A method to classify the signals from artificially prepared defects in GIS using the decision tree method

H. Hirose, T. Ohhata, Y. Kotou, S. Matsuda, M. Hikita, T. Nishimura, S. Ohtsuka, S. Matsumoto, S. Tsuru, J. Ichimaru

Research output: Contribution to conferencePaper

Abstract

On-line diagnosing of GIS (Gas Insulated Switchgears) requires the pattern classification and identification of signals that are emitted from GIS. To classify the patterns correctly, substantial data sets that are emitted by artificially mimicked defects in GIS are needed. Applying the neural networks to the data sets, in general, identification methods of defects in GIS have widely been developed. Some identification system shows a good success such that the misclassification rate is reduced to below 5%; the key features in identification, however, are not obviously revealed in neural networks systems because of nonlinear network structures. The decision tree method that classifies the signals using the feature rules in plain graphical representations can explains the classification rules in clear forms. We applied the decision tree classification method to the signals emitted from the signals by artificially prepared defects in GIS, and find that the method shows a good classification rates over 95% which are comparable to that in neural networks. We also discuss the robustness from noise, and compare the results of the misclassification rates by the two methods.

Original languageEnglish
Pages885-888
Number of pages4
Publication statusPublished - 2005 Oct 7
Event2005 International Symposium on Electrical Insulating Materials, ISEIM 2005 - Kitakyushu, Japan
Duration: 2005 Jun 52005 Jun 9

Conference

Conference2005 International Symposium on Electrical Insulating Materials, ISEIM 2005
CountryJapan
CityKitakyushu
Period05/6/505/6/9

ASJC Scopus subject areas

  • Engineering(all)
  • Materials Science(all)

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    Hirose, H., Ohhata, T., Kotou, Y., Matsuda, S., Hikita, M., Nishimura, T., Ohtsuka, S., Matsumoto, S., Tsuru, S., & Ichimaru, J. (2005). A method to classify the signals from artificially prepared defects in GIS using the decision tree method. 885-888. Paper presented at 2005 International Symposium on Electrical Insulating Materials, ISEIM 2005, Kitakyushu, Japan.