Diagnosis of mechanical unbalance for double cage induction motor load in time-varying conditions based on motor vibration signature analysis

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

Risultato della ricerca: Other

4 Citazioni (Scopus)

Abstract

This paper investigates the detectability of mechanical unbalance in double cage induction motor load using motor vibration signature analysis technique. Rotor imbalances induce specific harmonic components in electrical, electromagnetical, and mechanical quantities. Harmonic components characteristic of this category of rotor faults, issued from vibration signals analysis, are closely related to rotating speed of the rotor, which complicates its detection under non-stationary operating conditions of the motor. Firstly, experimental results were performed first under healthy and mechanical load unbalance cases, for different load levels under steady-state operating conditions to evaluate the sensitivity of motor axial vibration signature analysis (MAVSA) and motor radial vibration signature analysis (MRVSA) techniques. Secondly, and in order to overcome the limitations of the FFT analysis in time-varying conditions, a simple and effective method based on advanced use of wavelet analysis is proposed, that allows the diagnosis of mechanical load unbalance for a double cage induction machine operating under non-stationary conditions. Experimental tests were conducted for these purposes showing the effectiveness of the presented technique under time-varying operating conditions.
Lingua originaleEnglish
Pagine1157-1162
Numero di pagine6
Stato di pubblicazionePublished - 2013

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment

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