基于神经网络的退化同轴连接器高频特性预测

Q2 Computer Science

International Journal of Electrical and Electronic Engineering and Telecommunications Pub Date : 2022-01-01 DOI:10.18178/ijeetc.11.2.156-161

Q. Li, W. Yi, Jie Gao

{"title":"基于神经网络的退化同轴连接器高频特性预测","authors":"Q. Li, W. Yi, Jie Gao","doi":"10.18178/ijeetc.11.2.156-161","DOIUrl":null,"url":null,"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.","PeriodicalId":37533,"journal":{"name":"International Journal of Electrical and Electronic Engineering and Telecommunications","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of the High Frequency Behavior in Degraded Coaxial Connector Based on Neural Network\",\"authors\":\"Q. Li, W. Yi, Jie Gao\",\"doi\":\"10.18178/ijeetc.11.2.156-161\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":37533,\"journal\":{\"name\":\"International Journal of Electrical and Electronic Engineering and Telecommunications\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electrical and Electronic Engineering and Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18178/ijeetc.11.2.156-161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical and Electronic Engineering and Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18178/ijeetc.11.2.156-161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}

引用次数: 0

摘要

准确预测退化接触面的高频特性对连接器的可靠性评估具有重要意义。提出了一种神经网络预测算法来预测不同退化程度下的高频散射参数。根据建立的等效模型提取退化的高频参数。利用BP(反向传播)神经网络和Elman神经网络对特定频率下的散射参数进行了预测，并对预测精度进行了比较。同时，对两种退化水平在3.1GHz ~ 3.5GHz时的散射参数进行了预测，给出了在更高频率下的变化规律。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Electrical and Electronic Engineering and Telecommunications Engineering-Electrical and Electronic Engineering

CiteScore

5.90

自引率

0.00%

发文量

期刊介绍： International Journal of Electrical and Electronic Engineering & Telecommunications. IJEETC is a scholarly peer-reviewed international scientific journal published quarterly, focusing on theories, systems, methods, algorithms and applications in electrical and electronic engineering & telecommunications. It provide a high profile, leading edge forum for academic researchers, industrial professionals, engineers, consultants, managers, educators and policy makers working in the field to contribute and disseminate innovative new work on Electrical and Electronic Engineering & Telecommunications. All papers will be blind reviewed and accepted papers will be published quarterly, which is available online (open access) and in printed version.