Research On Nonlinear Dynamic Characters In Partial Discharge

Partial discharge (PD) is one of the most important reasons causing high voltage electric equipment insulation degradation and breakdown, and the insulation states of equipments affect their safe and stable run in power system directly. So PD research is very important in electric power engineering. Deeply research on the nonlinear dynamic characters of PD signals can make us know PD phenomena more and better, also it is benefit to further optimizing on-line partial discharge monitoring system which can detect and diagnose fault in time and more precision. There is a great significance in the matter of equipment fault and accident prevention and maintenance of the power system security and economic operation.Chaos and Fractal theory is basic science which researches on commonness in nonlinear phenomena, and widely applied in many areas of engineering in recent years. This dissertation looked partial discharge phenomenon in insulation as a dynamic system, used chaos and fractal theory to research nonlinear dynamic characters included in PD signals time series. Based on lots of experiments and analysis, we get the conclusions: first it proved that partial discharge phenomena in insulation have nonlinear chaos characters, and then we analyzed the feasibility whether these chaos characters can be seemed as eigenvectors of PD Pattern Recognition; at last we improved the methods to extract partial discharge signals and suppress interference in PD detection. There are six chapters in this dissertation.The first chapter discussed the significance and situation of partial discharge investigation, and analyzed the problems existed in on-line partial discharge monitoring currently, moreover it pointed out it was necessary to research the mechanism of partial discharge.The second chapter described the method based on chaos theory, it emphasized on the calculational methods of nonlinear dynamic characters such as maximum Lyapunov exponent, fractal dimension and Kolmogorov entropy which applied for the further PD nonlinear dynamic research.The third chapter introduced the typical insulation PD experimental system.The fourth chapter analyzed the nonlinear dynamic characters of PD signals which detected in experiments. Obtained some important conclusions, for example PD signals time series had chaos characters and they can be used as eigenvectors to indicate insulation aging state.Chapter V analyzed the problem of interference suppression in transformer PD pulse-current detection method, according to the chaos characters of PD signals we improved the PD signal detection and interference suppression methods based on the Chaos Oscillator.Final chapter summarized whole dissertation, and brief described and looked forward to the unresolved questions and follow-up work. The works of this dissertation provide the reference to the evaluation of transformer insulation condition and life prediction, there is great practical significance to PD online monitoring and fault diagnosis.