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Reference: ISH2015_43

ISH Collection

Effect of Moisture on the Accuracy to Predict Failure Probability of Oil-paper Insulation Using Multiple Parameters



Lifetime prediction of transformer is a big issue in diagnostics and monitoring. In the previous study, we proposed a model to predict the failure probability of oil-immersed transformer in consideration of moisture contents. But the estimated results varied with initial moisture content, leading to complicated lifetime predictions. To simplify the prediction process, this paper built a prediction model considering multiple parameters except the initial moisture content. The DP value was chosen as the criterion of aging degree of transformer. The relationship between multiple parameters and DP value was discussed. Pearson test and spearman test were performed to testify whether diagnostic parameters have significant correlation with DP value. We used ordinary least square (OLS) estimation to build multiple regression model and then tested the homoskedasticity of the model by White test. The property of normality was testified by using the Kolmogorov–Smirnov test and Lilliefors test. The test results suggest that the regression model is valid. By comparing the real DP values and estimated DP, we concluded that the initial moisture doesn't have significant effect on prediction accuracy by using the regression model proposed in this paper. Furthermore, the failure probability of oil-immersed transformer was calculated through the diagnostics of chosen parameters.

File Size: 441,6 KB

Year: 2015

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