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Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform

  • Published:2012-09 Issue:5 Volume:51 Page:566-572
  • ISSN:0019-0578
  • Container-title:ISA Transactions
  • language:en
  • Short-container-title:ISA Transactions

Author:

Ben Salem Samira,Bacha Khmais,Chaari Abdelkader

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference11 articles.

1. Guest editorial special section on motor fault detection and diagnosis;Chow;IEEE Transactions on Industrial Electronics,2000

2. Models for bearing damage detection in induction motors using stator current monitoring;Martin Blödt;IEEE Transactions on Industrial Electronics,2008

3. Fault detection in induction motors using Hilbert and Wavelet transforms;Jimenez;Electrical Engineering,2007

4. A new method for early fault detection and diagnosis of broken rotor bars;Aydin;Energy Conversion and Management,2011

5. An advanced Park's vectors approach for bearing fault detection;Zarei;Tribology International,2009

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3. Cost-effective process experimental studies on stator inter-turn faults detection in induction motor using harmonic RPVM and decomposition wavelet transform;International Journal of Emerging Electric Power Systems;2023-01-23

4. Fault diagnosis of induction motors using artificial intelligence techniques: A systematic review;TECHNOLOGIES AND MATERIALS FOR RENEWABLE ENERGY, ENVIRONMENT AND SUSTAINABILITY: TMREES22Fr;2023

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