Application of Time Domain Dielectric Spectral Characteristics in Quantitative Evaluation of Oil-paper Transformer Insulation Status

Previous studies have confirmed that the insulation status of oil-paper transformer can be qualitatively analyzed by its time domain dielectric spectral characteristics. However, it is more important to evaluate the insulation condition of transformers quantitatively in engineering practice. An evaluation system based on characteristics obtained by the return voltage measurements is constructed in this paper for the quantitative evaluation of the insulation state of oil-paper transformers. First, data of characteristics of transformer are normalized and neighborhood radius of each characteristic are calculated. Then, the decision table of oil-paper insulation diagnosis system is generated based on neighborhood rough set theory. Moreover, attribute reduction is carried out to the decision table and the best rules are extracted. Finally, the oil-paper insulation state evaluation system is constructed based on the historical database. Five transformers of known insulation status have verified the accuracy of the evaluation system.

[1]  Dun Liu,et al.  A fuzzy rough set approach for incremental feature selection on hybrid information systems , 2015, Fuzzy Sets Syst..

[2]  Stefan Wolny,et al.  Aging degree evaluation for paper-oil insulation using the recovery voltage method , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[3]  Hu Qing,et al.  Efficient Symbolic and Numerical Attribute Reduction with Neighborhood Rough Sets , 2008 .

[4]  Huang Yanjie.  Simulation of transformer insulation polarization spectrum , 2011 .

[5]  Zhou Tian-chun,et al.  Analysis of Oil-paper Insulation Aging Characteristics Using Recovery Voltage Method , 2011 .

[6]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[7]  Hossein Borsi,et al.  Diagnostic of insulation condition of oil impregnated paper insulation systems with return voltage measurements , 2003, 2003 Annual Report Conference on Electrical Insulation and Dielectric Phenomena.

[8]  Hu Qing,et al.  Numerical Attribute Reduction Based on Neighborhood Granulation and Rough Approximation , 2008 .

[9]  O. Kouzmine,et al.  Return Voltage Measurements - a good tool for the diagnosis of paper-oil insulations , 2005, 2005 IEEE Russia Power Tech.

[10]  Degang Chen,et al.  Attribute Reduction for Heterogeneous Data Based on the Combination of Classical and Fuzzy Rough Set Models , 2014, IEEE Transactions on Fuzzy Systems.

[11]  Huang Qinghua,et al.  Numerical Attribute Reduction Based on Neighborhood Granulation and Rough Approximation , 2008 .