Fault Prediction of Power Transformer by Combination of Rough Sets and Grey Theory
FEI Sheng-wei, SUN Yu (School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, Jiangsu Province, China)
A new transformer fault prediction method based on rough sets and grey theory was presented. The improved three-ratio attribute decision table was constructed and simplified by the knowledge acquisition method based on rough sets, and the minimal rules were obtained. Then, the prediction models of three ratios in decision table were constructed respectively. The ratios of feature gases could be predicted by grey model and their future state feature was obtained. According to the minimal rules, the incipient failure could be predicted, and its probability was acquired by combination rules’ credibility with the number of the failure acquired from predicted feature of gases’ ratios. The method can detect incipient failure early and correctly by combination predicted future state feature of gases’ ratios with minimal rules. According to predicted incipient failure, pertinent repair can be done early. Finally, the effectiveness and correctness of this method were validated by the result of fault prediction examples.
【CateGory Index】： TM41