Prediction Model Of Contact Resistance Of Fittings And Its Application

Electrical contacts are widely used in power systems,automatic control systems,and information transmission systems,such as the connection of valve hall fittings,relay contacts,and contacts of high voltage circuit breakers.The stability and reliability of electrical contacts are critical to the safety of related equipmen t and systems.Contact resistance is an important parameter that reflects the reliability of electrical contact.It is an important indicator to measure the contact between conductors.In the past,the study of contact resistance usually used theoretical a nd numerical modeling methods.This method often required some simplification and assumptions on the research object,which made the accuracy of the model obtained by theoretical method and numerical method difficult to meet the engineering requirements.The intelligent prediction method that has received extensive attention in recent years provides a possible solution to improve the accuracy of the contact resistance prediction model.In this paper,the method of calculating the contact resistance based on genetic algorithm optimization BP neural network is proposed for the first time.This method not only improves the calculation accuracy of the contact resistance,but also provides a new possibilities for contact resistance model.In addition,the contact resistance prediction model is related to the local heating problem of the valve hall fittings caused by the contact resistance.The first attempt is to combine the intelligent prediction model with the local temperature rise of the valve hall fittings of the converter station,and define the temperature field characteristic parameters by feature definition method,the final experimental results show that the genetic algorithm optimization BP neural network model can accurately predict the temperature rise of the valve hall fittings,and can grasp the temperature rise data without affecting the electric field distribution.It is of great significance to reduce the power system failure caused by local temperature rise,and also provides an important basis for the optimal design of the fittings.