Impulse Fault Analysis

This chapter presents a detailed description of different methods for impulse fault analysis of transformers. These methods form a broad spectrum ranging from the use conventional techniques to computational intelligence tools. All these aspects for impulse fault analysis are discussed in this chapter.

[1]  K.L. Wong.  Application of very-high-frequency (VHP) method to ceramic insulators , 2004, IEEE Transactions on Dielectrics and Electrical Insulation.

[2]  R. Candela,et al.  PD recognition by means of statistical and fractal parameters and a neural network , 2000 .

[3]  J. Mercer.  Functions of Positive and Negative Type, and their Connection with the Theory of Integral Equations , 1909 .

[4]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[5]  E. Gulski,et al.  The use of fractal features for recognition of 3-D discharge patterns , 1995 .

[6]  L. Satish,et al.  Can fractal features be used for recognizing 3-d partial discharge patterns , 1995 .

[7]  Sankar K. Pal,et al.  Case generation using rough sets with fuzzy representation , 2004, IEEE Transactions on Knowledge and Data Engineering.

[8]  T. Henriksen,et al.  Inductances for the Calculation of Transient Oscillations in Transformers , 1974 .

[9]  Sivaji Chakravorti,et al.  Investigations on the usefulness of an expert system for impulse fault analysis in distribution transformers , 2003 .

[10]  Nello Cristianini,et al.  Support vector machines , 2009 .

[11]  B. Chatterjee,et al.  Cross-wavelet transform as a new paradigm for feature extraction from noisy partial discharge pulses , 2010, IEEE Transactions on Dielectrics and Electrical Insulation.

[12]  A. De,et al.  A fuzzy ARTMAP fault classifier for impulse testing of power transformers , 2004, IEEE Transactions on Dielectrics and Electrical Insulation.

[13]  P. J. Griffin,et al.  An Artificial Neural Network Approach to Transformer Fault Diagnosis , 1996, IEEE Power Engineering Review.

[14]  Ryszard Malewski,et al.  Impulse testing of power transformers using the transfer function method , 1988 .

[15]  D. Levy,et al.  Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics. , 1997, Circulation.

[16]  Amitava Chatterjee,et al.  Cross-correlation aided support vector machine classifier for classification of EEG signals , 2009, Expert Syst. Appl..

[17]  L. Satish.  Short-time Fourier and wavelet transforms for fault detection in power transformers during impulse tests , 1998 .

[18]  Alexander Mamishev,et al.  Analysis of high impedance faults using fractal techniques , 1995 .

[19]  P.T.M. Vaessen,et al.  A new frequency response analysis method for power transformers , 1992 .

[20]  S. Chakravorti,et al.  Identification of simultaneously occurring dynamic disc-to-disc insulation failures in transformer winding under impulse excitation , 2012, IEEE Transactions on Dielectrics and Electrical Insulation.

[21]  Debangshu Dey,et al.  Cross-correlation-aided Fuzzy c-Means for Classification of Dynamic Faults in Transformer Winding During Impulse Testing , 2010 .

[22]  P. A. Abetti,et al.  Transformer Models for the Determination of Transient Voltages [includes discussion] , 1953, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.

[23]  M. J. Katz,et al.  Fractals and the analysis of waveforms. , 1988, Computers in biology and medicine.

[24]  Xiaoli Li,et al.  Computational Neuronal Oscillations using Morlet Wavelet Transform , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[25]  Z. Pawlak.  Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[26]  James M. Keller,et al.  Texture description and segmentation through fractal geometry , 1989, Comput. Vis. Graph. Image Process..

[27]  P.T.M. Vaessen.  Transformer model for high frequencies , 1988 .

[28]  Abhinandan De,et al.  Recognition of Impulse Fault Patterns in Transformers Using Kohonen's Self-Organizing Feature Map , 2002 .

[29]  K. D. Srivastava,et al.  Condition monitoring of transformers in service by the low voltage impulse test method , 1999 .

[30]  F. de Leon,et al.  Complete transformer model for electromagnetic transients , 1994 .

[31]  Chen-Fu Chien,et al.  Rough set theory for data mining for fault diagnosis on distribution feeder , 2004 .

[32]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[33]  Andrew Kusiak,et al.  Rough set theory: a data mining tool for semiconductor manufacturing , 2001 .

[34]  Brian Litt,et al.  A comparison of waveform fractal dimension algorithms , 2001 .

[35]  P. A. Abetti,et al.  Bibliography on the surge performance of transformers and rotating machines , 1958 .

[36]  Sivaji Chakravorti,et al.  Can fractal techniques be used for impulse fault pattern discrimination in distribution transformers , 2004 .

[37]  Michael Barr,et al.  The Emperor's New Mind , 1989 .

[38]  L. Pietronero,et al.  Fractal Dimension of Dielectric Breakdown , 1984 .

[39]  P. Purkait,et al.  Translationally adaptive fuzzy classifier for transformer impulse fault identification , 2003 .

[40]  B. Chatterjee,et al.  Rough-granular approach for impulse fault classification of transformers using cross-wavelet transform , 2008, IEEE Transactions on Dielectrics and Electrical Insulation.

[41]  P. Purkait,et al.  Pattern classification of impulse faults in transformers by wavelet analysis , 2002 .

[42]  A. S. Morched,et al.  A high frequency transformer model for the EMTP , 1993 .

[43]  Carlos Sevcik,et al.  A procedure to Estimate the Fractal Dimension of Waveforms , 2010, 1003.5266.

[44]  J. H. Hagenguth.  Progress in impulse testing of transformers , 1944, Electrical Engineering.

[45]  Amitava Chatterjee,et al.  Support vector machines employing cross-correlation for emotional speech recognition , 2009 .

[46]  M. Fujii,et al.  Fractal character of DC trees in polymethylmethacrylate , 1991 .

[47]  Yiyu Yao,et al.  Rough sets, neighborhood systems and granular computing , 1999, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411).

[48]  Gevork B. Gharehpetian,et al.  Hybrid modelling of inhomogeneous transformer winding for very fast transient overvoltage studies , 1998 .

[49]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[50]  Shaun Lovejoy,et al.  Scale Invariance, Symmetries, Fractals, and Stochastic Simulations of Atmospheric Phenomena , 1986 .

[51]  C. Koley,et al.  SVM Classifier for Impulse Fault Identification in Transformers using Fractal Features , 2007, IEEE Transactions on Dielectrics and Electrical Insulation.

[52]  P. Purkait,et al.  Wavelet transform-based impulse fault pattern recognition in distribution transformers , 2003 .

[53]  P. Purkait,et al.  Impulse fault classification in transformers by fractal analysis , 2003 .

[54]  J. R. Meador,et al.  Impulse Testing of Power Transformers [includes discussion] , 1952, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.

[55]  P. Purkait,et al.  Time and frequency domain analyses based expert system for impulse fault diagnosis in transformers , 2002 .

[56]  A. De,et al.  Impulse fault diagnosis in power transformers using self-organising map and learning vector quantisation , 2001 .

[57]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[58]  S. Mallat.  VI – Wavelet zoom , 1999 .

[59]  S Chakravorti,et al.  Cross-correlation aided wavelet network for classification of dynamic insulation failures in transformer winding during impulse test , 2011, IEEE Transactions on Dielectrics and Electrical Insulation.

[60]  C. Koley,et al.  Wavelet-aided SVM tool for impulse fault identification in transformers , 2006, IEEE Transactions on Power Delivery.

[61]  Melani I. Plett,et al.  Transient Detection With Cross Wavelet Transforms and Wavelet Coherence , 2007, IEEE Transactions on Signal Processing.

[62]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[63]  José Edison Cabral,et al.  Fraud detection in electrical energy consumers using rough sets , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[64]  C. K. Roy,et al.  Studies on impulse behaviour of a transformer winding with simulated faults by analogue modelling , 1994 .

[65]  Giovanni Coco,et al.  A cross-wavelet study of alongshore nonuniform nearshore sandbar behavior , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[66]  Joseph Picone,et al.  Applications of support vector machines to speech recognition , 2004, IEEE Transactions on Signal Processing.