基于振动测量的斜拉索长期张力监测异常自动检测与处理

W. Wu, Chien-Chou Chen, Shang-Li Lin, G. Lai
{"title":"基于振动测量的斜拉索长期张力监测异常自动检测与处理","authors":"W. Wu, Chien-Chou Chen, Shang-Li Lin, G. Lai","doi":"10.1093/iti/liac002","DOIUrl":null,"url":null,"abstract":"\n Stay cables are the crucial force-transmitting components of cable-stayed bridges. Consequently, effective cable tension monitoring is typically regarded as the most important issue in structural health monitoring for this type of bridges. In long-term monitoring of structures, the occurrence of abnormal signals due to different reasons such as sensor faults, system malfunction, data loss in transmission, or instability of power supply, is almost unavoidable and may strongly deteriorate the quality of followed analyses. The current paper presents the first phase of a project to develop an automatic monitoring system of cable tension based on ambient vibration signals for Mao-Luo-Hsi Bridge. The results demonstrate that automatic anomaly detection and processing for cable vibration measurements can be conveniently achieved with a relatively simple algorithm merely using an appropriate threshold of maximum response value. In addition, elimination of anomaly in the testing stage of installing the monitoring system is also reported.","PeriodicalId":191628,"journal":{"name":"Intelligent Transportation Infrastructure","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic anomaly detection and processing for long-term tension monitoring of stay cables based on vibration measurements\",\"authors\":\"W. Wu, Chien-Chou Chen, Shang-Li Lin, G. Lai\",\"doi\":\"10.1093/iti/liac002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Stay cables are the crucial force-transmitting components of cable-stayed bridges. Consequently, effective cable tension monitoring is typically regarded as the most important issue in structural health monitoring for this type of bridges. In long-term monitoring of structures, the occurrence of abnormal signals due to different reasons such as sensor faults, system malfunction, data loss in transmission, or instability of power supply, is almost unavoidable and may strongly deteriorate the quality of followed analyses. The current paper presents the first phase of a project to develop an automatic monitoring system of cable tension based on ambient vibration signals for Mao-Luo-Hsi Bridge. The results demonstrate that automatic anomaly detection and processing for cable vibration measurements can be conveniently achieved with a relatively simple algorithm merely using an appropriate threshold of maximum response value. In addition, elimination of anomaly in the testing stage of installing the monitoring system is also reported.\",\"PeriodicalId\":191628,\"journal\":{\"name\":\"Intelligent Transportation Infrastructure\",\"volume\":\"105 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent Transportation Infrastructure\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/iti/liac002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Transportation Infrastructure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/iti/liac002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

斜拉索是斜拉桥的重要传力构件。因此,有效的索张力监测通常被认为是这类桥梁结构健康监测中最重要的问题。在结构物的长期监测中,由于传感器故障、系统故障、传输数据丢失、供电不稳定等不同原因导致的异常信号的出现几乎是不可避免的,这可能会严重影响后续分析的质量。本文介绍了茂罗西桥基于环境振动信号的拉索张力自动监测系统的一期工程。结果表明,只需选择合适的最大响应值阈值,就可以用相对简单的算法方便地实现电缆振动测量的自动异常检测和处理。此外,还报道了安装监控系统测试阶段的异常消除情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic anomaly detection and processing for long-term tension monitoring of stay cables based on vibration measurements
Stay cables are the crucial force-transmitting components of cable-stayed bridges. Consequently, effective cable tension monitoring is typically regarded as the most important issue in structural health monitoring for this type of bridges. In long-term monitoring of structures, the occurrence of abnormal signals due to different reasons such as sensor faults, system malfunction, data loss in transmission, or instability of power supply, is almost unavoidable and may strongly deteriorate the quality of followed analyses. The current paper presents the first phase of a project to develop an automatic monitoring system of cable tension based on ambient vibration signals for Mao-Luo-Hsi Bridge. The results demonstrate that automatic anomaly detection and processing for cable vibration measurements can be conveniently achieved with a relatively simple algorithm merely using an appropriate threshold of maximum response value. In addition, elimination of anomaly in the testing stage of installing the monitoring system is also reported.
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:604180095
Book学术官方微信