AirleakSlam: Detection of Pressurized Air Leaks Using Passive Ultrasonic Sensors

Anthony Schenck, W. Daems, J. Steckel
{"title":"AirleakSlam: Detection of Pressurized Air Leaks Using Passive Ultrasonic Sensors","authors":"Anthony Schenck, W. Daems, J. Steckel","doi":"10.1109/SENSORS43011.2019.8956631","DOIUrl":null,"url":null,"abstract":"It is estimated that up to a third of the power consumption of compressed air networks is lost due to undetected leaks. Current methods of detecting and locating these air leaks involve manual labor using handheld devices that can detect the ultrasonic sound generated by the escaping air. In addition, the extra energy costs caused by the air leaks are concealed in the total cost of energy, reducing the sense of needing to find a solution. Therefore, there is limited commitment to actively detect and repair these air leaks. In order to address this issue, we propose a solution that requires no manual labor in the localization process, by fitting existing factory vehicles with an enclosure containing all the required sensors: a laser scanner for SLAM localization and an ultrasonic microphone array. By combining SLAM techniques with our ultrasonic microphone array on a robot, we are able to locate leaks in a large environment with high precision in 3D. By automating this process we aim to encourage the industry to proactively search for air leaks to reduce the amount of energy loss at a fraction of the cost of current methods.","PeriodicalId":6710,"journal":{"name":"2019 IEEE SENSORS","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE SENSORS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SENSORS43011.2019.8956631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

It is estimated that up to a third of the power consumption of compressed air networks is lost due to undetected leaks. Current methods of detecting and locating these air leaks involve manual labor using handheld devices that can detect the ultrasonic sound generated by the escaping air. In addition, the extra energy costs caused by the air leaks are concealed in the total cost of energy, reducing the sense of needing to find a solution. Therefore, there is limited commitment to actively detect and repair these air leaks. In order to address this issue, we propose a solution that requires no manual labor in the localization process, by fitting existing factory vehicles with an enclosure containing all the required sensors: a laser scanner for SLAM localization and an ultrasonic microphone array. By combining SLAM techniques with our ultrasonic microphone array on a robot, we are able to locate leaks in a large environment with high precision in 3D. By automating this process we aim to encourage the industry to proactively search for air leaks to reduce the amount of energy loss at a fraction of the cost of current methods.
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
据估计,压缩空气网络高达三分之一的电力消耗是由于未被发现的泄漏造成的。目前检测和定位这些空气泄漏的方法涉及使用手持设备的体力劳动,这些设备可以检测由逸出的空气产生的超声波。此外,由空气泄漏引起的额外能源成本隐藏在能源总成本中,减少了需要寻找解决方案的感觉。因此,积极检测和修复这些空气泄漏的承诺有限。为了解决这个问题,我们提出了一个在定位过程中不需要人工的解决方案,通过为现有的工厂车辆安装一个包含所有必要传感器的外壳:用于SLAM定位的激光扫描仪和超声波麦克风阵列。通过将SLAM技术与机器人上的超声波麦克风阵列相结合,我们能够在大环境中以高精度的3D方式定位泄漏。通过自动化这一过程,我们的目标是鼓励行业主动寻找空气泄漏,以减少能源损失,而成本只是当前方法的一小部分。
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
Identification of Legionella Species by Photogate-Type Optical Sensor A Nano-Watt Dual-Mode Address Detector for a Wi-Fi Enabled RF Wake-up Receiver Optical Feedback Interferometry imaging sensor for micrometric flow-patterns using continuous scanning DNN-based Outdoor NLOS Human Detection Using IEEE 802.11ac WLAN Signal Disconnect Switch Position Sensor Based on FBG
×
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