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Prediction of the High Frequency Behavior in Degraded Coaxial Connector Based on Neural Network

Q.Li 1, W. Yi 2, and J. Gao 3
1. Institute of Automation, Chinese Academy of Sciences, Beijing, China
2. Department of Materials Engineering, Auburn University, Auburn, AL, USA
3. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China

Abstract—Accurate prediction of high frequency behavior for the degraded contact surface is of great significance for the reliability evaluation of the connector. A prediction algorithm of neural network is proposed to forecast the high frequency scattering parameters under different degrada-tion levels. The degraded high frequency parameters are extracted according to the developed equivalent model. Simulations are conducted to predict the scattering para-meters at the specific frequencies using the BP (back propagation) and Elman neural networks, and the prediction accuracy is further compared. Moreover, the scattering parameters at 3.1GHz to 3.5GHz are predicted for the two degradation levels, which provides the variations under higher frequency.
 
Index Terms—Contact degradation, high frequency characteristics, neural network

Cite: Q.Li, W. Yi, and J. Gao, "Prediction of the High Frequency Behavior in Degraded Coaxial Connector Based on Neural Network," International Journal of Electrical and Electronic Engineering & Telecommunications