Bridge health monitoring system based on vibration measurements

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桥梁健康监测技术发展现状及趋势分析

２００８年９月第９期（总１２０）铁道工程学报ＪＯＵＲＮＡＬＯＦＲＡＩＬＷＡＹＥＮＧＩＮＥＥＲＩＮＧＳＯＣＩＥＴＹＳｅｐ２００８ＮＯ．９（Ｓｅｒ．１２０）文章编号：１００６—２１０６（２００８）０９—００４４—０４桥梁健康监测技术发展现状及趋势分析。

魏新良１王震洪２¨（１．新疆交通职业技术学院，鸟鲁木齐８３１４０１；２．新疆交通建设局，鸟鲁木齐８３１４０１）摘要：研究目的：通过对桥梁健康监测技术涉及到的模型修正、指纹、动力等不同的状态评估方法的归纳，对桥梁健康监测技术现状进行了综合分析，并对健康监测技术的发展趋势进行预测。

研究结果：桥梁健康监测与状态评估系统的研究尚处于基础性的探索阶段，距离实用性的系统目标尚有很大的差距。

目前仅能准确测量低频响应，而低频响应多为结构的整体模态，对整体响应贡献小的局部，即使在整体模态中有所反映，但由于量值过小，往往也容易淹没在噪声、误差和不确定因素引起的扰动之中。

今后桥梁健康监测的发展方向一是降低噪声和不确定性因素的影响，二是提高桥梁损伤诊断方法的灵敏度，通过技术优化可以达到对损伤程度的量化。

关键词：状态评估；损伤；监测；趋势中图分类号：Ｕ４４６文献标识码：ＡＴｈｅＣｕｒｒｅｎｔＤｅｖｅｌｏｐｍｅｎｔＳｉｔｕａｔｉｏｎａｎｄＴｒｅｎｄｏｆＭｏｎｉｔｏｒｉｎｇＴｅｃｈｎｏｌｏｇｙｆｏｒＢｒｉｄｇｅＨｅａｌｔｈＷＥｌＸｉｎ—ｌｉａｎ９１．ＷＡＮＧＺｈｅｎ—ｈｏｎ９２（１．ＸｉｎｊｉａｎｇＴｒａｎｓｐｏｒｔａｔｉｏｎＰｒｏｆｅｓｓｉｏｎａｌＴｅｃｈｎｏｌｏｇｙＩｎｓｔｉｔｕｔｅ，Ｕｒｕｍｑｉ，Ｘｉｎｊｉａｎｇ８３１４０１，Ｃｈｉｎａ；２．ＸｉｎｊｉａｎｇＴｒａｎｓｐｏｒｔａｔｉｏｎＢｕｒｅａｕ，Ｕｒｕｍｑｉ，Ｘｉｎｊｉａｎｇ８３１４０１，Ｃｈｉｎａ）Ａｂｓｔｒａｃｔ：Ｒｅｓｅａｒｃｈｐｕｒｐｏｓｅｓ：Ｔｈｒｏｕｇｈｍａｋｉｎｇｓｕｍｍａｒｙｏｎｔｈｅｅｖａｌｕａｔｉｏｎｍｅｔｈｏｄｓｆｏｒｔｈｅｄｉｆｆｅｒｅｎｔｓｔａｔｕｓｏｆｍｏｄｅｌｍｏｄｉｆｉｃａｔｉｏｎ，ｆｉｎｇｅｒｐｒｉｎｔａｎｄｄｙｎａｍｉｃｓｉｎｖｏｌｖｅｄｉｎｔｈｅｍｏｎｉｔｏｒｉｎｇｔｅｃｈｎｏｌｏｇｙｆｏｒｂｒｉｄｇｅｈｅａｌｔｈ，ｔｈｅｃｏｍｐｒｅｈｅｎｓｉｖｅａｎａｌｙｓｉｓｏｆｔｈｅｃｕｒｒｅｎｔｄｅｖｅｌｏｐｍｅｎｔｓｉｔｕａｔｉｏｎｏｆｍｏｎｉｔｏｒｉｎｇｔｅｃｈｎｏｌｏｇｙｆｏｒｂｒｉｄｇｅｈｅａｌｔｈｉｓｍａｄｅａｎｄｉｔｓｄｅｖｅｌｏｐｍｅｎｔｔＩｅｎｄｉｓｐｒｅｄｉｃｔｅｄ．Ｒｅｓｅａｒｃｈｒｅｓｕｌｔｓ：Ｔｈｅｒｅｓｅａｒｃｈｏｎｔｈｅｂｒｉｄｇｅｈｅａｌｔｈｍｏｎｉｔｏｒｉｎｇａｎｄｅｖａｌｕａｔｉｏｎｓｙｓｔｅｍｉｓａｔｔｈｅｂｅｇｉｎｎｉｎｇｓｔａｇｅａｎｄｉｔｈａｓｌｏｎｇｗａｙｔｏｇｏｔｏｐｕｔｔｈｅｓｙｓｔｅｍｉｎｔｏｐｒａｃｔｉｃｅ．Ｎｏｗａｄａｙｓｏｎｌｙｔｈｅｒｅｓｐｏｎｓｅｏｆｌｏｗｆｒｅｑｕｅｎｃｙｃａｎｂｅｍｅａｓｕｒｅｄｐｒｅｃｉｓｅｌｙａｎｄｏｎｌｙｃａｎｒｅｆｌｅｃｔｔｈｅｅｎｔｉｒｅｓｔａｔｕｓｏｆｔｈｅｓｔｒｕｃｔｕｒｅ．Ｈｏｗｅｖｅｒ，ｅｖｅｎｓｕｃｈｒｅｓｐｏｎｓｅｃａｎｂｅｒｅｆｌｅｃｔｅｄｉｎｔｈｅｅｎｔｉｒｅｓｔａｔｕｓ，ｂｕｔｉｔｉｓｅａｓｉｌｙｄｉｓｔｕｒｂｅｄｂｙｔｈｅｎｏｉｓｅ，ｅｒｒｏｒａｎｄｕｎｓｔａｂｌｅｆａｃｔｏｒｓｂｅｃａｕｓｅｔｈｅｍｅａｓｕｒｅｄｖａｌｕｅｉｓｔｏｏｓｍａｌｌ．Ｔｈｅｄｅｖｅｌｏｐｍｅｎｔｔｒｅｎｄｏｆｍｏｎｉｔｏｒｉｎｇｔｅｃｈｎｏｌｏｇｙｆｏｒｂｒｉｄｇｅｈｅａｌｔｈｉｓａｓｆｏｌｌｏｗｓ：Ｔｈｅｆｉｒｓｔｉｓｔｏｒｅｄｕｃｅｔｈｅｎｏｉｓｅａｎｄｕｎｓｔａｂｌｅｆａｃｔｏｒｓａｎｄｔｈｅｓｅｃｏｎｄｉｓｔｏｅｎｈａｎｃｅｔｈｅｓｅｎｓｉｔｉｖｉｔｙｏｆｄｉａｇｎｏｓｔｉｃｍｅｔｈｏｄｏｆｂｒｉｄｇｅｄａｍａｇｅｔｏｒｅａｌｉｚｅｔｈｅｑｕａｎｔｉｚａｔｉｏｎｏｆｔｈｅｂｒｉｄｇｅｄａｍａｇｅｔｈｒｏｕｇｈｏｐｔｉｍｉｚｉｎｇｔｈｅｔｅｃｈｎｏｌｏｇｙ．Ｋｅｙｗｏｒｄｓ：ｓｔａｔｕｓｅｖａｌｕａｔｉｏｎ；ｄａｍａｇｅ；ｍｏｎｉｔｏｒｉｎｇ；ｔｒｅｎｄ近几十年来，随着社会的进步和土木工程技术的发展，越来越多的大跨度桥梁得到了修建，虽然保守的设计是结构安全的根本保证，但是限于当前对大型复杂结构的认识程度，许多不定时的或不可确定因素’收稿日期：２００８—０７—１５・’作者简介：魏新良．１９７４年出生，男。

桥梁管理系统(BMS)与结构健康监测(SHM)3

事实数据：
➢ 桥梁使用超过25年即进入性能加速退化期 ➢ 美、日等过在20-30年间建设桥梁占到总桥梁数的70%，在其
后的20-30年迎来巨大的桥梁养护工作
➢ 美国总计约7万多座桥梁退化为缺损桥梁，每年维修资金30亿美元 ➢ 法国、德国和挪威，缺损桥梁比例分别达到39%、37%和26% ➢ 欧洲各国用于桥梁维修费用占桥梁重建费用的0.5%~1%，而在美国Biblioteka 桥梁结构健康监测系统(SHM)
结构健康监测系统是基于传感、信息、结构分析技术的自动监测与评估系统，是从营运状态的结构中获取并处理数据以评价结构主要性能指标的有效办法。它结合了无损检测和结构特性分析，可以诊断结构中的损伤发生及其位置，并估计损伤的程度及其对结构造成的影响。
养护管理的基本周期与内容
• 结构初期功能设定 • 结构服役期性能退化预测，对策预案 • 结构可能遭遇的灾害及对策预案 • 分析结构使用时其功能带来的优缺点，并反馈给其它环节
同济大学桥梁工程系孙利民
8
养护管理工作的构成
数据库
同济大学桥梁工程系孙利民
9
养护管理的目标
• 狭义目标：以最小的费用维持某结构在使用期内的性能达到设计要求。
V.S.
桥梁管理系统的发展
1967年美国Silver桥事故
1968年，美国“国家桥梁档案”（NBI）
美国：PONTIS、BRIDGIT 法国：Edouard 英国：NATS 日本：道路共用桥梁管理系统韩国：SHBMS 中国：交通部的CBMS2000系统……
荷兰：基于概率论方法的评估方法（基于可靠度的方法）
结构安全监测出现警报或到达规定检测年限时的检测和安全评估技术；结构安全性不能满足要求时需要采用的维修加固技术

桥梁结构健康监测系统设计规范 DB32_T 3562—2019 江苏地方标准

ICS91.08.040P 25备案号：*** DB32 江苏省地方标准DB32/T 3562—2019桥梁结构健康监测系统设计规范Design Code for Bridge Structural Health Monitoring System2019-04-08发布2019-04- 30实施目录前言 (II)1 范围 (1)2 术语和定义 (1)3 总体要求 (2)4 传感器子系统设计 (3)5 数据采集与传输子系统设计 (5)6 数据存储与处理子系统设计 (8)7 数据预警与结构评估子系统设计 (9)条文说明 (11)1 范围 (11)2 术语和定义 (11)3 总体要求 (11)4 传感器子系统设计 (11)5. 数据通信与传输子系统设计 (12)6. 数据存储与处理子系统设计 (13)7. 数据预警与结构评估子系统 (13)前言本标准按GB/T 1.1—2009给出的规则起草。

本标准由江苏省交通运输厅提出并归口。

本标准起草单位：江苏交通控股有限公司、苏交科集团股份有限公司、东南大学、江苏省长大桥梁健康监测数据中心。

本标准主要起草人：吴智深、张宇峰、吴赞平、孙震、彭家意、杨超、王浩、假冬冬、张建、王友高、徐一超、赵亮、王路、欧阳歆泓、郭俊、徐嵩。

桥梁结构健康监测系统设计规范1 范围1.0.1本规范规定了桥梁结构健康监测系统的设计要求，以提高设计质量，保障桥梁服役期的健康与安全，有效指导桥梁养护管理。

1.0.2 本标准适用于新建或在役的大跨径斜拉桥、悬索桥、拱桥、以及梁桥。

1.0.3 引用标准名录GB 50139-2014 《内河通航标准》GB/T 5083 《公路工程结构可靠度设计统一标准》GB/T17955 《桥梁球形支座》GB/T 21296 《动态公路车辆自动衡器》CJJ 11 《城市桥梁设计规范》JT/T 1037-2016 《公路桥梁结构安全监测系统技术规程》JT/T 391 《公路桥梁盆式支座》JT/T 4 《公路桥梁板式橡胶支座》JTGD60 《公路桥涵设计通用规范》JTG D60-01 《公路桥梁抗风设计规范》JTG/T D65-01 《公路斜拉桥设计细则》EIA/TIA-568A 《商用建筑线缆标准》DB32/T 2880-2016《基于分布式长标距光纤传感的桥梁结构健康监测系统设计与施工规范》T/CECS 505-2018 《光纤光栅结构振动检测与监测标准》2 术语和定义以下术语和定义适用于本文件。

考虑异常监测数据影响的桥梁拉索振动频率识别方法研究

第 54 卷第 12 期2023 年 12 月中南大学学报(自然科学版)Journal of Central South University (Science and Technology)V ol.54 No.12Dec. 2023考虑异常监测数据影响的桥梁拉索振动频率识别方法研究钟国强1，柳尚1，徐润1，丁幼亮2，宋杰1，鞠翰文3，邓扬3(1. 山东省交通规划设计院集团有限公司，山东济南，250101；2. 东南大学土木工程学院，江苏南京，210096；3. 北京建筑大学土木与交通工程学院，北京，100044)摘要：针对桥梁健康监测系统中包含大量异常监测数据的现象，提出考虑异常监测数据影响的桥梁拉索振动频率识别方法。

首先，根据正常监测数据的功率谱密度函数的分布特征，确定拉索振动频率的近似频带区间，进而采用峰值拾取法自动化获取近似频带区间内的拉索振动频率初始识别值。

其次，利用前三阶频率建立三维空间密度聚类模型，进而采用聚类模型检测并剔除频率初始识别值中的异常值。

利用外滩大桥的拉索加速度监测数据对所提方法进行验证。

分析不同类型异常监测数据对拉索频率识别值的影响，考察不同维密度聚类模型对频率异常识别值的检测准确率。

研究结果表明：异常监测数据严重干扰了拉索振动频率的准确识别；三维空间密度聚类模型对拉索振动频率异常识别值的检测准确率达到了98%以上，且剔除异常识别值后的拉索频率与环境温度呈现合理的相关性。

关键词：结构健康监测；频率识别；拉索；异常数据；密度聚类中图分类号：TU311 文献标志码：A 文章编号：1672-7207（2023）12-4870-12Vibration frequency identification method of bridge cableconsidering abnormal monitoring dataZHONG Guoqiang 1, LIU Shang 1, XU Run 1, Ding Youliang 2, SONG Jie 1, JU Hanwen 3, DENG Yang 3(1. Shandong Provincial Communications Planning and Design Institute Group Co. Ltd., Jinan 250101, China;2. School of Civil Engineering, Southeast University, Nanjing 210096, China;3. School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture,Beijing 100044, China)Abstract: Aiming at the phenomenon that the bridge health monitoring systems contain a large number of收稿日期： 2023 −03 −14；修回日期： 2023 −05 −01基金项目(Foundation item)：山东省交通运输科技计划项目(2021B66)；国家自然科学基金资助项目(51878027)；北京市教委青年拔尖人才培育计划项目(CIT&TCD201904060) (Project(2021B66) supported by the Transportation Technology Program of Shandong Province; Project(51878027) supported by the National Natural Science Foundation of China; Project (CIT&TCD201904060) supported by the Beijing Municipal Education Commission)通信作者：钟国强，博士，高级工程师，从事交通基础设施监测预警研究；E-mail ：*****************DOI: 10.11817/j.issn.1672-7207.2023.12.024引用格式：钟国强, 柳尚, 徐润, 等. 考虑异常监测数据影响的桥梁拉索振动频率识别方法研究[J]. 中南大学学报(自然科学版), 2023, 54(12): 4870−4881.Citation: ZHONG Guoqiang, LIU Shang, XU Run, et al. Vibration frequency identification method of bridge cable considering abnormal monitoring data[J]. Journal of Central South University(Science and Technology), 2023, 54(12): 4870−4881.第 12 期钟国强，等：考虑异常监测数据影响的桥梁拉索振动频率识别方法研究abnormal monitoring data, an identification method for vibration frequencies of bridge cables with the influence of abnormal monitoring data was proposed. Firstly, the approximate band interval of each vibration frequency of the cables was determined according to the distribution characteristics of power spectral density function of normal monitoring data. Peak picking method was adopted to extract the initial identified results of the vibration frequencies of bridge cables automatically in the approximate band intervals. Secondly, a three-dimensional spatial density clustering model was established based on the first three order frequencies. Then, the abnormal values were detected and eliminated from the initial identified results of the vibration frequencies by using the clustering model. The proposed method was verified by using the cable acceleration monitoring data of the Waitan Bridge.The influence of different abnormal monitoring data on identification results of cable frequencies was analyzed.And the detection accuracy of density clustering models with different dimensions on abnormal values of the identified cable frequencies was also investigated. The results show that frequency identification of bridge cables is seriously interfered by abnormal monitoring data. The detection accuracy of three-dimensional spatial density clustering model on the abnormal identified frequencies is more than 98%. In addition, the cable frequency after removing the abnormal identification values shows a reasonable correlation with the ambient temperature.Key words: structural health monitoring; frequency identification; cable; abnormal data; density clustering在大型桥梁结构的健康监测中，桥梁拉索振动响应监测与索力识别至关重要，拉索的受力与工作状态是直接反映桥梁是否处于正常运营的重要标志之一[1−2]。

大型桥梁结构健康监测系统的设计方法-(李惠+欧进萍)

大型桥梁结构健康监测系统的设计方法李惠欧进萍（哈尔滨工业大学土木工程学院）摘要结构智能健康监测愈来愈成为重大工程结构健康与安全的重要保障技术，也愈来愈成为重大工程结构损伤积累、乃至灾害演变规律重要的研究手段。

由于我国重大工程结构建设日新月异、突飞猛进，智能健康监测方法、技术和系统的研究、开发与应用吸引了我国土木工程领域众多科技工作者很大的兴趣和积极的参与，并且得到了快速的发展。

我国是桥梁大国，而桥梁结构是服役性能退化较显著的重大工程之一。

本文首先研究了大型桥梁结构健康监测系统的设计总则，结合与桥梁结构健康监测系统有关的理论、方法和技术，分析了健康监测系统的传感器子系统、数据采集子系统、信号传输子系统、损伤识别与模型修正及安全评定、数据管理子系统及系统集成技术等的设计原则与方法及功能要求；采用上述桥梁健康监测系统设计方法，为山东滨州黄河公路大桥和松花江斜拉桥设计并实现了不同等级的健康监测系统，系统运行表明，所建立的桥梁结构健康监测系统协调运行，系统性能很好。

关键词：桥梁；健康监测系统；光纤光栅传感器；无线传输技术；系统集成；数据库；工程应用Design and implementation of health monitoring systems forcable-stayed bridgesLI Hui OU Jinping(School of Civil Engineering, Harbin Institute of Technology)ABSTRACT The intelligent health monitoring system more and more becomes a technique for ensuring the health and safety of civil infrastructures and also an important approach for research of the damage accumulation or even disaster evolving characteristics of civil infrastructures, and attracts prodigious research interests and active development interests of scientists and engineers since a great number of civil infrastructures are planning and building each year in mainland China. Number of cable-stayed bridges have been constructed and are planning to be constructed in mainland China, however, the performance of cable-stayed bridges deteriorates rapidly in long-term service. General design principles of the health monitoring systems for cable-stayed bridges are studied. The design methods of the sensors, software and hardware of data acquisition module, signal transmission, damage detection, model updating, safety evaluation, database and system integrated technologies are analyzed and the basic functions of the health monitoring systems are pointed out. An on-line health monitoring system for the Shandong Binzhou Yellow River Bridge and an off-line health monitoring system for the Harbin Songhua River Bridge are designed and implemented. The two systems have been running for several months and data measured by these two systems are also presented in this paper.Keywords: cable-stayed bridges; health monitoring systems; optical fiber Bragg-grating sensors; wireless communication techniques; system integration; database; implementation国家自然科学基金重大国际合作研究项目（编号：50410133）的资助1. 前言我国经济正处于高速增长时期，为适应经济建设的需要，我国交通事也得到了大规模的发展，大跨度桥梁的建设方兴未艾，并将在未来仍然保持高速增长。

土木工程专业英语(带翻译)

土木工程专业英语（带翻译）State-of-the-art report of bridge health monitoringAbstractThe damage diagnosis and healthmonitoring of bridge structures are active areas of research in recent years. Comparing with the aerospace engineering and mechanical engineering, civil engineering has the specialities of its own in practice. For example, because bridges, as well as most civil engineering structures, are large in size, and have quite lownatural frequencies and vibration levels, at low amplitudes, the dynamic responses of bridge structure are substantially affected by the nonstructural components, unforeseen environmental conditions, and changes in these components can easily to be confused with structural damage.All these give the damage assessment of complex structures such as bridges a still challenging task for bridge engineers. This paper firstly presents the definition of structural healthmonitoring system and its components. Then, the focus of the discussion is placed on the following sections:①the laboratory and field testing research on the damage assessment;②analytical developments of damage detectionmethods, including (a) signature analysis and pattern recognition approaches, (b) model updating and system identification approaches, (c) neural networks approaches; and③sensors and their optimum placements. The predominance and shortcomings of each method are compared and analyzed. Recent examples of implementation of structural health monitoring and damage identification are summarized in this paper. The key problem of bridge healthmonitoring is damage automatic detection and diagnosis, and it is the most difficult problem. Lastly, research and development needs are addressed.1 IntroductionDue to a wide variety of unforeseen conditions and circumstance, it will never be possible or practical to design and build a structure that has a zero percent probability of failure. Structural aging, environmental conditions, and reuse are examples of circumstances that could affect the reliability and the life of a structure. There are needs of periodic inspections to detect deterioration resulting from normal operation and environmental attack or inspections following extreme events, such as strong-motion earthquakes or hurricanes. To quantify these system performance measures requires some means to monitor and evaluate the integrity of civil structureswhile in service. Since the Aloha Boeing 737 accident that occurred on April28, 1988, such interest has fostered research in the areas of structural health monitoring and non-destructive damage detection in recent years.According to Housner, et al. (1997), structural healthmonitoring isdefined as“the use ofin-situ,non-destructive sensing and analysis ofstructural characteristics, including the structural response, for detecting changes that may indicate damage or degradation”[1]. This definition also identifies the weakness. While researchers have attempted the integration of NDEwith healthmonitoring, the focus has been on data collection, not evaluation. What is needed is an efficient method to collect data from a structure in-service and process the data to evaluate key performance measures, such as serviceability, reliability, and durability. So, the definition byHousner, et al.(1997)should be modified and the structural health monitoring may be defined as“the use ofin-situ,nondestructive sensing and analysis of structural characteristics, including the structural response, for the purpose of identifying if damage has occurred, determining the location of damage, estimatingthe severityof damage and evaluatingthe consequences of damage onthe structures”(Fig.1). In general, a structural health monitoring system has the potential to provide both damage detection and condition assessment of a structure.Assessing the structural conditionwithout removingthe individualstructural components is known as nondestructive evaluation (NDE) or nondestructive inspection. NDE techniques include those involving acoustics, dye penetrating,eddy current, emission spectroscopy, fiber-optic sensors,fiber-scope, hardness testing, isotope, leak testing, optics, magnetic particles, magnetic perturbation, X-ray, noise measurements, pattern recognition, pulse-echo, ra-diography, and visual inspection, etc. Mostofthese techniques have been used successfullyto detect location of certainelements, cracks orweld defects, corrosion/erosion, and so on. The FederalHighwayAdministration(FHWA, USA)was sponsoring a large program of research and development in new technologies for the nondestructive evaluation of highway bridges. One of the two main objectives of the program is todevelop newtools and techniques to solve specific problems. The other is to develop technologies for the quantitative assessment of the condition ofbridges in support of bridge management and to investigate howbest to incorporate quantitative condition information into bridge management systems. They hoped to develop technologies to quickly, efficiently, and quantitativelymeasure global bridge parameters, such as flexibility and load-carrying capacity. Obviously, a combination of several NDEtechniques may be used to help assess the condition of the system. They are very important to obtain the data-base for the bridge evaluation.But it is beyond the scope of this review report to get into details of local NDE.Health monitoring techniques may be classified as global and local. Global attempts to simultaneously assess the condition of the whole structure whereas local methods focus NDE tools on specific structural components. Clearly, two approaches are complementaryto eachother. All such available informationmaybe combined and analyzed by experts to assess the damage or safety state of the structure.Structural health monitoring research can be categorized into thefollowing four levels: (I) detecting the existence of damage, (II) findingthe location of damage, (III) estimatingthe extentof damage, and (IV)predictingthe remaining fatigue life. The performance of tasks of Level (III) requires refined structural models and analyses, local physical examination, and/or traditional NDE techniques. To performtasks ofLevel (IV) requires material constitutive information on a local level, materials aging studies, damage mechanics, and high-performance computing. With improved instrumentation and understanding of dynamics of complex structures, health monitoring and damage assessment of civil engineering structures has become more practical in systematic inspection and evaluation of these structures during the past two decades.Most structural health monitoringmethods under current investigation focus on using dynamic responses to detect and locate damage because they are global methods that can provide rapid inspection of large structural systems.These dynamics-based methods can be divided into fourgroups:①spatial-domain methods,②modal-domain methods,③time-domain methods, and④frequency- domain methods. Spatial-domain methods use changes of mass, damping, and stiffness matrices to detect and locate damage. Modal-domain methods use changes of natural frequencies, modal damping ratios, andmode shapesto detect damage. In the frequency domain method, modal quantities such as natural frequencies, damping ratio, and model shapes are identified.The reverse dynamic systemof spectral analysis and the generalized frequency response function estimated fromthe nonlinear auto-regressive moving average (NARMA) model were applied in nonlinear system identification. In time domainmethod, systemparameterswere determined fromthe observational data sampled in time. It is necessarytoidentifythe time variation of systemdynamic characteristics fromtime domain approach if the properties of structural systemchangewith time under the external loading condition. Moreover, one can use model-independent methods or model-referenced methods to perform damage detection using dynamic responses presented in any of the four domains. Literature shows that model independent methods can detect the existence of damage without much computational efforts, butthey are not accurate inlocating damage. On the otherhand, model-referencedmethods are generally more accurate in locating damage and require fewer sensors than model-independent techniques, but they require appropriate structural models and significant computational efforts. Although time-domain methods use original time-domain datameasured using conventional vibrationmeasurement equipment, theyrequire certain structural information and massive computation and are case sensitive. Furthermore, frequency- and modal-domain methods use transformed data,which contain errors and noise due totransformation.Moreover, themodeling and updatingofmass and stiffnessmatrices in spatial-domain methods are problematic and difficult to be accurate. There are strong developmenttrends that two or three methods are combined together to detect and assess structural damages.For example, several researchers combined data of static and modal tests to assess damages. The combination could remove the weakness of each method and check each other. It suits the complexity of damage detection.Structural health monitoring is also an active area of research in aerospace engineering, but there are significant differences among the aerospace engineering, mechanical engineering, and civil engineering in practice. For example,because bridges, as well as most civil engineering structures, are large in size, and have quite lownatural frequencies and vibration levels, at lowamplitudes, the dynamic responses of bridge structure are substantially affected by the non-structural components, and changes in these components can easily to be confused with structural damage.Moreover,the level of modeling uncertainties in reinforced concrete bridges can be much greater than the single beam or a space truss. All these give the damage assessment of complex structures such as bridges a still challenging task for bridge engineers. Recent examples of research and implementation of structural health monitoring and damage assessment are summarized in the following sections.2 Laboratory and field testing researchIn general, there are two kinds of bridge testing methods, static testing and dynamic testing. The dynamic testing includes ambient vibration testingand forcedvibration testing. In ambient vibration testing, the input excitation isnot under the control. The loading could be either micro-tremors, wind, waves, vehicle or pedestrian traffic or any other service loading. The increasing popularity of this method is probably due to the convenience of measuring the vibrationresponse while the bridge is under in-service and also due to theincreasing availability of robust data acquisition and storage systems. Since the input is unknown, certain assumptions have to be made. Forced vibration testing involves application of input excitation of known force level at known frequencies. The excitation manners include electro-hydraulic vibrators, force hammers, vehicle impact, etc. The static testing in the laboratory may be conducted by actuators, and by standard vehicles in the field-testing.we ca n distinguish that①the models in the laboratory are mainly beams, columns, truss and/or frame structures, and the location and severity of damage in the models are determined in advance;②the testing has demonstrated lots of performances of damage structure s;③the field-testing and damage assessmentof real bridges are more complicated than the models in the laboratory;④the correlation between the damage indicator and damagetype,location, and extentwill still be improved.3 Analytical developmentThe bridge damage diagnosis and health monitoring are both concerned with two fundamental criteria of the bridges, namely, the physical condition andthe structural function. In terms of mechanics or dynamics, these fundamental criteria can be treated as mathematical models, such as response models, modal models and physical models.Instead of taking measurements directly to assess bridge condition, the bridge damage diagnosis and monitoring systemevaluate these conditions indirectly by using mathematical models. The damage diagnosis and health monitoring are active areas of research in recentyears. For example, numerous papers on these topics appear in the proceedings of Inter-national Modal Analysis Conferences (IMAC) each year, in the proceedings ofInternational Workshop on Structural HealthMonitoring (once of two year, at Standford University), in the proceedings of European Conference on Smart materials and Structures and European Conference on Structural DamageAssessmentUsing Advanced Signal Processing Procedures, in the proceedings ofWorld Conferences of Earthquake Engineering, and in the proceedings of International Workshop on Structural Control, etc.. There are several review papers to be referenced, for examples,Housner, et al. (1997)provided an extensive summary of感谢您的阅读，祝您生活愉快。

自锚式悬索桥监测数据分析

1工程概况某桥梁主桥为5跨连续钢桁架桥塔自锚式悬索桥,半漂浮体系,跨径布置40m+90m+220m+90m+40m。

桥梁中跨为220m,主缆垂跨比为1/5.5,主缆在横桥向的间距为36m。

桥面纵坡为双向1%,主桥设半径为11000m的竖曲线。

主梁采用整幅钢箱梁,主桥有索区钢箱梁宽43.3m,配重跨无索区宽40m。

钢箱梁梁高在有索区为3m,配重跨为2.3m,顶板为正交异性板结构。

主缆通过焊接在钢梁上的锚板锚固于主梁上,锚固处梁高局部加厚为4.8m。

主塔在洪水位以上采用钢桁架结构,以下为钢筋混凝土塔座。

桥面以上塔高45.05m,主塔中心横桥向间距为36m,塔座为钢筋混凝土结构。

主缆及吊杆为平面布置,全桥共设两根主缆,横桥向的中心间距为36m。

桥塔侧吊索距桥塔中心线水平距离为11m,其余吊索水平间距为9m。

90m边跨内共设置吊杆7对,220m 主跨内共设置吊杆23对。

结构体系约束情况为:4#、5#、6#、7#桥墩分别设置一个单向支座和一个双向支座;5#、6#支座设置横向限位支座和阻尼器; 3#、8#过渡墩上各设置两个双向支座。

考虑到桥梁结构特殊,综合历年检测情况,为保证桥梁在设计使用寿命内的安全运营,并提升桥梁工程的管理水平,建立了一套功能全面、性能优良、稳定耐久、经济合理的结构健康监测与安全评价系统,以诊断荷载和响应异常情况下可能发生的结构损坏,保证结构的运营安全,在灾难性极端事故发生后,及时提供安全评价的实时材料,并为桥梁检查、养护和自锚式悬索桥监测数据分析Data Analysis of Self-Anchored Suspension Bridge Monitoring李贵祥，杜世康（北京九通衢检测技术股份有限公司，北京100000）LI Gui-xiang,DU Shi-kang(Beijing Jiutongqu Testing Technology Co.Ltd.,Beijing100000,China)【摘要】为保证桥梁在设计使用寿命内的安全运营，某自锚式悬索桥安装了健康监测系统，在监测期间内，利用数据清洗技术，剔除异常数据后，结果表明主梁位移未达到满载设计值，主梁位移状态正常；现场索力增量平均值均未超过预警值，吊索工作状态正常；倾角监测数据正常，风速风向、温湿度环境监测类数据正常，桥梁目前主体受力处于合理范围之内，桥梁运行安全。

毕业设计134南京理工大型桥梁健康监测自动化及安全评估的研究

摘要桥梁健康监测系统是大型桥梁安全保障体系的发展趋势。

本文结合具体的工程项目对实现桥梁结构的监测自动化和安全评估开展了深入研究，提出了自动监测系统的总体设计构思，并完成了相应的软件设计与开发。

基于建立桥梁健康监测系统的目标和功能要求，本文对具体桥型结构的承载特点进行了分析，逐步确立了监测项目并提出了监测系统的构建方案，并对监测系统的工程实施作了较为详细的介绍。

为满足数据采集和数据传输的要求，开发了用于全面控制和设置采集设备的数据采集应用程序，提供现场调试设备、自定义采集模式、调整采样间隔以及远程数据传输等功能。

根据用户需求分析，进行了数据管理与安全评估软件的设计开发，实现了监测数据的分类管理、数据查询的图表显示以及数据的计算处理等功能。

本文还提出了结合层次分析法和人工神经网络算法的安全评估方法，并在软件中集成了相应功能。

关键词：大型桥梁，健康监测，数据采集，安全评估，层次分析法，人工神经网络AbstractBridge Health Monitoring System is the developing trend of long-span bridge safety ensuring system. Associated with the project, the research on monitoring automation and safety evaluation of bridge structure is investigated in this paper. And the program of the whole monitoring system is put forward, the software design and development is also accomplished.Based on the objective and functional requirement of establishing the Bridge Health Monitoring System, the load characteristic of specified bridge style is analyzed and the monitoring program is formed by step in the paper. Moreover, the construction of monitoring system is described in detail.In order to meet the need of data acquisition and data transfer, an application of data acquisition is developed to generally control and configure the acquisition equipment. Supplied functions include testing the equipment, user-defining the acquisition mode, altering the sampling interval, remote data transfer, and so on.According to the user requirement analysis, the computer software implemented data management and safety evaluation has also been designed and developed. It provides classifying management of monitoring data, displaying the query result with chart and table, data calculation and processing, and other functions. A method of safety evaluation combined Analytic Hierarchy Process and Artificial Neural Network algorithms is advanced in the paper, and the corresponding software function is achieved too.Keywords: long-span bridge, health monitoring, data acquisition, safety evaluation, AHP, ANN目录1 绪论 (1)1.1 引言 (1)1.2 桥梁健康监测系统 (2)1.2.1 桥梁健康监测的概念 (2)1.2.2 桥梁健康监测的意义 (2)1.2.3 桥梁健康监测系统的发展 (3)1.2.4 桥梁健康监测系统的构建 (4)1.3 课题来源 (6)1.4 本文主要工作 (6)2 桥梁健康监测系统的总体设计 (7)2.1 自动监测项目的确定 (7)2.2 监测项目方案的制定 (9)2.2.1 拱肋监测方案 (9)2.2.2 拉索监测方案 (9)2.2.3 主梁和桥墩监测方案 (10)2.2.4 风速、温度和湿度监测方案 (11)2.3 数据采集系统的方案制定 (12)2.4 远程数据传输方式的确定 (13)2.5 桥梁自动监测系统的总体方案 (13)3 自动监测系统的实现 (15)3.1 拉索应变监测系统 (15)3.1.1 电阻应变测量原理 (15)3.1.2 传感器布片方案及测量电路 (17)3.1.3 拉索应变监测系统的安装 (17)3.2 主梁、桥墩光纤应变监测系统 (19)3.2.1 光纤应变测量原理 (19)3.2.2 光纤应变传感器对温度不敏感的原理 (21)3.2.3 光纤应变监测系统的安装 (22)3.3 风速、温度和湿度监测系统 (23)3.4 数据采集系统 (24)3.4.1 分布式数据采集模块 (24)3.4.2 数据采集控制站 (25)4 数据采集软件的设计开发 (26)4.1 软件开发平台的选择 (26)4.2 软件开发的关键技术 (27)4.2.1 Visual Basic数据库编程 (27)4.2.2 Visual Basic串行通信编程 (27)4.2.3 Visual Basic网络通信编程 (28)4.2.4 I-7017模块的命令格式 (29)4.3 软件主要功能的程序设计 (30)4.3.1 数据采集功能的设计原理 (30)4.3.2 数据采集功能的流程框图 (31)4.3.3 自动数据采集的设计原理 (32)4.4 数据采集软件的功能和操作介绍 (33)4.4.1 数据采集软件的主要界面 (33)4.4.2 数据采集软件的自动采集功能 (35)4.4.3 数据采集软件的辅助功能 (35)5 数据管理与安全评估软件的设计开发 (40)5.1 软件基本功能的设计思路 (40)5.2 软件基本功能的实现 (40)5.2.1 软件的主要界面 (40)5.2.2 软件的数据管理功能 (41)5.3 软件高级功能的实现 (43)5.3.1 测点数据的趋势分析 (44)5.3.2 测点数据的极限判断 (45)5.3.3 测点数据的突变搜索 (45)5.3.4 测点数据的频谱分析 (46)5.4 桥梁安全评估功能的研究 (47)5.4.1 已有桥梁安全评估方法综述 (47)5.4.2 结合层次分析法和神经网络算法的安全评估方法 (48)5.4.3 安全评估功能的实现 (51)结论 (55)致谢 (56)参考文献 (57)1 绪论1.1 引言大型桥梁的成功建造使“天堑变通途”的梦想成为现实，对改善道路交通状况和促进地区间的经济贸易发展起到了不可替代的作用。

结构健康监测论文：结构健康监测模态分析模态参数识别环境激励

结构健康监测论文：结构健康监测模态分析模态参数识别环境激励【中文摘要】土木工程结构是国家基础设施的重要组成部分,对人民的生活和安全有着直接的影响,所以在桥梁、大坝等大型土木工程结构中安装结构健康监测系统是十分有必要的。

而通过大型的土木工程结构动力特征参数的了解和掌握,可以方便的对其进行全方位的检测、评估和健康监测。

结构的模态参数能够反映出其动力特征,模态参数识别是实验模态分析的核心。

实验模态分析的模态参数识别可以分为两类,即传统的结构模态参数识别方法和环境激励下的结构模态参数识别方法。

两者相比较而言,基于环境激励下的模态参数识别方法能够仅仅利用所测得的响应信号来识别结构的模态参数,是仅基于输出数据的模态参数识别；并且具有无需对结构施加激励,节省人工和设备费用,可以避免对结构产生损伤等优点,因而在工程中得到了广泛的应用。

本文主要研究基于环境激励下桥梁模态参数识别问题。

完成的主要工作如下：(1)对目前国内外桥梁健康监测技术的发展进行了回顾,论述了其重要意义。

以桥梁健康监测技术所涉及的结构动力学层面的问题为切入点,对模态分析这一概念做了简单的概述,并就其核心问题—模态参数的识别进行了较为全面的论述,包括研究现状、已有成果和存在问题等方面。

(2)介绍了实验模态分析的相关原理,重点介绍了信号处理知识和模态参数识别知识：给出了离散傅里叶变换和快速傅里叶变换的推导公式；介绍了模态参数识别中频域方法和时域方法各自的技术路线,并对一些方法的原理、优缺点、流程等进行了研究。

(3)系统地讨论了环境激励情况下模态参数识别的频域方法。

通过对系统结构振动方程的分析,介绍了传统模态参数识别频域方法的表达式以及基本的识别过程。

重点研究了输入未知时正交多项式拟合法的理论背景和计算公式,给出了该方法的一般流程图,并对实验过程中需要注意的问题进行了探讨。

最后进行了数值算例的验证,证明了其有效性和可行性。

(4)为进一步研究正交多项式拟合法基于环境激励下输入未知时的稳定性和适用性,利用该方法应用于工程实例—郑州市南三环立交桥。

干涉型光纤振动传感器定位精度及解调算法研究

太原理工大学博士研究生学位论文干涉型光纤振动传感器定位精度及解调算法研究摘要分布式光纤传感具有本征安全、抗电磁干扰、耐腐蚀、可大范围连续监测等优势，近年来得到了国内外的广泛关注。

振动传感作为分布式光纤传感领域中主要的研究方向之一，在民用设施周界安防、油气管道安全监测、桥梁结构健康监测、军事基地入侵预警等领域具有广阔的应用前景。

干涉型光纤振动传感技术包括前向传输光干涉型和后向散射光干涉型两类。

基于前向传输光干涉型光纤振动传感器，如萨格纳克（Sagnac）干涉仪和马赫泽德（Mach-Zehnder）干涉仪，是将被测的振动信号转换为光纤中前向传输光的相位变化，再通过干涉将相位变化转换成光强变化。

它结构相对简单、响应速度快，但振动定位精度较低。

而后向散射光干涉型光纤振动传感器，如相位敏感光时域反射仪（phase-sensitive optical time domain reflectometer，Φ-OTDR），是利用高相干光脉冲在光纤中传输时产生的后向瑞利散射光的干涉效应，通过建立后向散射光信号与时间的关系获得振动位置信息，其定位精度高，但存在振动信号解调复杂以及实时性不高等问题。

本文围绕干涉型光纤振动传感器的定位精度及解调算法开展研究，主要内容包括：（1）研究了基于混沌光源的Sagnac高精度振动定位系统，利用外腔反馈半导体混沌激光器作为系统光源，再结合振动频谱中的高阶零频点进行定位。

实验了在12.101 km长的传感光纤上22 m的振动定位误差。

太原理工大学博士研究生学位论文（2）研究了基于计数脉冲方法的Mach-Zehnder高精度振动定位系统，将调制后的周期性脉冲序列后注入到干涉结构中，通过分析干涉脉冲序列包络特征定位振动发生的位置。

实验结果表明，当脉冲宽度为20 ns时，在总长940 m的传感光纤长度上，振动定位误差为9 m。

（3）研究了基于包络正交解调算法的Φ-OTDR振动相对振幅表征方法。

大桥结构健康监测系统

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HIGHWAYS DEPARTMENT
TSING MA CONTROL AREA DIVISION BRIDGE HEALTH SECTION
Bridges with WASHMS
• Locations • Bridge Types • Functions • Major Structural Features
Kowloon
Stonecutters Bridge
Lantau Island
Hong Kong Island
HIGHWAYS AREA DIVISION DEPARTMENT
TSING MA CONTROL BRIDGE HEALTH SECTION
7
Tsing Ma Bridge 8
HIGHWAYS DEPARTMENT
SHES
DPCS
Schematic Layout of A Typical WASHMS
19
Flow Chart for Normal Operation of WASHMS
HIGHWAYS DEPARTMENT
TSING MA CONTROL AREA DIVISION BRIDGE HEALTH SECTION
TSING MA CONTROL AREA DIVISION BRIDGE HEALTH SECTION
Kap Shui Mun Bridge 9
Ting Kau Bridge
1
0
HIGHWAYS DEPARTMENT
TSING MA CONTROL AREA DIVISION BRIDGE HEALTH SECTION
1. WASHMS refers to Wind And Structural Health Monitoring System.

桥梁工程英文参考文献(精选118个最新)

桥梁工程指桥梁勘测、设计、施工、养护和检定等的工作过程，以及研究这一过程的科学和工程技术，它是土木工程的一个分支。

桥梁工程学的发展主要取决于交通运输对它的需要。

以下是搜索整理的关于桥梁工程英文参考文献，欢迎借鉴参考。

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Monitoring induced floor vibrations: dance performance and bridge engineering[P]. Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring,2019.[118]Tianshu Li,Devin Harris. Automated construction of bridge condition inventory using natural language processing and historical inspection reports[P]. Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring,2019.以上就是关于桥梁工程英文参考文献的分享，希望对你有所帮助。

润扬大桥结构健康监测系统传感器测点布置_赵翔

Miao Changqing ( Key Lab for RC & PC Structures of Ministry of Education, Southeast University Nanjing 210096)
Abstract : Runyang Yangtse River Highway Bridge is the longest bridge at present, it is practically significant to health monitoring, diagnosis, forecast and evaluation of injury influenced by disasters, during its building and working, also , it is the purpose of the Health Monitoring System of Runyang Bridge. As one of the most important problems of the system, optimum placement of sensor must be sloved rationally. From this point of view, in detail this paper introduces the primary academic gist, which contains analytic result of finite element model and optimum placement of sensor in g irder based on generalized genetic algorithm, and sensor placement for the Health Monitoring System of Runyang Bridge. Keywords : health monitoring sensor optimum placement finite element model generalized genetic algorithm

桥梁主跨挠度监测点布置原则

桥梁主跨挠度监测点布置原则## Bridge Main Span Deflection Monitoring Point Layout Principles.### English Answer:The layout of monitoring points for bridge main span deflection is a crucial aspect of structural health monitoring systems. It involves the strategic placement of sensors to accurately measure the displacement of the bridge under various loading conditions. The principles for the layout of deflection monitoring points include:Span Subdivision: The main span of the bridge is typically divided into approximately equal segments, with monitoring points placed at the mid-point of each segment. This allows for the determination of the deflection profile along the length of the span.Critical Locations: Monitoring points should be placedat locations where the deflections are expected to be maximum, such as the center of the span or near supports. These points are particularly sensitive to changes in the structural behavior.Accessibility and Visibility: The monitoring points should be easily accessible for sensor installation and maintenance. They should also be visible for visual inspection and assessment of the bridge's overall condition.Redundancy: Multiple monitoring points should be used within each segment to provide redundancy and reduce therisk of data loss due to sensor failure or damage.Instrumentation Type: The type of instrumentation used for deflection monitoring, such as inclinometers, strain gauges, or extensometers, should be selected based on the specific requirements of the bridge and the anticipated deflection range.### 中文回答：桥梁主跨挠度监测点布置原则。

基于SVR的桥梁健康监测系统缺失数据在线填补研究

ＺＨＵＦａｎｇ１ꎬＦＵＹｕｍｅｉ２ꎬＣＨＥＮＤｅｂａｏ１∗
(１.ＳｃｈｏｏｌｏｆＰｈｙｓｉｃｓａｎｄＥｌｅｃｔｒｉｃａｌＩｎｆｏｒｍａｔｉｏｎꎬＨｕａｉｂｅｉＮｏｒｍａｌＵｎｉｖｅｒｓｉｔｙꎬＨｕａｉｂｅｉＡｎｈｕｉ２３５０００ꎬＣｈｉｎａꎻ２.ＴｈｅＫｅｙＬａｂｏｒａｔｏｒｙｆｏｒＯｐｔｏｅｌｅｃｔｒｏｎｉｃＴｅｃｈｎｏｌｏｇｙａｎｄＳｙｓｔｅｍｓꎬＭｉｎｉｓｔｒｙｏｆＥｄｕｃａｔｉｏｎꎬＣｏｌｌｅｇｅｏｆＯｐｔｏｅｌｅｃｔｒｏｎｉｃＥｎｇｉｎｅｅｒｉｎｇꎬＣｈｏｎｇｑｉｎｇＵｎｉｖｅｒｓｉｔｙꎬＣｈｏｎｇｑｉｎｇ４０００４４ꎬＣｈｉｎａ)
关键词:支持向量回归ꎻ在线预测ꎻ桥梁健康监测系统ꎻ缺失数据ꎻ序列最小优化算法中图分类号:ＴＰ２７４＋.２文献标识码:Ａ文章编号:１００４－１６９９(２０１８)０５－０７２６－０７
对桥梁的运行状态进行长期在线监测ꎬ能有效掌握桥梁结构的损伤程度ꎬ提前发出事故警告ꎬ降低生命财产损失[１－２] ꎮ 对桥梁所采集的实测数据进行填补的方法主要有传统的时间序列法和人工智能法等[３－５] ꎮ 文献[６]利用高斯粒子滤波器引入贝叶斯法建立了动
Ａｂｓｔｒａｃｔ:Ｔｈｅｒｅａｌ￣ｔｉｍｅｄａｔａｓｅｔｓｃｏｌｌｅｃｔｅｄｂｙｔｈｅｂｒｉｄｇｅｈｅａｌｔｈｍｏｎｉｔｏｒｉｎｇｓｙｓｔｅｍａｒｅｉｎｃｏｍｐｌｅｔｅꎬａｎｄｔｈｅｙｓｅｒｉｏｕｓｌｙａｆｆｅｃｔｔｈｅｓａｆｅｔｙａｓｓｅｓｓｍｅｎｔｏｆｔｈｅｂｒｉｄｇｅ. Ｉｎｔｈｉｓｐａｐｅｒꎬｔｈｅｒｅａｌ￣ｔｉｍｅｏｎｌｉｎｅｐｒｅｄｉｃｔｉｏｎｍｏｄｅｌｏｆｍｉｓｓｉｎｇｄａｔａｉｎｂｒｉｄｇｅｈｅａｌｔｈｍｏｎｉｔｏｒｉｎｇｓｙｓｔｅｍｂａｓｅｄｏｎｓｕｐｐｏｒｔｖｅｃｔｏｒｒｅｇｒｅｓｓｉｏｎ( ＳＶＲ) ｗａｓｐｒｏｐｏｓｅｄ. Ｔｈｅｍｅａｓｕｒｅｄｄａｔａｈａｓｔｈｅｃｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆｔｅｍｐｏｒａｌｉｔｙꎬｎｏｎｌｉｎｅａｒｉｔｙａｎｄｐｅｒｉｏｄｉｃｉｔｙꎬｔｈｅｉｎｐｕｔｓａｍｐｌｅｄｉｍｅｎｓｉｏｎｉｎｓｕｐｐｏｒｔｖｅｃｔｏｒｒｅｇｒｅｓｓｉｏｎｍｏｄｅｌｗａｓｆｉｒｓｔｌｙｒｅｃｏｎｓｔｒｕｃｔｅｄａｃｃｏｒｄｉｎｇｔｏｔｈｅａｕｔｏｃｏｒｒｅｌａｔｉｏｎｏｆｖａｒｉａｂｌｅｓａｎｄｔｈｅｃｏｒｒｅｌａｔｉｏｎａｍｏｎｇｖａｒｉａｂｌｅｓ. ＩｎｏｒｄｅｒｔｏｉｍｐｒｏｖｅｔｈｅａｃｃｕｒａｃｙａｎｄｅｆｆｉｃｉｅｎｃｙｏｆｔｈｅｐｒｅｄｉｃｔｉｏｎｍｏｄｅｌｆｏｒｔｈｅｍｉｓｓｉｎｇｄａｔａｓｅｔｓｏｆｂｒｉｄｇｅꎬｔｈｅＬａｇｒａｎｇｅｍｕｌｔｉｐｌｉｅｒｓｉｎｔｈｅｓｕｐｐｏｒｔｖｅｃｔｏｒｒｅｇｒｅｓｓｉｏｎｍｏｄｅｌａｒｅｕｐｄａｔｅｄｉｎｒｅａｌ￣ｔｉｍｅｂｙｕｓｉｎｇｔｈｅｓｅｑｕｅｎｔｉａｌｍｉｎｉｍｕｍｏｐｔｉｍｉ￣ｚａｔｉｏｎ( ＳＭＯ) ａｌｇｏｒｉｔｈｍａｃｃｏｒｄｉｎｇｔｏｔｈｅｕｐｄａｔｅｄｓａｍｐｌｅｓ. Ｆｉｎａｌｌｙꎬｔｈｅｏｎｌｉｎｅａｄａｐｔｉｖｅｐｒｅｄｉｃｔｉｏｎｍｏｄｅｌｏｆｓｕｐｐｏｒｔｖｅｃｔｏｒｒｅｇｒｅｓｓｉｏｎｍｏｄｅｌｉｓｐｕｔｆｏｒｗａｒｄａｎｄｒｅａｌｉｚｅｄｉｎｔｈｅｐｒａｃｔｉｃａｌｐｒｏｂｌｅｍｓ. Ｔｈｅｍｅａｓｕｒｅｄｍｉｓｓｉｎｇｄａｔａｏｆｂｒｉｄｇｅａｒｅｐｒｅｄｉｃｔｅｄｂｙｏｎｌｉｎｅｍｏｄｅｌａｎｄｏｆｆ￣ｌｉｎｅｍｏｄｅｌꎬｔｈｅｅｘｐｅｒｉｍｅｎｔａｌｒｅｓｕｌｔｓｓｈｏｗｔｈａｔｔｈｅｏｎｌｉｎｅｍｏｄｅｌｃａｎａｃｈｉｅｖｅｈｉｇｈｅｒｐｒｅｄｉｃｔｉｏｎａｃｃｕｒａｃｙｉｎｔｈｅｆｕｔｕｒｅｂｙｕｐｄａｔｉｎｇｔｈｅｓａｍｐｌｅｓ. Ｋｅｙｗｏｒｄｓ:ｓｕｐｐｏｒｔｖｅｃｔｏｒｒｅｇｒｅｓｓｉｏｎꎻｏｎｌｉｎｅｐｒｅｄｉｃｔｉｏｎꎻｂｒｉｄｇｅｈｅａｌｔｈｍｏｎｉｔｏｒｉｎｇｓｙｓｔｅｍꎻｍｉｓｓｉｎｇｄａｔａꎻｓｅｑｕｅｎｔｉａｌｍｉｎｉｍａｌｏｐｔｉｍｉｚａｔｉｏｎ( ＳＭＯ) ａｌｇｏｒｉｔｈｍＥＥＡＣＣ:７２２０ｄｏｉ:１０.３９６９ / ｊ.ｉｓｓｎ.１００４－１６９９.２０１８.０５.０１３

基于监测数据的斜拉桥基准有限元模型修正

［摘要］大跨度桥梁由于在交通运输中的重要作用，其安全性已成为人们所关心的热点问题。近年来，桥梁健康监测系
统得到了广泛的研究与应用，对于桥梁的长期监测和状态评估一个准确有效的基准有限元模型是不可或缺的。本文基于上海长
江大桥主航道斜拉桥健康监测系统的监测数据，对建立的初始有限元模型进行修正，得到更符合桥梁真实状况的基准有限元
模型。
［关键词］监测数据；斜拉桥；模态分析；基准模型
［中图分类号］Ｕ４４８．２７；Ｕ４４６
［文献标志码］Ａ
［文章编号］１００１—５２３Ｘ（２０１８）１８＿ｏ１０４＿Ｊ０２
ＢａｓｅｌｉｎｅＭｏｄｅｌＵｐｄａｔｉｎｇｏｆＣａｂｌｅ－ｓｔａｙｅｄＢｒｉｄｇｅＢａｓｅｄｏｎＭｏｎｉｔｏｒｉｎｇＤａｔａ
上海长江大桥斜拉桥初始有限元模型采用ＡＮＳＹＳ大型结行对比如表１所示，计算的结构前八阶的竖弯频率与实测频
构分析通用程序，建立空间有限元模型。由于上海长江大桥率比较吻合，最大误差为三阶竖弯一５．１０％；而横弯频率与实
是分离式双主梁的结构形式，因此有限元建模采用双主梁模测频率相差较大，一阶二阶横弯频率与实测值的误差分别为型，主梁、主塔、边墩和辅助墩均采用ＢＥＡＭ４单元；斜拉索１２．０２％，１３．８８％；扭转频率与实测值吻合较好，前两阶扭转频采用ＬＩＮＫ８单元；二期恒载和压重采用ＭＡＳＳ２１质量单元。率与实测值误差分别为＿３．７５％．１．０４％。

新型公路桥梁健康监测与安全预警云平台设计及应用

doi: 10.3969/j.issn.1673-6478.2023.03.022新型公路桥梁健康监测与安全预警云平台设计及应用贺效鹏 1，郑益斌2，罗晓玲1，张艳1（1. 厦门卫星定位应用股份有限公司，福建厦门，361008；2. 厦门万宾科技有限公司，福建厦门，361008）摘要：基于公路桥梁健康监测在实际工程应用中存在的监测终端布设困难、采集方式与传输方式较为落后等问题，本文采取“前端优化、后端升级”的模式进行优化研究，轻量化公路桥梁健康监测的系统性应用，体系化解决公路桥梁安全运营难题。

通过融合前端新一代公路桥梁智能监测仪器、升级后端以云平台为核心的公路桥梁健康监测与安全预警系统，搭建形成集公路桥梁AIoT 开放平台（PaaS ）、公路桥梁健康监测与安全预警系统（SaaS ）于一体的新型公路桥梁健康监测与安全预警云平台，以全面保障公路桥梁的安全运行。

关键词：公路桥梁；健康监测；安全预警中图分类号：U446文献标识码：A文章编号：1673-6478（2023）03-0123-05Design and Application of a New Cloud Platform for Highway Bridge Health Monitoringand Safety WarningHE Xiaopeng 1, ZHENG Yibin 2, LUO Xiaoling 1, ZHANG Yan 1(1. Xiamen Gnss Development & Application Co., Ltd., Xiamen Fujian 361008, China; 2. Xiamen WitbeeTechnology Co., Ltd., Xiamen Fujian 361001, China)Abstract: Based on the difficulties in the layout of monitoring terminals and the relatively backward collection and transmission modes in the practical engineering application of highway bridge health monitoring, this paper adopts the mode of "front-end optimization and back-end upgrade" to conduct optimization research, and systematically solves the safety operation problems of highway bridge through the systematic application of lightweight highway bridge health monitoring. A new highway bridge health monitoring and safety early warning cloud platform integrating highway bridge AIoT open platform (PaaS) and highway bridge health monitoring and safety early warning system (SaaS) is built by integrating a new generation of highway bridge intelligent monitoring instruments at the front end and upgrading the highway bridge health monitoring and safety early warning system at the back end. To guarantee the safety of highway bridge operation. Key words: highway bridge; health monitoring; safety warning0 引言桥梁是公路基础设施建设的重要组成部分，桥梁健康监测是复杂的系统性工程。

公路桥梁健康监测与安全预警研究

公路桥梁健康监测与安全预警研究Study on Health Monitoring and Safety Warning of Highway Bridges吕强（合肥市正茂科技有限公司，合肥230088）LV Qiang(Zenmorn (Hefei)Technology Co.Ltd.,Hefei 230088,China)【摘要】很多公路桥梁随着运营时间的增加出现了严重的功能退化，致使安全隐患增多，因此，需要注重公路桥梁健康监测与安全预警研究。

论文对公路桥梁健康监测研究进行概述，介绍了适应于一般公路桥梁安全预警监测体系，在传统“桥梁健康监测体系”的基础上，结合当代高新技术，提出来适合大多数公路桥梁的“安全预警监测内容与评判体系”，并对系统应用中的公路桥梁安全预测点的布置进行了详细介绍。

【Abstract 】With the increase of operation time,many highway bridges have serious functional degradation,resulting in increased safety risks.Therefore,it is necessary to pay attention to health monitoring and safety warning research of highway bridges.This paper summarizes the research of highway bridge health monitoring,and introduces the early warning and monitoring system adapted to the general highway bridge safety.Based on the traditional “bridge health monitoring system ”and combining with modern high and new technology,the “safety early warning monitoring content and evaluation system ”suitable for most highway bridges is put forward,and the layout of safety prediction points in thesystem isintroduced in detail.【关键词】公路桥梁；健康监测；安全预警【Keywords 】highwaybridge;health monitoring;safetyearlywarning 【中图分类号】U446【文献标志码】A【文章编号】1007-9467（2022）01-0046-03【DOI 】10.13616/ki.gcjsysj.2022.01.214【作者简介】吕强（1980~），男，安徽亳州人，工程师，从事机电工程研究。