Nonlinear Analysis Of Resistance To Tracking Of Polymer Insulating Materials

The polymer insulating material has wide application in the modern electrical power system, but polymer insulating materials may be damaged by tracking .Tracking failure is dielectric breakdown phenomena on the surface of polymer materials. The tracking process can be divided into three steps: First the heat generated during the discharge process leads to carbon separating out of the polymer material to form carbon track on the surface. Second the density of carbon increases as the heat increases. Third in some cases, the carbon track finally forms conduction path and at one point there is sufficient energy for bonds to be broken.Tracking failure of polymer insulating material can menace safety of electronic devices. From the viewpoint of safety and reliability, the research of the tracking failure is very important. The common approach to evaluate the insulation performance of polymer materials is to work with the CTI value. However, the CTI values show wide variations. Due to the complex fluctuation in the tracking phenomena, there exists chaotic behavior in the discharge process. In this paper, the chaos method is used to analyze the behavior of discharge current.In this paper, chaos analysis of discharge current is presented based on tracking test of PL and PVC in accordance with IEC60112. According to characteristics of statistical self-similarity and complexity of the discharge current, the largest Lyapunov exponent is calculated, the Poincare map is reconstructed, which all produce the evidences that there exists chaotic behavior in the discharge current. On the basis of chaos theory, the attractors of discharge current and recurrence plots of different discharge states are reconstructed. The results indicate that the chaos attractors have different characteristics in evolutionary tracks, the topological structure and grain direction of recurrence plots show significant differences. The chaos attractor could describe the tracking process. The recurrence plot could identify the tracking state clearly, while its arithmetic is much simply. Based on the above analysis, it can be concluded that the chaos attractor and recurrence plot are successful ways to describe the tracking process.