Storage Life Prediction of Space Relay Based on Elman Neural Network

Abstract

When the linear equation is used to fit the life data for predicting the storage life at room temperature, there is a large error. From this point of view, the parameter degradation is considered and the contact pressure drop parameter is fused according to the comprehensive correlation degree at 60°C, 73°C, 92°C and 125°C. The accelerating factors of four temperature gradients are obtained by using the Arrhenius equation. The parameters and storage life in high temperature state are equivalent to normal temperature. The Elman neural network is used to study and train the fusion parameters, then the storage life of the relay at room temperature is predicted. The prediction error of this method is 2.44%, which is smaller than expected.