Diagnosis of Inter-Turn Fault in the Transformer Winding using Wavelet Based AI Approaches

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R. Rajeswari
N. Kamaraj

Abstract

In this paper, Wavelet based ANFIS for finding the inter-turn fault of a transformer is proposed. The detector uniquely responds to the winding inter-turn fault with remarkably high sensitivity. Discrimination of different percentages of winding affected by inter-turn fault is provided via ANFIS having an eight dimensional input vector. This input vector is obtained from features extracted from DWT of inter-turn faulty current, leaving the transformer phase winding. Training data for ANFIS are generated via a simulation of transformer with inter-turn fault using MATLAB. The proposed algorithm using ANFIS gives more satisfactory performance than ANN and GABPN with selected statistical data of decomposed levels of faulty current.

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How to Cite
Rajeswari, R., & Kamaraj, N. (2009). Diagnosis of Inter-Turn Fault in the Transformer Winding using Wavelet Based AI Approaches. Power Research - A Journal of CPRI, 17–26. Retrieved from https://cprijournal.in/index.php/pr/article/view/958

References

  1. Fernando H Magnago and Ali Abur, "Fault Location Using Wavelets", IEEE Transactions on Power Delivery, Vol. 13, No. 4, Oct. 1998.
  2. G T Heydt and A W Galli, "Transient Power Quality Problems Analysed Using Wavelets", IEEE Transactions on Power Delivery, Vol. 12, No. 2, April 1997.
  3. David C Robertson and Octavia I Camps, "Wavelets and Electromagnetic Power System Transients", IEEE Transactions on Power Delivery, Vol. 11, No. 2, April 1996.
  4. D C Robertson, O I Campus, J S Meyer, and W B Gish, "Wavelet and Electromagnetic Power System Transients", IEEE Trans. Power Delivery, Vol. 11, pp. 1050-1056, Apr. 1996.
  5. Hongkyun Kim, Jinmok Lee, Jae Choi, Sanghoon Lee and Jaesig Kim, "Power Quality Monitoring System Using Wavelet Based Neural Network", 2004, International Conference on Power System Technology–POWERCON 2004, Singapore, 21-24 November 2004.
  6. M V Chilukiri, P K Dash and K P Basu, "Time–Frequency–Based Pattern Recognition Technique for Detection and Classification of Power Quality Disturbances", IEEE Trans. Power Delivery.
  7. A I Taalab, H A Darwish and T A Kawady, "ANN-based Novel Fault Detector for Generator Windings Protection", IEEE Transactions on Power Delivery, Vol. 14, No. 3, July 1999.