Cognisense

M. Heggo, Laksh Bhatia, J. Mccann
{"title":"Cognisense","authors":"M. Heggo, Laksh Bhatia, J. Mccann","doi":"10.1145/3485730.3492879","DOIUrl":null,"url":null,"abstract":"Several engineering applications require reliable rotation speed measurement for their correct functioning. The rotation speed measurements can be used to enhance the machines' vibration signal analysis and can also elicit faults undetectable by vibration monitoring alone. The current state of the art sensors for rotation speed measurement are optical, magnetic and mechanical tachometers. These sensors require line-of-sight and direct access to the machine which limits their use-cases. In this demo, we showcase Cognisense, an RF-based hardware-software sensing system that uses Orbital Angular Momentum (OAM) waves to accurately measure a machine's rotation speed. Cognisense uses a novel compact patch antenna in a monostatic radar configuration capable of transmitting and receiving OAM waves in the 5GHz license-exempt band. The demo will show Cognisense working on machines with varied numbers of blades, sizes and materials. We will also present how Cognisense operates reliably in non-line-of-sight scenarios where traditional tachometers fail. We demonstrate how Cognisense works well in high-scattering scenarios and is not impacted by the material of rotor blades. Unlike optical tachometers that require one to face the machine head-on, Our demo will also show Cognisense performing reliably in the presence of a tilt angle between the system and the machine which is not possible with optical tachometers.","PeriodicalId":356322,"journal":{"name":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3485730.3492879","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

Several engineering applications require reliable rotation speed measurement for their correct functioning. The rotation speed measurements can be used to enhance the machines' vibration signal analysis and can also elicit faults undetectable by vibration monitoring alone. The current state of the art sensors for rotation speed measurement are optical, magnetic and mechanical tachometers. These sensors require line-of-sight and direct access to the machine which limits their use-cases. In this demo, we showcase Cognisense, an RF-based hardware-software sensing system that uses Orbital Angular Momentum (OAM) waves to accurately measure a machine's rotation speed. Cognisense uses a novel compact patch antenna in a monostatic radar configuration capable of transmitting and receiving OAM waves in the 5GHz license-exempt band. The demo will show Cognisense working on machines with varied numbers of blades, sizes and materials. We will also present how Cognisense operates reliably in non-line-of-sight scenarios where traditional tachometers fail. We demonstrate how Cognisense works well in high-scattering scenarios and is not impacted by the material of rotor blades. Unlike optical tachometers that require one to face the machine head-on, Our demo will also show Cognisense performing reliably in the presence of a tilt angle between the system and the machine which is not possible with optical tachometers.
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
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
Adaptive Video Transmission Strategy Based on Ising Machine Wavoice: A Noise-resistant Multi-modal Speech Recognition System Fusing mmWave and Audio Signals Experimental Scalability Study of Consortium Blockchains with BFT Consensus for IoT Automotive Use Case MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar FedMask
×
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