Insulation Condition Assessment of Power Transformers Employing Fused Information in Time and Space Dimensions

References

• R. Liao et al., “Extraction of frequency domain dielectric characteristic parameter of oil-paper insulation for transformer condition assessment,” Electric Power Compon. Syst., vol. 43, no. 5, pp. 578–587, 2015. DOI: 10.1080/15325008.2014.989377.
   Web of Science ®Google Scholar
• W. H. Tang, J. Y. Goulermas, Q. H. Wu, Z. J. Richardson, and J. Fitch, “A probabilistic classifier for transformer dissolved gas analysis with a particle swarm optimizer,” IEEE Trans. Power Deliv., vol. 23, no. 2, pp. 751–759, April 2008. DOI: 10.1109/TPWRD.2008.915812.
   Web of Science ®Google Scholar
• J. Faiz and M. Soleimani, “Assessment of computational intelligence and conventional dissolved gas analysis methods for transformer fault diagnosis,” IEEE Trans. Dielectric. Electric. Insul., vol. 25, no. 5, pp. 1798–1806, 2018. DOI: 10.1109/TDEI.2018.007191.
   Web of Science ®Google Scholar
• O. E. Gouda, S. H. El-Hoshy, and H. H. El-Tamaly, “Proposed heptagon graph for DGA interpretation of oil transformers,” IET Gener. Transm. Distrib., vol. 12, no. 2, pp. 490–498, 2018. DOI: 10.1049/iet-gtd.2017.0826.
   Web of Science ®Google Scholar
• K. Bacha, S. Souahlia, and M. Gossa, “Power transformer fault diagnosis based on dissolved gas analysis by support vector machine,” Electric Power Syst. Res., vol. 83, no. 1, pp. 73–79, 2012. DOI: 10.1016/j.epsr.2011.09.012.
   Web of Science ®Google Scholar
• A. D. Ashkezari, H. Ma, T. K. Saha, and Y. Cui, “Investigation of feature selection techniques for improving efficiency of power transformer condition assessment,” IEEE Trans. Dielectric. Electric. Insul., vol. 21, no. 2, pp. 836–844, 2014. DOI: 10.1109/TDEI.2013.004090.
   Web of Science ®Google Scholar
• H. Zeinoddini-Meymand and B. Vahidi, “Techno-economical lifetime assessment of power transformers rated over 50 MVA using artificial intelligence models,” IET Gener. Transm. Distrib., vol. 10, no. 15, pp. 3885–3892, 2016. DOI: 10.1049/iet-gtd.2016.0480.
   Web of Science ®Google Scholar
• M. M. Islam, G. Lee, and S. N. Hettiwatte, “Application of a general regression neural network for health index calculation of power transformers,” Int. J. Electric. Power Energy Syst., vol. 93, pp. 308–315, 2017. DOI: 10.1016/j.ijepes.2017.06.008.
   Web of Science ®Google Scholar
• R. Liao, Y. Zhang, L. Yang, H. Zheng, and X. She, “A cloud and evidential reasoning integrated model for insulation condition assessment of high voltage transformers,” Int. Trans. Electric. Energy Syst., vol. 24, no. 7, pp. 913–926, 2014. DOI: 10.1002/etep.1738.
   Web of Science ®Google Scholar
• S. Ying, G. He, L. Kejun, and L. Yongliang, “Condition assessment model of distribution transformer based on multi-period information fusion,” High Voltage Eng., vol. 42, no. 7, pp. 2054–2062, 2016.
   Google Scholar
• G. K. Irungu, A. O. Akumu, and J. L. Munda, “Application of fuzzy logic and evidential reasoning methodologies in transformer insulation stress assessment,” IEEE Trans. Dielectric. Electric. Insul., vol. 23, no. 3, Suppl, pp. 1444–1452, 2016. DOI: 10.1109/TDEI.2015.005560.
   Web of Science ®Google Scholar
• M. Arshad, S. M. Islam, and A. Khaliq, “Fuzzy Logic Approach in Power Transformers Management and Decision Making,” IEEE Trans. Dielectric. Electric. Insul., vol. 21, no. 5, pp. 2343–2354, 2014. DOI: 10.1109/TDEI.2014.003859.
   Web of Science ®Google Scholar
• L. Sun et al., “Research on multi-attribute decision-making in condition evaluation for power transformer using fuzzy AHP and modified weighted averaging combination,” IET Gener. Transm. Distrib., vol. 10, no. 15, pp. 3855–3864, 2016. DOI: 10.1049/iet-gtd.2016.0381.
   Web of Science ®Google Scholar
• C. Ranga, A. K. Chandel, and R. Chandel, “Condition assessment of power transformers based on multi-attributes using fuzzy logic,” IET Sci. Meas. Technol., vol. 11, no. 8, pp. 983–990, 2017. DOI: 10.1049/iet-smt.2016.0497.
   Web of Science ®Google Scholar
• F. Tian, Z. Jing, H. Zhao, E. Zhang, and J. Liu, “A synthetic condition assessment model for power transformers using the fuzzy evidence fusion method,” Energies, vol. 12, no. 5, pp. 857, 2019. DOI: 10.3390/en12050857.
   Web of Science ®Google Scholar
• W. Gao, C. Bai, and T. Liu, “A dynamic integrated fault diagnosis method for power transformers,” Scientific World J., vol. 2015, pp. 1–526, 2015.
   Google Scholar
• A. Akbari, A. Setayeshmehr, H. Borsi, E. Gockenbach, and I. Fofana, “Intelligent agent-based system using dissolved gas analysis to detect incipient faults in power transformers,” IEEE Electric. Insul. Mag., vol. 26, no. 6, pp. 27–40, November 2010. DOI: 10.1109/MEI.2010.5599977.
   Web of Science ®Google Scholar
• X. Mao, Y. Wu, Y. Shen, X. Peng, and Y. Sun, “Study on the plan of uhv substation location based on grey comprehensive optimal selection using moment estimation theory to weight,” presented at the 2012 IEEE International Conference on Power System Technology (POWERCON), Auckland, New Zealand, Oct 2012, pp. 1–6. DOI: 10.1109/PowerCon.2012.6401308.
   Google Scholar
• L. Li et al., “An integrated method of set pair analysis and association rule for fault diagnosis of power transformers,” IEEE Trans. Dielectric. Electric. Insul., vol. 22, no. 4, pp. 2368–2378, August 2015. DOI: 10.1109/TDEI.2015.004855.
   Web of Science ®Google Scholar
• M. Pinto, “A grounded theory on abstracts quality: Weighting variables and attributes,” Scientometrics, vol. 69, no. 2, pp. 213–226, 2006. DOI: 10.1007/s11192-006-0150-9.
   Web of Science ®Google Scholar
• R. Feng, X. Xu, X. Zhou, and J. Wan, “A trust evaluation algorithm for wireless sensor networks based on node behaviors and ds evidence theory,” Sensors, vol. 11, no. 2, pp. 1345–1360, 2011. DOI: 10.3390/s110201345.
   PubMed Web of Science ®Google Scholar
• W. Tang, K. Spurgeon, Q. Wu, and Z. Richardson, “An evidential reasoning approach to transformer condition assessments,” IEEE Trans. Power Deliv., vol. 19, no. 4, pp. 1696–1703, 2004. DOI: 10.1109/TPWRD.2003.822542.
   Web of Science ®Google Scholar
• R. Liao et al., “An integrated decision-making model for condition assessment of power transformers using fuzzy approach and evidential reasoning,” IEEE Trans. Power Deliv., vol. 26, no. 2, pp. 1111–1118, 2011. DOI: 10.1109/TPWRD.2010.2096482.
   Web of Science ®Google Scholar