On line trained fuzzy logic and adaptive continuous wavelet transform based high precision fault detection of IM with broken rotor bars

A. Saghafinia, S. Kahourzade, A. Mahmoudi, W. P. Hew, M. Nasir Uddin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper presents an online trained fuzzy logic and adaptive wavelet based high precision fault detection of broken rotor bars for squirrel cage induction motor (IM). Motor faults which consist of broken rotor bars, bearing decay, eccentricity, etc. appears as different frequencies in the stator current signals. The winding function is used to obtain stator current and speed signals at different fault and load conditions. These signals are analysed through the adaptive continuous wavelet transform (CWT) to detect the amplitudes and frequency components corresponding to different fault and load conditions. The coefficients of CWT are adapted online based on the harmonics amplitude, which are the output of CWT. These amplitudes and frequencies are applied to train a fuzzy logic controller (FLC) in simulation. Then the adaptive CWT and trained FLC are applied to detect the fault condition of a large size motor in both simulation and realtime. The experimental results found that the proposed adaptive CWT and FLC based fault detection method can detect the motor fault conditions accurately. Thus, the proposed method could be a potential candidate to detect the motor fault, especially for large size industrial motors.

Original languageEnglish
Title of host publication2012 IEEE Industry Applications Society Annual Meeting, IAS 2012
DOIs
Publication statusPublished - 1 Dec 2012
Externally publishedYes
Event2012 IEEE Industry Applications Society Annual Meeting, IAS 2012 - Las Vegas, NV, United States
Duration: 7 Oct 201211 Oct 2012

Publication series

NameConference Record - IAS Annual Meeting (IEEE Industry Applications Society)
ISSN (Print)0197-2618

Conference

Conference2012 IEEE Industry Applications Society Annual Meeting, IAS 2012
CountryUnited States
CityLas Vegas, NV
Period7/10/1211/10/12

Keywords

  • adaptive continuous wavelet transform
  • broken rotor bars
  • fault detection
  • fuzzy logic controller
  • squirrel cage induction motor

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    Saghafinia, A., Kahourzade, S., Mahmoudi, A., Hew, W. P., & Uddin, M. N. (2012). On line trained fuzzy logic and adaptive continuous wavelet transform based high precision fault detection of IM with broken rotor bars. In 2012 IEEE Industry Applications Society Annual Meeting, IAS 2012 [6374027] (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)). https://doi.org/10.1109/IAS.2012.6374027