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Vibration Fault Diagnosis of Large Generator Sets Using Extension Neural Network-Type 1

  • Meng-hui Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

This paper proposes a novel neural network called Extension Neural Network-Type 1 (ENN1) for vibration fault recognition according to generator vibration characteristic spectra. The proposed ENN1 has a very simple structure and permits fast adaptive processes for new training data. Moreover, the learning speed of the proposed ENN1 is shown to be faster than the previous approaches. The proposed method has been tested on practical diagnostic records in China with rather encouraging results.

Keywords

Fault Diagnosis Vibration Signal Multilayer Neural Network Extension Distance Fault Diagnosis Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Meng-hui Wang
    • 1
  1. 1.Department of Electrical EngineeringNational Chin-Yi Institute of TechnologyTaiping, TaichungTaiwan, ROC

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