基于pso的差压液位传感器自动校准

P. Esmaili, P. Esmaili, F. Cavedo, M. Norgia
{"title":"基于pso的差压液位传感器自动校准","authors":"P. Esmaili, P. Esmaili, F. Cavedo, M. Norgia","doi":"10.1109/ICAIoT53762.2021.00013","DOIUrl":null,"url":null,"abstract":"To achieve desired level of accuracy in piezoresistive pressure sensors based on silicon, calibration should be performed frequently. In this paper, an Intelligent auto-calibration approach is proposed to update characterization curve in differential pressure-based level sensor. This intelligent method is based on particle swarm optimization method. To achieve optimum results, different factors such as self-knowledge and social knowledge coefficients in addition to inertia weight have been considered in this intelligent auto-calibration method. The compensation process is the last part of the system. It leads to achieve the up bounded measurement error becomes limited to 0.25 mm.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PSO-based autocalibration for differential pressure level sensor\",\"authors\":\"P. Esmaili, P. Esmaili, F. Cavedo, M. Norgia\",\"doi\":\"10.1109/ICAIoT53762.2021.00013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To achieve desired level of accuracy in piezoresistive pressure sensors based on silicon, calibration should be performed frequently. In this paper, an Intelligent auto-calibration approach is proposed to update characterization curve in differential pressure-based level sensor. This intelligent method is based on particle swarm optimization method. To achieve optimum results, different factors such as self-knowledge and social knowledge coefficients in addition to inertia weight have been considered in this intelligent auto-calibration method. The compensation process is the last part of the system. It leads to achieve the up bounded measurement error becomes limited to 0.25 mm.\",\"PeriodicalId\":344613,\"journal\":{\"name\":\"2021 International Conference on Artificial Intelligence of Things (ICAIoT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Artificial Intelligence of Things (ICAIoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIoT53762.2021.00013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIoT53762.2021.00013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了在基于硅的压阻压力传感器中达到所需的精度水平,应该经常进行校准。本文提出了一种智能自动校准方法来更新差压式液位传感器的表征曲线。该智能方法基于粒子群优化方法。该智能自动标定方法除考虑惯性权重外,还考虑了自我知识系数和社会知识系数等不同因素,以达到最优结果。补偿过程是系统的最后一部分。从而实现上界测量误差限制在0.25 mm以内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSO-based autocalibration for differential pressure level sensor
To achieve desired level of accuracy in piezoresistive pressure sensors based on silicon, calibration should be performed frequently. In this paper, an Intelligent auto-calibration approach is proposed to update characterization curve in differential pressure-based level sensor. This intelligent method is based on particle swarm optimization method. To achieve optimum results, different factors such as self-knowledge and social knowledge coefficients in addition to inertia weight have been considered in this intelligent auto-calibration method. The compensation process is the last part of the system. It leads to achieve the up bounded measurement error becomes limited to 0.25 mm.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信