Journal of Ocean Engineering and Technology (한국해양공학회지)

Korean Society of Ocean Engineers (한국해양공학회)
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Fault Diagnosis of Rotating Machines Using Wavelet Transform and Neural Network

웨이블렛 변환과 신경망 알고리즘을 이용한 회전기기 결함진단

  • 최태묵 (부산대학교 조선해양공학과 대학원) ;
  • 조대승 (부산대학교 조선해양공학과)
  • Published : 2002.10.01
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Abstract

The fault detection and diagnosis of rotating machinery widely used in plants including the ship are important for maintaining the performance of Plants. Recently, the wavelet transform has been recognized an efficient method to detect a little variation of physical quantities by the synchronous localization of time and frequency domains using the translation and dilation of signals. In this Paper, In order to develop efficient and reliable fault detection and diagnosis system rotating machines, the performance of wavelet transformation to detect a little variation of machine status and neural network to diagnose the cause of machine faults are investigated and experimented.

Keywords

References

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