Degradation Trend Prediction of Linear Regulator Based on SVR Under Nuclear Radiation Stress

Hongwei Qiao, Li Zhan, Jie Liu, Lin Zhang, Zhangchun Tang, Jia Xie
{"title":"Degradation Trend Prediction of Linear Regulator Based on SVR Under Nuclear Radiation Stress","authors":"Hongwei Qiao, Li Zhan, Jie Liu, Lin Zhang, Zhangchun Tang, Jia Xie","doi":"10.1109/phm-qingdao46334.2019.8942997","DOIUrl":null,"url":null,"abstract":"Due to the development of science and technology, many electronic products still need a long time to degrade and fail under the condition of accelerated life test, especially under the harsh test conditions such as nuclear radiation, and it brings great challenges to research on the reliability of electronic products. In order to obtain the performance index of electronic product degradation failure, this paper proposes to use support vector regression(SVR) method to predict the performance degradation index of AP1117E series linear voltage stabilizer under nuclear radiation stress, and use the degradation data obtained from the test and the predicted degradation data to complete the reliability evaluation of the device. The prediction method proposed in this paper is used in the actual reliability assessment engineering project, and it has played a certain suggestive role for future reliability assessment work.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/phm-qingdao46334.2019.8942997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Due to the development of science and technology, many electronic products still need a long time to degrade and fail under the condition of accelerated life test, especially under the harsh test conditions such as nuclear radiation, and it brings great challenges to research on the reliability of electronic products. In order to obtain the performance index of electronic product degradation failure, this paper proposes to use support vector regression(SVR) method to predict the performance degradation index of AP1117E series linear voltage stabilizer under nuclear radiation stress, and use the degradation data obtained from the test and the predicted degradation data to complete the reliability evaluation of the device. The prediction method proposed in this paper is used in the actual reliability assessment engineering project, and it has played a certain suggestive role for future reliability assessment work.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于SVR的线性调节器在核辐射胁迫下的退化趋势预测
由于科学技术的发展,许多电子产品在加速寿命试验的条件下,特别是在核辐射等恶劣的试验条件下,仍然需要很长时间才能降解失效,这给电子产品可靠性的研究带来了很大的挑战。为了获得电子产品退化失效的性能指标,本文提出采用支持向量回归(SVR)方法预测AP1117E系列线性稳压器在核辐射应力下的性能退化指标,并利用试验获得的退化数据和预测的退化数据完成对器件的可靠性评估。本文提出的预测方法在实际的可靠性评估工程项目中得到了应用,对今后的可靠性评估工作起到了一定的提示作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Wagon PHM State Model Based on AHP and Gray Clustering Model Fault Feature Extraction of Compound Planetary Gear Based on VMD and DE Review on Key Technologies of Wireless Monitoring of Pump Group Based on Internet of Things Motion Characteristic Analysis of High Voltage Circuit Breaker Transmission Mechanism Design of the Power Supply System and the PHM Architecture for Unmanned Surface Vehicle
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1