also for time-verying conditions where rotor fault components are spread in a wide frequency range.Practical implications - The developed approach is best suited for automotive or high power traction systems, in which safe-operating and availability are mandatory.Originality/value - The paper presents a diagnosis technique for rotor broken bar in double cage induction motor base on advanced use of Wavelet Transform which allows the extraction of the most relevant rotor fault component issued from axial vibration signal and clamping it in a single frequency bandwidth, avoiding confusions with other components and false interpretations.

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