Modelling and Prediction of Oil Monitoring Data for Power System Based on Grey Theory

In order to realize the modeling and prediction of oil monitoring parameters for unequal interval sampling of equipment power system, an improved two-step non-equidistance GM (1,1) modeling method is studied. This method is not only suitable for high growth sequence, but also has high model accuracy. Based on this method, the grey prediction model of oil wear particle number is established, and the prediction accuracy is compared with that of the non-equidistance modeling accuracy of data transformation method. The results show that the former has higher accuracy and is more suitable for the short-term prediction of oil wear particle number trend.