LOW VOLTAGE APPARATUS ›› 2024, Vol. 0 ›› Issue (3): 30-35.doi: 10.16628/j.cnki.2095-8188.2024.03.005

• Research & Analysis • Previous Articles     Next Articles

Storage Life Prediction Method of Aerospace Electromagnetic Relay with Improved RBF Neural Network Based on Snake Algorithm Optimization

LI Jiuxin, WANG Zhaobin, ZHU Jiamiao   

  1. College of Automation,Jiangsu University of Science and Technology, Zhenjiang 212003, China
  • Received:2023-10-02 Online:2024-03-30 Published:2024-04-22

Abstract:

Aiming at the prediction and prediction accuracy of contact resistance of aerospace electromagnetic relays,a radial basis function (BRF) neural network model based on snake optimization (SO) algorithm is proposed.On the basis of the traditional RBF model,the SO algorithm is used to optimize the weight parameters so as to better predict the contact resistance value of the relay.The constructed SO-RBF prediction model is compared with RBF model.The models are used to predict the change trend of contact resistance.The comparison and analysis of the prediction results show that the proposed model has high prediction accuracy.

Key words: radial basis function (RBF) neural network, degradation test, storage, relay

CLC Number: