Study of Temperature Distribution Along an Artificially Polluted Insulator String

Insulator becomes wet partially or completely, and the pollution layer on itbecomes conductive, when collecting pollutants for an extended period during dew, light rain, mist,fog or snow melting. Heavy rain is a complicated factor that it may wash away the pollution layerwithout initiating other stages of breakdown or it may bridge the gaps between sheds to promoteflashover. The insulator with a conducting pollution layer being energized, can cause a surfaceleakage current to flow (also temperature-rise). As the surface conductivity is non-uniform, theconducting pollution layer becomes broken by dry bands (at spots of high current density),interrupting the flow of leakage current. Voltage across insulator gets concentrated across drybands, and causes high electric stress and breakdown (dry band arcing). If the resistance of theinsulator surface is sufficiently low, the dry band arcs can be propagated to bridge the terminalscausing flashover. The present paper concerns the evaluation of the temperature distribution alongthe surface of an energized artificially polluted insulator string.

A LS-SVM （Least Squares Support Vector Machines） Approach for Predicting Critical Flashover Voltage of Polluted Insulators

LS-SVM （least squares support vector machines） are a class of kemel machines emphasizing on primal-dual aspects in a constrained optimization framework. LS-SVMs aim at extending methodologies typical of classical support vector machines for problems beyond classification and regression. This paper describes a methodology that was developed for the prediction of the critical flashover voltage of polluted insulators by using a LS-SVM. The methodology uses as input variables characteristics of the insulator such as diameter, height, creepage distance, form factor and equivalent salt deposit density. The estimation offlashover performance of polluted insulators is based on field experience and laboratory tests are invaluable as they significantly reduce the time and labour involved in insulators design and selection. The majority of the variables to be predicted are dependent upon several independent variables. The results from this work are useful to predict the contamination severity, critical flashover voltage as a function of contamination severity, arc length, and especially to predict the flashover voltage. The validity of the approach was examined by testing several insulators with different geometries. Moreover, the performance of the proposed approach with other intelligence method based on ANN （artificial neural networks） is compared. It can be concluded that the LS-SVM approach has better generalization ability that assist the measurement and monitoring of contamination severity, flashover voltage and leakage current.

Resistance Measurements and Interpretations Relating to Flashover of Artificially Contaminated Ceramic Insulator Strings

The flashover of insulator strings occurring at normal working voltages undercontaminated/polluted conditions, obviously deserves serious consideration. Though much researchhas been gone into pollution-induced flashover phenomena but grey areas still exist in ourknowledge. In the present experimental study the breakdown (flashover) voltages across gaps oninsulator top surfaces and gaps between sheds (on the underside of an insulator), also the flashoverstudies on a single unit and a 3-unit insulator strings were carried out. An attempt has been madeto correlate the values obtained for all the cases. From the present investigation it was found thatresistance measurement of individual units of a polluted 3-unit string before and after flashoverindicates that strongly differing resistances could be the cause of flashover of ceramic discinsulator strings.