To investigate the fouling characteristics of the composite insulator surface under the salt fog environment,the FXBW-110/120-2 composite insulator was taken as the research object.Based on the field-induced charge me...To investigate the fouling characteristics of the composite insulator surface under the salt fog environment,the FXBW-110/120-2 composite insulator was taken as the research object.Based on the field-induced charge mechanism,the multi-physical field coupling software COMSOL was used to numerically simulate the fouling characteristics,explored the calculation method of ESDD,and demonstrated its rationality.Based on this method,the pollution characteristics of the composite insulator under the pollution fog environment were studied,and the influence of wind speed,droplet size,and voltage type on the pollution characteristics of the composite insulator was analyzed.The results showed that:with the increase in wind speed,the amount of accumulated pollution of insulator increases in the range of droplet size,and the relationship between wind speed and accumulated pollution is approximately linear;at the same wind speed,the amount of accumulated pollution increases with the increase of droplet size under the action of DC voltage;when there is no voltage,the amount of dirt on the upper surface of the insulator is more than that on the lower surface,while it is the opposite under DC voltage.展开更多
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 su...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.展开更多
文摘To investigate the fouling characteristics of the composite insulator surface under the salt fog environment,the FXBW-110/120-2 composite insulator was taken as the research object.Based on the field-induced charge mechanism,the multi-physical field coupling software COMSOL was used to numerically simulate the fouling characteristics,explored the calculation method of ESDD,and demonstrated its rationality.Based on this method,the pollution characteristics of the composite insulator under the pollution fog environment were studied,and the influence of wind speed,droplet size,and voltage type on the pollution characteristics of the composite insulator was analyzed.The results showed that:with the increase in wind speed,the amount of accumulated pollution of insulator increases in the range of droplet size,and the relationship between wind speed and accumulated pollution is approximately linear;at the same wind speed,the amount of accumulated pollution increases with the increase of droplet size under the action of DC voltage;when there is no voltage,the amount of dirt on the upper surface of the insulator is more than that on the lower surface,while it is the opposite under DC voltage.
文摘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.
