Online Adaptive Continuous Wavelet Transform and Fuzzy Logic Based High Precision Fault Detection of Broken Rotor Bars for IM
Volume 4, Issue 6, December 2016, Pages: 157-168
Received: Nov. 24, 2016;
Accepted: Jan. 16, 2017;
Published: Feb. 7, 2017
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Ali Saghafinia, Department of Electrical Engineering, Majlesi Branch, Islamic Azad University, Majlesi, Iran
S. Hr. Kaboli, UM Power Energy Dedicated Advanced Centre (UMPEDAC), Wisma R&D, University of Malaya (UM), Jalan Pantai Baharu, Kuala Lumpur, Malaysia
This paper presents an intelligent fault detection based on adaptive continuous wavelet transform of broken rotor bars for Induction Motor (IM). Broken rotor bars, bearing decay, eccentricity, as motor faults appears as different frequencies in the stator current signals. The stator current and speed signals at deferent operation conditions obtained from the winding function are analysed through the adaptive continuous wavelet transform (CWT) to detect the amplitudes and frequency components corresponding to different broken bar fault and load conditions. The adaptive coefficients of CWT based on the harmonics amplitude, are applied to train a fuzzy logic controller (FLC) in simulation. Then, detection of the fault condition are done based on the adaptive CWT and trained FLC in both simulation and real-time. The experimental results are confirmed the simulation results and show the effectiveness of the proposed method to detect the motor fault conditions accurately.
S. Hr. Kaboli,
Online Adaptive Continuous Wavelet Transform and Fuzzy Logic Based High Precision Fault Detection of Broken Rotor Bars for IM, Science Research.
Vol. 4, No. 6,
2016, pp. 157-168.
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