Journal of Mechanical Science and Technology

The Korean Society of Mechanical Engineers (대한기계학회)
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Neural Network Based Expert System for Induction Motor Faults Detection

  • Su Hua (Department of Computation for Design and Optimization, MIT) ;
  • Chong Kil-To (Faculty of Electronics & Information Engineering, Chonbuk National University)
  • Published : 2006.07.01
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Abstract

Early detection and diagnosis of incipient induction machine faults increases machinery availability, reduces consequential damage, and improves operational efficiency. However, fault detection using analytical methods is not always possible because it requires perfect knowledge of a process model. This paper proposes a neural network based expert system for diagnosing problems with induction motors using vibration analysis. The short-time Fourier transform (STFT) is used to process the quasi-steady vibration signals, and the neural network is trained and tested using the vibration spectra. The efficiency of the developed neural network expert system is evaluated. The results show that a neural network expert system can be developed based on vibration measurements acquired on-line from the machine.

Keywords

References

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