Location prediction model of zero value insulator based on PNN

Zero insulators directly reduce the electrical performance of insulator strings, affecting the safe and reliable operation of transmission lines. The grounding current of the insulator string contains the characteristic information of insulator electrical performance. Extracting the characteristic information of grounding current can realize the detection of zero value insulator, which is of great significance to ensure the safe operation of transmission lines. In this paper, the composite insulator used on ultra high voltage (UHV) lines is studied to analyze the influence of zero insulators on the electric field distribution. Furthermore, the corresponding characteristics of the zero insulators at different locations are extracted. The fitting relationship between the characteristic quantity and the zero-insulator position is analyzed. The effective characteristics of grounding current are selected as training sample to establish the zero-insulator position prediction model based on probabilistic neural network (PNN). The research result is meaningful for the detection of zero insulators.