An overview of state-of-the-art partial discharge analysis techniques for condition monitoring

IEEE Electrical Insulation Magazine

Volumn 31, Issue 6, 2015, Pages 22-35

  Wu, Min ^a   Cao, Hong ^a   Cao, Jianneng ^a   Nguyen, Hai Long ^a   Gomes, João Bártolo ^a   Krishnaswamy, Shonali Priyadarsini ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

condition monitoring; feature extraction; partial discharge; pattern recognition; sensor

Indexed keywords

ELECTRIC POWER TRANSMISSION NETWORKS; FEATURE EXTRACTION; OUTAGES; PARTIAL DISCHARGES; PATTERN RECOGNITION; SENSORS;

ELECTRICAL FAILURES; ELECTRICAL INSULATION FAILURE; KEY INDICATOR; MAINTENANCE COST; PARTIAL DISCHARGE ANALYSIS; POWER FAILURE; POWER GRIDS; STATE OF THE ART;

CONDITION MONITORING;

EID: 84946826810     PISSN: 08837554     EISSN: None     Source Type: Journal    
DOI: 10.1109/MEI.2015.7303259     Document Type: Article

References (80)

1. Y. Han and Y. Song, "Condition monitoring techniques for electrical equipment-A literature survey," IEEE Trans. Power Del., vol. 18, pp. 4-13, 2003.
2. G. Montanari and A. Cavallini, "Partial discharge diagnostics: From apparatus monitoring to smart grid assessment," IEEE Electr. Insul. Mag., vol. 29, pp. 8-17, 2013.
3. U. Fromm, "Partial discharge and breakdown testing at high DC voltage," PhD dissertation, Delft Univ. Technol., Delft, the Netherlands, 1995.
4. P. H. Morshuis and J. J. Smit, "Partial discharges at DC voltage: Their mechanism, detection and analysis," IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 328-340, 2005.
5. C. Hudon and M. Belec, "Partial discharge signal interpretation for generator diagnostics," IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 297-319, 2005.
6. K. Lai, B. Phung, and T. Blackburn, "Application of data mining on partial discharge Part I: Predictive modelling classification," IEEE Trans. Dielectr. Electr. Insul., vol. 17, pp. 846-854, 2010.
7. H. Ma, J. C. Chan, T. K. Saha, and C. Ekanayake, "Pattern recognition techniques and their applications for automatic classification of artificial partial discharge sources," IEEE Trans. Dielectr. Electr. Insul., vol. 20, pp. 468-478, 2013.
8. G. Montanari, A. Cavallini, and F. Puletti, "A new approach to partial discharge testing of HV cable systems," IEEE Electr. Insul. Mag., vol. 22, pp. 14-23, 2006.
9. G. Stone, "Partial discharge diagnostics and electrical equipment insulation condition assessment," IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 891-904, 2005.
10. M. D. Judd, L. Yang, and I. B. Hunter, "Partial discharge monitoring of power transformers using UHF sensors. Part I: Sensors and signal interpretation," IEEE Electr. Insul. Mag., vol. 21, pp. 5-14, 2005.
11. W. Gao, D. Ding, and W. Liu, "Research on the typical partial discharge using the UHF detection method for GIS," IEEE Trans. Power Del., vol. 26, pp. 2621-2629, 2011.
12. S. Birlasekaran and W. H. Leong, "Comparison of known PD signals with the developed and commercial HFCT sensors," IEEE Trans. Power Del., vol. 22, pp. 1581-1590, 2007.
13. G. Luo and D. Zhang, "Study on performance of HFCT and UHF sensors in partial discharge detection," in IEEE Int. Power Electron. Conf. (IPEC), 2010, pp. 630-635.
14. S. Markalous, S. Tenbohlen, and K. Feser, "Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals," IEEE Trans. Dielectr. Electr. Insul., vol. 15, pp. 1576-1583, 2008.
15. W. Si, J. Li, D. Li, J. Yang, and Y. Li, "Investigation of a comprehensive identification method used in acoustic detection system for GIS," IEEE Trans. Dielectr. Electr. Insul., vol. 17, pp. 721-732, 2010.
16. P. M. Eleftherion, "Partial discharge. XXI. Acoustic emission based PD source location in transformers," IEEE Electr. Insul. Mag., vol. 11, pp. 22-26, 1995.
17. J. Deng, H. Xiao, W. Huo, M. Luo, R. May, A. Wang, and Y. Liu, "Optical fiber sensor-based detection of partial discharges in power transformers," Optics Laser Technol., vol. 33, pp. 305-311, 2001.
18. M. MacAlpine, Z. Zhiqiang, and M. S. Demokan, "Development of a fibre-optic sensor for partial discharges in oil-filled power transformers," Electr. Power Syst. Res., vol. 63, pp. 27-36, 2002.
19. X. Wang, B. Li, H. T. Roman, O. L. Russo, K. Chin, and K. R. Farmer, "Acousto-optical PD detection for transformers," IEEE Trans. Power Del., vol. 21, pp. 1068-1073, 2006.
20. J. Posada-Roman, J. A. Garcia-Souto, and J. Rubio-Serrano, "Fiber optic sensor for acoustic detection of partial discharges in oil-paper insulated electrical systems," Sensors, vol. 12, pp. 4793-4802, 2012.
21. Z. Wang, I. Cotton, and S. Northcote, "Dissolved gas analysis of alternative fluids for power transformers," IEEE Electr. Insul. Mag., vol. 23, pp. 5-14, 2007.
22. S. Singh and M. Bandyopadhyay, "Dissolved gas analysis technique for incipient fault diagnosis in power transformers: A bibliographic survey," IEEE Electr. Insul. Mag., vol. 26, pp. 41-46, 2010.
23. N. Bakar, A. Abu-Siada, and S. Islam, "A review of dissolved gas analysis measurement and interpretation techniques," IEEE Electr. Insul. Mag., vol. 30, pp. 39-49, 2014.
24. M. Duval and A. DePabla, "Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases," IEEE Electr. Insul. Mag., vol. 17, pp. 31-41, 2001.
25. T. Pinpart and M. Judd, "Experimental comparison of UHF sensor types for PD location applications," in IEEE Electr. Insul. Conf. (EIC), 2009, pp. 26-30.
26. H. Sinaga, B. Phung, and T. Blackburn, "Partial discharge localization in transformers using UHF detection method," IEEE Trans. Dielectr. Electr. Insul., vol. 19, pp. 1891-1900, 2012.
27. S. M. Markalous, S. Tenbohlen, and K. Feser, "New robust non-iterative algorithms for acoustic PD-localization in oil/paper-insulated transformers," in 14th Int. Symp. High Volt. Eng., 2005, pp. 29-34.
28. W. Zheng, Y. Qian, N. Yang, C. Huang, and X. Jiang, "Research on partial discharge localization in XLPE cable accessories using multi-sensor joint detection technology," Przegla{ogonek}d Elektrotechniczny, vol. 87, pp. 281-284, 2011.
29. Y. Tian, P. Lewin, and A. Davies, "Comparison of on-line partial discharge detection methods for HV cable joints," IEEE Trans. Dielectr. Electr. Insul., vol. 9, pp. 604-615, 2002.
30. L. Hao, P. Lewin, and S. Dodd, "Comparison of support vector machine based partial discharge identification parameters," in IEEE Int. Symp. Electr. Insul. (ISEI), 2006, pp. 110-113.
31. L. Hao and P. Lewin, "Partial discharge source discrimination using a support vector machine," IEEE Trans. Dielectr. Electr. Insul., vol. 17, pp. 189-197, 2010.
32. N. Sahoo, M. Salama, and R. Bartnikas, "Trends in partial discharge pattern classification: A survey," IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 248-264, 2005.
33. E. Gulski and A. Krivda, "Neural networks as a tool for recognition of partial discharges," IEEE Trans. Electr. Insul., vol. 28, pp. 984-1001, 1993.
34. R. Candela, G. Mirelli, and R. Schifani, "PD recognition by means of statistical and fractal parameters and a neural network," IEEE Trans. Dielectr. Electr. Insul., vol. 7, pp. 87-94, 2000.
35. L. Hao, P. Lewin, J. Hunter, D. Swaffield, A. Contin, C. Walton, and M. Michel, "Discrimination of multiple PD sources using wavelet decomposition and principal component analysis," IEEE Trans. Dielectr. Electr. Insul., vol. 18, pp. 1702-1711, 2011.
36. C. Chang, J. Jin, C. Chang, T. Hoshino, M. Hanai, and N. Kobayashi, "Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations," IEEE Trans. Power Del., vol. 20, pp. 1363-1369, 2005.
37. D. Evagorou, A. Kyprianou, P. Lewin, A. Stavrou, V. Efthymiou, A. Metaxas, and G. E. Georghiou, "Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network," IET Sci., Meas. Technol., vol. 4, pp. 177-192, 2010.
38. I. Jolliffe, "Principal component analysis," in Encyclopedia of Statistics in Behavioral Science, B. S. Everitt and D. Howell, Ed. Wiley Online Library: John Wiley & Sons Ltd, 2005.
39. R. Liao, Y. Fernandess, K. Tavernier, G. Taylor, and M. Irving, "Recognition of partial discharge patterns," in IEEE Power Ener. Soc. Gen. Meet., 2012, pp. 1-8.
40. T. Babnik, R. K. Aggarwal, and P. J. Moore, "Principal component and hierarchical cluster analyses as applied to transformer partial discharge data with particular reference to transformer condition monitoring," IEEE Trans. Power Del., vol. 23, pp. 2008-2016, 2008.
41. K. Lai, B. Phung, T. Blackburn, and N. Muhamad, "Classification of partial discharge using PCA and SOM," in Int. Power Eng. Conf. (IPEC), 2007, pp. 1311-1316.
42. L. Van der Maaten and G. Hinton, "Visualizing data using t-SNE," J. Mach. Learn. Res., vol. 9, pp. 2579-2605, 2008.
43. P. Lewin, L. Petrov, and L. Hao, "A feature based method for partial discharge source classification," in IEEE Int. Symp. Electr. Insul. (ISEI), 2012, pp. 443-448.
44. V. Chatpattananan, N. Pattanadech, and P. Yutthagowith, "Partial discharge classification on high voltage equipment with K-means," in 8th Int. Conf. Prop. Appl. Dielectr. Mater., 2006, pp. 191-194.
45. Y. H. Lin, "Using K-means clustering and parameter weighting for partial-discharge noise suppression," IEEE Trans. Power Del., vol. 26, pp. 2380-2390, 2011.
46. R. Sharkawy, R. Mangoubi, T. Abdel-Galil, M. Salama, and R. Bartnikas, "SVM classification of contaminating particles in liquid dielectrics using higher order statistics of electrical and acoustic PD measurements," IEEE Trans. Dielectr. Electr. Insul., vol. 14, pp. 669-678, 2007.
47. T. Abdel-Galil, R. Sharkawy, M. Salama, and R. Bartnikas, "Partial discharge pulse pattern recognition using an inductive inference algorithm," IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 320-327, 2005.
48. T. Abdel-Galil, R. Sharkawy, M. M. Salama, and R. Bartnikas, "Partial discharge pattern classification using the fuzzy decision tree approach," IEEE Trans. Inst. Meas., vol. 54, pp. 2258-2263, 2005.
49. R. Liao, L. Yang, J. Li, and S. Grzybowski, "Aging condition assessment of transformer oil-paper insulation model based on partial discharge analysis," IEEE Trans. Dielectr. Electr. Insul., vol. 18, pp. 303-311, 2011.
50. S. Poyhonen, M. Conti, A. Cavallini, G. C. Montanari, and F. Filippetti, "Insulation defect localization through partial discharge measurements and numerical classification," in IEEE Int. Symp. Ind. Electron., 2004, pp. 417-422.
51. J. Li, R. Liao, S. Grzybowski, and L. Yang, "Oil-paper aging evaluation by fuzzy clustering and factor analysis to statistical parameters of partial discharges," IEEE Trans. Dielectr. Electr. Insul., vol. 17, pp. 756-763, 2010.
52. V. P. Darabad, M. Vakilian, T. Blackburn, and B. Phung, "Data mining on partial discharge signals of power transformer's defect models," Int. Trans. Electr. Energy Syst., vol. 23, pp. 423-437, 2013.
53. J. Hunter, L. Hao, P. Lewin, C. Walton, and M. Michel, "Partial discharge diagnostics of defective medium voltage three-phase PILC cables," in IEEE Int. Symp. Electr. Insul. (ISEI), 2012, pp. 371-375.
54. A. Contin and S. Pastore, "Classification and separation of partial discharge signals by means of their auto-correlation function evaluation," IEEE Trans. Dielectr. Electr. Insul., vol. 16, pp. 1609-1622, 2009.
55. X. Peng, C. Zhou, D. M. Hepburn, M. D. Judd, and W. Siew, "Application of K-Means method to pattern recognition in on-line cable partial discharge monitoring," IEEE Trans. Dielectr. Electr. Insul., vol. 20, pp. 754-761, 2013.
56. J. C. Bezdek, R. Ehrlich, and W. Full, "FCM: The fuzzy c-means clustering algorithm," Comp. Geosci., vol. 10, pp. 191-203, 1984.
57. A. Contin, A. Cavallini, G. Montanari, G. Pasini, and F. Puletti, "Digital detection and fuzzy classification of partial discharge signals," IEEE Trans. Dielectr. Electr. Insul., vol. 9, pp. 335-348, 2002.
58. W. Si, J. Li, P. Yuan, and Y. Li, "Digital detection, grouping and classification of partial discharge signals at DC voltage," IEEE Trans. Dielectr. Electr. Insul., vol. 15, pp. 1663-1674, 2008.
59. M. Ester, H. P. Kriegel, J. Sander, and X. Xu, "A density-based algorithm for discovering clusters in large spatial databases with noise," in ACM Conf. Knowl. Disc. Data Mining (KDD), 1996, pp. 226-231.
60. A. Contin and S. Pastore, "Automatic separation of multiple PD sources using an Amplitude-AutoCorrelation Relation Diagram," in IEEE Int. Symp. Electr. Insul. (ISEI), 2012, pp. 434-438.
61. M. E. Newman, "Modularity and community structure in networks," Proc. Natl. Acad. Sci. (PNAS), vol. 103, pp. 8577-8582, 2006.
62. Y. Yang and K. Chen, "Temporal data clustering via weighted clustering ensemble with different representations," IEEE Trans. Knowl. Data Eng., vol. 23, pp. 307-320, 2011.
63. S. Vega-Pons and J. Ruiz-Shulcloper, "A survey of clustering ensemble algorithms," Int. J. Pattern Recog. Art. Intel., vol. 25, pp. 337-372, 2011.
64. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. New York, NY: Cambridge University Press, 2000.
65. P. N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining. Addison-Wesley, 2005.
66. M. Danikas, N. Gao, and M. Aro, "Partial discharge recognition using neural networks: A review," Electr. Eng., vol. 85, pp. 87-93, 2003.
67. A. R. G. Castro and V. Miranda, "Knowledge discovery in neural networks with application to transformer failure diagnosis," IEEE Trans. Power Syst., vol. 20, pp. 717-724, 2005.
68. M. H. Wang, "Partial discharge pattern recognition of current transformers using an ENN," IEEE Trans. Power Del., vol. 20, pp. 1984-1990, 2005.
69. T. Boczar, S. Borucki, A. Cichon, and D. Zmarzly, "Application possibilities of artificial neural networks for recognizing partial discharges measured by the acoustic emission method," IEEE Trans. Dielectr. Electr. Insul., vol. 16, pp. 214-223, 2009.
70. V. Miranda and A. R. G. Castro, "Improving the IEC table for transformer failure diagnosis with knowledge extraction from neural networks," IEEE Trans. Power Del., vol. 20, pp. 2509-2516, 2005.
71. A. Yazdandoust, F. Haghjoo, and S. Shahrtash, "Insulation status assessment in high voltage cables based on decision tree algorithm," in IEEE Canada Electr. Power Conf., 2008, pp. 1-5.
72. H. Hirose, M. Hikita, S. Ohtsuka, S. Tsuru, and J. Ichimaru, "Diagnosis of electric power apparatus using the decision tree method," IEEE Trans. Dielectr. Electr. Insul., vol. 15, pp. 1252-1260, 2008.
73. K. Lai, B. Phung, and T. Blackburn, "Descriptive data mining of partial discharge using decision tree with genetic algorithm," in Australasian Univ. Power Eng. Conf. (AUPEC), 2008, pp. 1-6.
74. X. Chen, H. Cui, and L. Luo, "Fault diagnosis of transformer based on random forest," in Int. Conf. Intel. Comp. Technol. Automat. (ICICTA), 2011, pp. 132-134.
75. W. Tang, K. Spurgeon, Q. Wu, and Z. Richardson, "An evidential reasoning approach to transformer condition assessments," IEEE Trans. Power Del., vol. 19, pp. 1696-1703, 2004.
76. R. Liao, H. Zheng, S. Grzybowski, L. Yang, Y. Zhang, and Y. Liao, "An integrated decision-making model for condition assessment of power transformers using fuzzy approach and evidential reasoning," IEEE Trans. Power Del., vol. 26, pp. 1111-1118, 2011.
77. T. Jiang, J. Li, Y. Zheng, and C. Sun, "Improved bagging algorithm for pattern recognition in UHF signals of partial discharges," Energies, vol. 4, pp. 1087-1101, 2011.
78. G. Hinton, S. Osindero, and Y. W. Teh, "A fast learning algorithm for deep belief nets," Neural Comput., vol. 18, pp. 1527-1554, 2006.
79. M. M. Gaber, A. Zaslavsky, and S. Krishnaswamy, "Mining data streams: A review," ACM Sigmod Rec., vol. 34, pp. 18-26, 2005.
80. K. Shim, "MapReduce algorithms for big data analysis," Proc. VLDB Endow., vol. 5, pp. 2016-2017, 2012.