Review on flashover risk prediction method of iced insulator based on icing monitoring technology

Insulator flashover caused by atmospheric icing is a serious accident with high frequency, which seriously influences the security of the power system in icing areas. Therefore, it is of great theoretical significance and engineering value to carry out research on risk prediction technology of icing flashover. Firstly, in this paper, the main influencing factors of icing flashover of insulators are analyzed, and the morphological characteristics of iced insulators are deeply studied, such as icing type, icing amount, icicle length and bridging state, insulator pollution, etc. Secondly, the monitoring methods of iced insulator are analyzed and compared, and the results show that the image monitoring technology has obvious advantages in icing flashover prediction. More importantly, the current research progress and technical difficulties of image recognition technology for icing flashover parameters are discussed. Finally, the research prospect of flashover risk prediction model for iced insulator is introduced based on deduction method and machine learning algorithm.

Automated summary

The paper analyzes the main influencing factors of icing flashover on insulators and deeply studies the morphological characteristics of iced insulators, as well as compares monitoring methods. Results suggest that image monitoring technology has advantages in predicting icing flashover. Discussions on the current progress and technical difficulties of image recognition technology for icing flashover parameters are also presented.