Diagnosis of HV capacitive insulators by Partial Discharge measurements

Partial Discharges (PD) measurements are generally considered as a tool to detect defects in the insulation of HV components, that otherwise would be subjected to a high failure probability. In recent years, a pursued goal has been not only the identification of defects but also the separation of multiple defects simultaneously active in the measured HV bushing insulators. In this paper a novel defects separation and identification method is presented. Starting from PD data detected on different families of HV insulator with some different type of defect, the method aims at the separation of the PD data coming from the different source and at the evaluation of a suitable set of parameters to be used as input variables for a neural network able to identify the probable defect inside the insulation. In this aim, after the initial procedure of separation of the discharges by means of a new algorithm based on an evolutionary strategy, the statistical Weibull analysis is performed on PD pulse amplitude histograms to obtain the scale parameter a and the shape parameter β. Then, two fractal parameters (fractal dimension and lacunarity) and two statistical operators (Skewness and Kurtosis) are evaluated from the PD phase histogram and from the 3-dimension histogram respectively. After the exposition of the basic mathematical concepts regarding the separation method and the validity of the above parameters, experimental results are reported on the performance of the identification method. In particular it is showed how is possible to define the defect category in some 15 kV and 25 kV epoxy bushing insulators and the related comment are put forward