Correction Model of Pressure Sensor Based on Support Vector Machine

B. Peng, He Changlong, Zhang Bin, Chen Chang-xing, Li Yan
{"title":"Correction Model of Pressure Sensor Based on Support Vector Machine","authors":"B. Peng, He Changlong, Zhang Bin, Chen Chang-xing, Li Yan","doi":"10.1109/ICIM.2009.33","DOIUrl":null,"url":null,"abstract":"The temperature and voltage fluctuation characteristics of pressure sensor was analyzed and found that the sensor output is nonlinear and easy to be affected by temperature and voltage fluctuation over a wide measuring range, a correction model of pressure sensor based on Support Vector Machine was presented. The approximate ability of the SVM to any nonlinear function was utilized to drill the correction model. so as to enable it to be setup at different temperatures and voltage fluctuation, thus allowing the sensor output can be in a nonlinear mapping relation to the voltage values the sensor actually sensed. The experimental results showed that the max comes down from 22.2% for 0.64%; the model can not only eliminate the influence of temperature fluctuation and voltage fluctuation but obtain the expected linear output from the output terminal of correction model.","PeriodicalId":126685,"journal":{"name":"2009 International Conference on Innovation Management","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Innovation Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIM.2009.33","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

The temperature and voltage fluctuation characteristics of pressure sensor was analyzed and found that the sensor output is nonlinear and easy to be affected by temperature and voltage fluctuation over a wide measuring range, a correction model of pressure sensor based on Support Vector Machine was presented. The approximate ability of the SVM to any nonlinear function was utilized to drill the correction model. so as to enable it to be setup at different temperatures and voltage fluctuation, thus allowing the sensor output can be in a nonlinear mapping relation to the voltage values the sensor actually sensed. The experimental results showed that the max comes down from 22.2% for 0.64%; the model can not only eliminate the influence of temperature fluctuation and voltage fluctuation but obtain the expected linear output from the output terminal of correction model.
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
基于支持向量机的压力传感器校正模型
分析了压力传感器的温度和电压波动特性,发现传感器输出是非线性的,在较宽的测量范围内容易受到温度和电压波动的影响,提出了基于支持向量机的压力传感器校正模型。利用支持向量机对任意非线性函数的近似能力钻取修正模型。从而使其能够设置在不同的温度和电压波动下,从而使传感器的输出能够与传感器实际感知到的电压值呈非线性映射关系。实验结果表明,最大值由22.2%下降到0.64%;该模型不仅可以消除温度波动和电压波动的影响,而且可以从修正模型的输出端获得期望的线性输出。
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
Correction Model of Pressure Sensor Based on Support Vector Machine Open-Loop and Closed-Loop Differential Duopolistic Models of Optimal Sticky Prices and Advertising in Product Differentiation Market Technology Incubator Performance in New Zealand An Improved Estimation Algorithm of Symbol Synchronization for QAM Signal Study of Knowledge-Based Dynamic Consistency upon Employee Performance Standards
×
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