Feasibility Study on Simultaneous Detection of Partial Discharge and Axial Displacement of HV Transformer Winding Using Electromagnetic Waves

Recently, axial displacement detection of transformer winding has been performed using synthetic-aperture radar (SAR) imaging, as an online method, in ultra-wideband frequency band. Another important problem in power transformers is partial discharge (PD), which emits signal in the ultra-high-frequency (UHF) frequency band. If detection of axial displacement using SAR imaging can be applied to the UHF band, both defects can be detected using only one set of antennas and application of these methods can be more economic. However, as shown in this paper, using the same frequency band for detection of both defects leads to wrong conclusions about winding conditions, if PD is occurred during the application of SAR imaging. As a solution, UHF stepped-frequency imaging method and generalized likelihood ratio test method are proposed for detection of axial displacement. Finally, on a three-phase real transformer both defects are simultaneously detected using designed monitoring system.

[1]  Saeed Gazor,et al.  Invariant tests for rapid-fluctuating radar signal detection with unknown arrival time , 2007, Signal Process..

[2]  M. S. Naderi,et al.  Three-dimensional simulation of PD source allocation through TDOA method , 2012, The 4th Conference on Thermal Power Plants.

[3]  Gholamreza Moradi,et al.  Online monitoring of transformer winding axial displacement and its extent using scattering parameters and k-nearest neighbour method , 2011 .

[4]  Junhao Li,et al.  Partial discharge characteristics over differently aged oil/pressboard interfaces , 2009, IEEE Transactions on Dielectrics and Electrical Insulation.

[5]  G. B. Gharehpetian,et al.  ANN and cross-correlation based features for discrimination between electrical and mechanical defects and their localization in transformer winding , 2014, IEEE Transactions on Dielectrics and Electrical Insulation.

[6]  G. B. Gharehpetian,et al.  A Feasibility Study on the Application of Radar Imaging for the Detection of Transformer Winding Radial Deformation , 2012, IEEE Transactions on Power Delivery.

[7]  Gevork B. Gharehpetian,et al.  Determination of transformer HV winding axial displacement occurrence, direction, and extent using time‐domain analysis of UWB signals , 2018, IET Science, Measurement & Technology.

[8]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[9]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[10]  Hamid Sheikhzadeh,et al.  Detection of Winding Radial Deformation in Power Transformers by Confocal Microwave Imaging , 2014 .

[11]  Yasser Abdel-Rady I. Mohamed,et al.  Experimental Studies on Monitoring and Metering of Radial Deformations on Transformer HV Winding Using Image Processing and UWB Transceivers , 2015, IEEE Transactions on Industrial Informatics.

[12]  S. Esmaeili,et al.  Discrimination Between Radial Deformation and Axial Displacement in Power Transformers Using Analysis of Electromagnetic Waves , 2017, IEEE Sensors Journal.

[13]  D. Rajan.  Probability, Random Variables, and Stochastic Processes , 2017 .

[14]  Kamal Sarabandi,et al.  Refocusing Through Building Walls Using Synthetic Aperture Radar , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Gevork B. Gharehpetian,et al.  Application of Classifiers for On-line Monitoring of Transformer Winding Axial Displacement by Electromagnetic Non-destructive Testing , 2011 .

[16]  Narayan C. Kar,et al.  Expectation-Maximization Particle-Filter- and Kalman-Filter-Based Permanent Magnet Temperature Estimation for PMSM Condition Monitoring Using High-Frequency Signal Injection , 2017, IEEE Transactions on Industrial Informatics.

[17]  Gevork B. Gharehpetian,et al.  Determination of Transformer Winding Radial Deformation Using UWB System and Hyperboloid Method , 2015, IEEE Sensors Journal.

[18]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[19]  Gholamreza Moradi,et al.  A new on-line monitoring method of transformer winding axial displacement based on measurement of scattering parameters and decision tree , 2011, Expert Syst. Appl..

[20]  Gevork B. Gharehpetian,et al.  Application of Characteristic Impedance and Wavelet Coherence Technique to Discriminate Mechanical Defects of Transformer Winding , 2013 .

[21]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[22]  Gevork B. Gharehpetian,et al.  GLRT-Based Mitigation of Partial Discharge Effect on Detection of Radial Deformation of Transformer HV Winding Using SAR Imaging Method , 2016, IEEE Sensors Journal.

[23]  E. Gockenbach,et al.  A novel method for ultra-high-frequency partial discharge localization in power transformers using the particle swarm optimization algorithm , 2013, IEEE Electrical Insulation Magazine.

[24]  Jianwei Yang,et al.  Feature Trend Extraction and Adaptive Density Peaks Search for Intelligent Fault Diagnosis of Machines , 2019, IEEE Transactions on Industrial Informatics.

[25]  E. Gockenbach,et al.  Advancing new techniques for UHF PDdetection and localization in the power transformers in the factory tests , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

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

[27]  G. B. Gharehpetian,et al.  A simultaneous method for detection of radial deformation and axial displacement in transformer winding using UWB SAR imaging , 2012, The 4th Conference on Thermal Power Plants.

[28]  Gevork B. Gharehpetian,et al.  Detection of HV Winding Radial Deformation and PD in Power Transformer Using Stepped-Frequency Hyperboloid Method , 2019, IEEE Transactions on Instrumentation and Measurement.