UHF PD Experiments on Real Power Transformer and its Frequency Characteristics Results
Abstract
A number of methods have been used in partial discharge (PD) detection and recognition. Among these methods, ultra-high frequency (UHF) detection and recognition based on a single signal have attracted much attention. In this paper, a UHF PD detection system is built, and samples are acquired through experiments on a real power transformer. The received signal is decomposed into different frequency ranges through wavelet packet decomposition (WPD). In each frequency range, a pattern recognition neural network is built, and then the relationship between the information in that frequency range and PD type is described. By comparing the recognition accuracy of these networks, frequency range selection is optimized. In this specific case (the specific transformer, PD sources, and UHF sensors), results show that low frequency (156.25 MHz to 312.5 MHz) and high frequency ranges (1093.75 MHz to 1250 MHz) contain the most information for recognition. If a PD detection recognition system is to be designed, then the performance around these frequency ranges should be given attention.
Keywords:
partial discharge, wavelet transform, neural networkDownloads
References
E. Lemke, P. Schmiegel, Introduction to fundamentals of PD diagnostics, Lemke Diagnostics GmbH, Germany, 2000
R. Bartnikas, “Partial discharges. Their mechanism, detection and measurement”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 9, No. 5, pp. 763-808, 2002 DOI: https://doi.org/10.1109/TDEI.2002.1038663
B. F. Hampton, R. J. Meats, “Diagnostic measurements at UHF in gas insulated substations”, IEE Proceedings C on Generation, Transmission and Distribution, Vol. 135. No. 2, pp. 137-145, 1988 DOI: https://doi.org/10.1049/ip-c.1988.0017
J. Pearson, J., B. F. Hampton, M. D. Judd, B. Pryor, P. F. Coventry, “Experience with advanced in-service condition monitoring techniques for GIS and transformers”, IEE Colloquium on HV Measurement, Condition Monitoring and Associated Database Handling Strategies, London, UK, 3 June 1998, pp. 8-8, 1998 DOI: https://doi.org/10.1049/ic:19980722
K. Raja, T. Floribert, “Comparative investigations on UHF and acoustic PD detection sensitivity in transformers”, Conference Record of the 2002 IEEE International Symposium, Boston, MA, USA, pp. 150-153, 7-10 April, 2002
M. D. Judd, L. Yang, I. B. B. Hunter, “Partial discharge monitoring of power transformers using UHF sensors. Part 2: Field Experience”, IEEE Electrical Insulation Magazine, Vol. 21, No. 3, pp. 5-13, 2005 DOI: https://doi.org/10.1109/MEI.2005.1437603
H. R. Mirzaei, A. Akbari, E. Gockenbach, K. Miralikhani, “Advancing new techniques for UHF PD detection and localization in the power transformers in the factory tests”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 1, pp. 448-455, 2015 DOI: https://doi.org/10.1109/TDEI.2014.004249
H. Suzuki, T. Endoh, “Pattern recognition of partial discharge in XLPE cables using a neural network”, Proceedings of the 3rd International Conference on Properties and Applications of Dielectric Materials, Tokyo, Japan, pp. 43-48, 8-12 July, 1991
Z. M. Li, Y. P. Feng, J. Q. Chen, X. Z. Zhang, “UHF partial discharge monitoring in GIS and signal processing”, Proceedings of 1998 International Symposium on.Electrical Insulating Materials, Toyohashi, Japan, pp. 67-70, 27-30 September, 1998
L. Yang, M. D. Judd, “Recognising multiple partial discharge sources in power transformers by wavelet analysis of UHF signals”, IEE Proceedings-Science, Measurement and Technology, Vol. 150, No. 3 pp. 119-127, 2003 DOI: https://doi.org/10.1049/ip-smt:20030201
Y. Wang, J. Wu, Z. Li, Y. Yin, “Research on a practical de-noising method and the characterization of partial discharge UHF signals”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 21, No. 5, pp. 2206-2216, 2014 DOI: https://doi.org/10.1109/TDEI.2014.004187
K. Wang, J. Li, S. Zhang, R. Liao, “A hybrid algorithm based on s transform and affinity propagation clustering for separation of two simultaneously artificial partial discharge sources”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 2, pp. 1042-1060, 2015 DOI: https://doi.org/10.1109/TDEI.2015.7076806
H. H. Sinaga, B. T. Phung, T. R. Blackburn, “Recognition of single and multiple partial discharge sources in transformers based on ultra-high frequency signals”, IET Generation, Transmission & Distribution Vol. 8, No. 1, pp. 160-169, 2014 DOI: https://doi.org/10.1049/iet-gtd.2013.0131
W. Gao, D. Zhao, D. Ding, S. Yao, “Investigation of frequency characteristics of typical PD and the propagation properties in GIS”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 3, pp. 1654-1662, 2015 DOI: https://doi.org/10.1109/TDEI.2015.7116362
L. Yang, M. D. Judd, C. J. Bennoch, “Denoising UHF signal for PD detection in transformers based on wavelet technique”, Annual report on Electrical Insulation and Dielectric Phenomena (CEIDP), pp. 166-169, 17-20 October , 2004
S. Sagar, J.Raghunath, J. Amarnath, S. Narasimham, “Wavelet Transform Technique for Denoising of UHF PD Signals in GIS”, Third International Conference on Industrial and Information Systems (ICIIS 2008), pp. 1-4, Kharagpur, India, 8-10 December, 2008 DOI: https://doi.org/10.1109/ICIINFS.2008.4798458
S. McCulloch, S. Warren, W. Pitts, “A logical calculus of the ideas immanent in nervous activity”, The Bulletin of Mathematical Biophysics, Vol. 5, No. 4, pp. 115-133, 1943 DOI: https://doi.org/10.1007/BF02478259
I. Portugues, P. J. Moore, I. A. Glover, “The effect of multipath in time domain characterization of partial discharges”, Proceedings of the 7th International Conference on. Properties and Applications of Dielectric Materials, Vol. 1, pp. 311-314, 2003
Z. Zheng, K. Tan, “Comparison of feature extraction methods in partial discharge waveform recognition”, Annual Report Conference on Electrical Insulation and Dielectric Phenomena, USA, 14-17 October, 2001
S. Markalous, S. Tenbohlen, K. Feser, “Detection and Location of Partial Discharges in Power Transformers using acoustic and electromagnetic signals”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 15, No. 6, pp. 1576-1583, 2008 DOI: https://doi.org/10.1109/TDEI.2008.4712660
C. U. Grosse, H. Reinhardt, “Schallemissionsquellen automatisch lokalisieren: Entwicklung eines Algorithmus”, Materialprüfung, Vol. 41, No. 9, pp. 342-347, 1999
J. W. Cooley, J. W. Tukey, “An algorithm for the machine calculation of complex Fourier series”, Mathematics of Computation, Vol. 19, No. 90, pp. 297-301, 1965 DOI: https://doi.org/10.1090/S0025-5718-1965-0178586-1
Y. Wang, C. Zhu, Q. Wang, Z. Wang, Y. Yin, “Processing of partial discharge ultra-high frequency signals from a true size transformer”, 2013 IEEE International Conference on Solid Dielectrics (ICSD), Bologna, Italy, pp. 1012-1015, 30 June – 4 July 2013 DOI: https://doi.org/10.1109/ICSD.2013.6619659
X. Zhao, Y. H. Cheng, Y. -P. Meng, M. G. Danikas, “Applying WPD and SVD to classification of EM wave induced by partial discharge in power transformer”, Journal of Electrical Engineering, Vol. 64, No. 4, pp. 222-229, 2013 DOI: https://doi.org/10.2478/jee-2013-0032
R. Sarathi, P. D. Singh, M. G. Danikas, “Characterization of partial discharges in transformer oil insulation under AC and DC voltage using Acoustic Emission Technique”, Journal of Electrical Engineering, Vol. 58, No. 2, pp. 91-97, 2007
Downloads
How to Cite
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
