Transformer Incipient Fault Diagnosis Using Artificial Neural Network

  • Nandkumar Wagh
  • Dinesh Deshpande
Part of the Communications in Computer and Information Science book series (CCIS, volume 250)


This paper presents the artificial neural network approach for incipient fault diagnosis of power transformers filled with oil.DGA data from reputed testing unit is obtained to deal with all possible faulty conditions in a power transformer. Well designed artificial neural network having the adaptive features and fast diagnosis capabilities are proposed and testing and training results of DGA samples made available are presented using neural network tool in Matlab 7.10. The diagnosis accuracy obtained during training and testing of samples is better. Programming features are incorporated proposing appropriate preventive maintenance action represented by a type of fault, so that the transformer in service can be saved.


Artificial Neural Network Hide Layer Fault Diagnosis Connection Weight Power Transformer 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nandkumar Wagh
    • 1
  • Dinesh Deshpande
    • 1
  1. 1.Electrical Engineering DepartmentMaulana Azad National Institute of TechnologyBhopalIndia

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