Using multivariate statistical method to recognize different aging stages of oil-paper

The multivariate statistical method is introduced in this paper to diagnose insulation performance and identify its aging stages. Based on the lifetime model obtained by lifetime tests, a reasonable experimental condition is chosen to age several oil-paper samples for about 240 hours. Determination of partial discharge signal is carried out in the constant interval throughout the whole aging period. There are a total of 31 parameters extracted and 11 were found to be closely correlated to the aging stages and are used as aging characteristic parameters in the following analysis. In order to identify the proper aging conditions, the cluster method is used to analyze 30 vectors extracted from 6 samples at 5 different aging stages. It is shown that different samples have the similar performance at the same aging stage. The 30 vectors are used to obtain discriminant functions. The characteristic vector with eleven-dimensions is mapped to two-dimensions and the other 30 vectors are analyzed using discriminant functions. It is concluded that a reasonable result can be achieved using the discriminant functions.