35
Views
0
CrossRef citations to date
0
Altmetric
Conference Paper

Descriptive Data Mining of Partial Discharge Using Decision Tree With Genetic Algorithm

, &
Pages 249-259 | Published online: 22 Sep 2015

References

  • Lai, K. X., Phung, B. T. & Blackburn, T. R. 2009, Australian Journal of Electrical & Electronics Engineering, Vol. 6, No. 3, pp. 249–260.
  • Babnik, T., Aggarwal, R. & Moore, P. 2007, “Data mining on a transformer partial discharge data using the self-organizing map”, IEEE Transactions on Dielectrics and Electrical Insulation, (see also IEEE Transactions on Electrical Insulation), Vol. 14, pp. 444–452.
  • Bartnikas, R. 2002, “Partial discharges. Their mechanism, detection and measurement”, IEEE Transactions on Dielectrics and Electrical Insulation, (see also IEEE Transactions on Electrical Insulation), Vol. 9, pp. 763–808.
  • Chatpattananan, V., Pattanadech, N. & Yutthagowith, P. 2006, “Partial Discharge Classification on High Voltage Equipment with K-Means”, 8th International Conference on Properties and Applications of Dielectric Materials.
  • Contin, A. & Pastore, S. 2006, “Classification of Partial Discharge Signals by Means of Auto-Correlation Function Evaluation”, IEEE International Symposium on Electrical Insulation, pp. 302–305.
  • Dawes, C. L. & Hoover, P. L. 1926, “Ionisation studies in paper-insulated cables”, Journal of the American Institute of Electrical Engineers, Vol. 45, pp. 337–347.
  • Dunham, M. H. 2003, Data mining introductory and advanced topics, Prentice Hall/Pearson Education, Upper Saddle River, N.J.
  • Feng, Z., Jian, L., Ruijin, L. & Grzybowski, S. 2007, “Aged oil-paper classification using statistical parameters and clustering analysis”, Annual Report — Conference on Electrical Insulation and Dielectric Phenomena, CEIDP 2007.
  • Han, J. & Kamber, M. 2006, Data mining: concepts and techniques, Elsevier, Amsterdam, Morgan Kaufmann, Boston, San Francisco, CA.
  • Hand, D. J., Smyth, P. & Mannila, H. 2001, Principles of data mining, MIT Press, Cambridge, Mass.
  • Kantardzic, M. 2003, Data mining: concepts, models, methods and algorithms, IEEE Pr., Wiley Interscience, Piscataway, NJ.
  • Karthikeyan, B., Gopal, S., Srinivasan, P. S. & Venkatesh, S. 2006, “Efficacy Of Back Propagation Neural Network Based On Various Statistical Measures For Pd Pattern Classification Task”, 8th International Conference on Properties and applications of Dielectric Materials.
  • Lin, T., Aggarwal, R. K. & Kim, C. H. 2004, “Identification of the defective equipments in GIS using the self organizing map”, IEE Proceedings — Generation, Transmission and Distribution, Vol. 151, pp. 644–650.
  • Mang-Hui, W. 2005, “Partial discharge pattern recognition of current transformers using an ENN”, IEEE Transactions on Power Delivery, Vol. 20, pp. 1984–1990.
  • Murthy, D. N. P. 2003, Weibull Models, 1st edition, John Wiley & Sons, Hoboken, NJ.
  • Negnevitsky, M. 2005, Artificial intelligence: a guide to intelligent systems, Addison-Wesley, Harlow, England.
  • Phung, B. T. 1997, “Computer-based Partial Discharge Detection and Characterisation”, PhD Thesis, School of Electrical Engineering, University of New South Wales, Sydney.
  • Phung, B. T., Blackburn, T. R. & James, R. E. 1992, “The use of artificial neural networks in discriminating partial discharge patterns”, Sixth International Conference on Dielectric Materials, Measurements and Applications.
  • Seong-Hee, P., Seok-Jae, K., Kee-Joe, L. & Seong-Hwa, K. 2005, “Comparison of recognition rates between BP and ANFIS with FCM clustering method on off-line PD diagnosis of defect models of traction motor stator coil”, Proceedings of 2005 International Symposium on Electrical Insulating Materials, ISEIM 2005.
  • Tag-Yong, K., Hyun-Taek, S., Jong-Yong, L., Kyu-Ho, Y., Chung-Ho, L. & Jin-Woong, H. 2006, “Analysis of Partial Discharge Using Non-Linear Clustering Algorism”, 8th International Conference on Properties and Applications of Dielectric Materials.
  • Tao, H. & Fang, M. T. C. 2001, “Detection and classification of partial discharge using a feature decomposition-based modular neural network”, IEEE Transactions on Instrumentation and Measurement, Vol. 50, pp. 1349–1354.
  • Wen-Yeau, C. & Hong-Tzer, Y. 2006, “Partial Discharge Pattern Recognition of Molded Type Transformers Using Self Organizing Map”, 8th International Conference on Properties and Applications of Dielectric Materials.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.