钢管混凝土拱桥吊杆损伤分布式识别

随着工程结构的日益大型化和复杂化,结构损伤检测时需要布置大量的传感器.传统的集中采集和处理的技术将难以胜任海量数据的处理要求.有利于降低成本,密集布置的无线智能传感器就成为大型结构健康监测系统的最佳选择.采用分布式损伤识别方法是密集布排的无线传感测试系统的必然要求.针对拱桥吊杆损伤的问题提出应用于无线传感网络的分布式识别技术.以一混凝土钢管拱桥为实验平台,松动吊杆端部锚具制造不同程度的松弛损伤,对损伤前后拱桥进行振动测试,按照网络拓扑情况,利用功率谱密度曲率差法进行损伤识别分析.结果表明:分布式损伤识别技术能够成功识别拱桥吊杆损伤,并且该方法可以应用到其他密集布排无线传感器的大型复杂结构的健康监测和检测中.     

数字图像相关技术在结构损伤检测中的应用

结构损伤识别技术是结构健康监测的核心技术,也是健康监测的重难点之一。工程测量中受测量环境和技术的影响,很难获得完备的实验数据。论文利用一种新型测量技术,数字图像相关性(Digital Image Correlation,以下简称"DIC")技术,来提高模态应变能的识别精度。首先运用DIC技术和传统加速度传感器两种测量手段来获取固有频率和模态振型,实验结果表明,DIC技术获取的频率和振型与加速度传感器基本一致;随后对网壳结构进行基于DIC的模态应变能损伤识别分析,参数识别法获得模态振型及利用振型拟合得到的转角代入损伤识别指标进行损伤识别,结果表明,基于DIC的模态应变能损伤识别法能够有效进行损伤定位识别,且识别精度较好。     

基于ARMAX模型和稀疏正则化的结构损伤识别方法

结构健康监测系统对于保障工程结构安全具有重要意义,而结构损伤识别方法是结构健康监测系统的关键组成部分.本文提出一种基于时间序列ARMAX模型和稀疏正则化的结构损伤识别方法.首先,建立与结构运动方程对应的ARMAX模型,并利用模型自回归系数提取结构的固有频率和振型;然后,将提取的结构模态参数作为损伤敏感特征,构建损伤识别...     

环境激励下钢板组合梁桥模态参数识别

结构模态参数识别是结构健康监测领域的重点研究问题之一,主要应用于结构损伤识别、安全评估、模型修正等多个方面。文章以一座四跨连续钢板组合梁桥为例,根据设计图纸,利用SAP2000有限元软件建立其初始有限元模型。根据健康监测系统采集得到的加速度时程数据,分别利用随机子空间方法(SSI)和基于离散解析模式分解方法(DAMD)对实际结构的频率、振型、阻尼比进行识别,并将识别结果和有限元法计算结果进行对比。研究结果表明,文章所述的两种参数识别方法对桥梁固有频率均有较好的识别效果,对于所测得的加速度响应时程较短的工况条件下,利用基于离散解析模式分解的方法相比于传统随机子空间方法可以更准确地识别出桥梁结构的阻尼比。     

基于分布式同步采集的赛格大厦结构动力学参数识别

在大型复杂工程结构上进行现场模态测试时,由于结构规模体量大并存在空间隔断,导致数据采集设备与传感器之间快速布设数据传输线困难。因此,有必要解决不同位置分布式同步采集设备时间精确同步问题,研发易于快速安装的分布式数据采集和无线传输设备。为此,提出基于“北斗”卫星授时的结构振动分布式同步采集算法,集成分布式同步采集硬件与研发数据在线采集和无线传输软件,获取大型复杂工程结构不同空间位置时间同步动态响应,基于随机子空间算法自动识别工程结构服役状态下真实的模态参数。在赛格大厦振动事件溯源工作中,该系统成功捕捉到5月20日12:00—13:00结构共振时第69层与桅杆底部的加速度响应,发现四次共振均以频率2.12 Hz振动主导。基于该系统在环境激励条件下的现场模态测试,识别结构前19阶动力学参数,发现频率2.12 Hz是主体结构弯扭耦合和桅杆面内对称振动模态。基于现场激振测试识别频率2.12 Hz对应的阻尼比,发现阻尼比随着振幅的增加突然减小然后逐步增加,较低的阻尼比是导致赛格大厦发生共振的原因之一。     

土木工程健康监测无线测试信号同步性研究(Ⅱ)

无线传感技术应用到土木工程结构健康监测系统中需解决的重要问题之一,是传感器在数据采集过程中的同步性问题。本文从时延误差的产生入手,用频域内的峰值拾取法(PP)和时域内的特征系统实现算法(ERA),通过理论分析和数值模型实验考察了不同算法识别的结构动力参数的精度以及对包含时延的测试数据的处理情况,以此来判断其对整体结构分析带来的误差,并针对不同的系统识别方法提出了处理意见。     

土木工程健康监测无线测试信号同步性研究(Ⅰ)

无线传感技术应用到土木工程结构健康监测系统中需解决的重要问题之一,是传感器在数据采集过程中的同步性问题.本文从时延误差的产生入手,用频域内的峰值拾取法(PP)和时域内的特征系统实现算法(ERA),通过理论分析和数值模型实验考察了不同算法识别的结构动力参数的精度以及对包含时延的测试数据的处理情况,以此来判断其对整体结构分析带来的误差,并针对不同的系统识别方法提出了处理意见.     

Structural dynamic parameter identification of Saige building based on distributed synchronous acquisition method

在大型复杂工程结构上进行现场模态测试时，由于结构规模体量大并存在空间隔断，导致数据采集设备与传感器之间快速布设数据传输线困难。因此，有必要解决不同位置分布式同步采集设备时间精确同步问题，研发易于快速安装的分布式数据采集和无线传输设备。为此，提出基于“北斗”卫星授时的结构振动分布式同步采集算法，集成分布式同步采集硬件与研发数据在线采集和无线传输软件，获取大型复杂工程结构不同空间位置时间同步动态响应，基于随机子空间算法自[JP2]动识别工程结构服役状态下真实的模态参数。在赛格大厦振动事件溯源工作中，该系统成功捕捉到5月20日12:00—13:00[JP]结构共振时第69层与桅杆底部的加速度响应，发现四次共振均以频率2.12 Hz振动主导。基于该系统在环境激励条件下的现场模态测试，识别结构前19阶动力学参数，发现频率2.12 Hz是主体结构弯扭耦合和桅杆面内对称振动模态。基于现场激振测试识别频率2.12 Hz对应的阻尼比，发现阻尼比随着振幅的增加突然减小然后逐步增加，较低的阻尼比是导致赛格大厦发生共振的原因之一。     

粒子群算法在网架结构损伤识别中的应用研究

粒子群算法作为新兴的智能优化算法,因其处理优化问题突出已逐步应用在结构损伤检测领域,基于粒子群算法,提出了网架结构损伤识别方法。首先利用模态保证准则(MAC),结合频率和振型在损伤识别中各自的优势,构造了基于频率和振型的适应度函数;其次,以两个测试函数来对比分析,说明改进的粒子群算法寻优性能更佳;最后,通过一个网架结构仿真模型算例,对所提方法的有效性进行验证。设置了3种工况进行损伤识别并对结果进行分析,结果表明基于粒子群算法的损伤识别方法能够准确识别出损伤发生的位置及程度。     

基于MATLAB的结构模态分析与损伤识别系统软件开发

为采集反应结构服役状况的相关数据,发现结构的损伤并评估其安全性,本文研究了空间网格结构健康监测系统的设计和具体实现方法,阐述了空间网格结构健康监测系统的基本组成和监测内容,将健康监测系统开发的重点放在数据处理、模态分析和损伤识别等模块上,成功地开发了一套基于MATLAB的结构模态分析与损伤识别系统(Structural Modal Analysis and Damage Identification System-SMADIS 1.0)。软件主要功能包括:环境振动实测数据的预处理、时频域数据分析、模态参数识别、结果后处理及振型动画显示、模型缩聚和实测振型扩充、有限元模型修正、有限元数据提取、损伤定位及评估等。结果表明:整个软件系统采用模块化的程序设计理念,具有功能全面、界面友好、灵活实用和可继承性等特点,值得在结构健康监测领域进行推广。     

A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures

Automatic health monitoring and maintenance of civil infrastructure systems is a challenging area of research. Nondestructive evaluation techniques, such as digital image processing, are innovative approaches for structural health monitoring. Current structure inspection standards require an inspector to travel to the structure site and visually assess the structure conditions. A less time consuming and inexpensive alternative to current monitoring methods is to use a robotic system that could inspect structures more frequently. Among several possible techniques is the use of optical instrumentation (e.g. digital cameras) that relies on image processing. The feasibility of using image processing techniques to detect deterioration in structures has been acknowledged by leading experts in the field. A survey and evaluation of relevant studies that appear promising and practical for this purpose is presented in this study. Several image processing techniques, including enhancement, noise removal, registration, edge detection, line detection, morphological functions, colour analysis, texture detection, wavelet transform, segmentation, clustering and pattern recognition, are key pieces that could be merged to solve this problem. Missing or deformed structural members, cracks and corrosion are main deterioration measures that are found in structures, and they are the main examples of structural deterioration considered here. This paper provides a survey and an evaluation of some of the promising vision-based approaches for automatic detection of missing (deformed) structural members, cracks and corrosion in civil infrastructure systems. Several examples (based on laboratory studies by the authors) are presented in the paper to illustrate the utility, as well as the limitations, of the leading approaches.     

Health monitoring of flexural steel structures based on distributed fibre optic sensors

In our previous study, a distributed long-gauge fibre optic sensing system (with the ability to obtain effective average strain, or macro-strain, distributions) for practical adaptation in civil structural health monitoring was developed and verified. The present paper is devoted to proposing an integrated health monitoring scheme for elastic beam-like structures, where flexure dominates structural responses, based on static testing and measurements using the developed sensors. A series of experimental investigations on steel beams with different levels of damage are first carried out. The static strain measurements from distributed sensors are characterised and some concerns on the data processing and feature extraction are discussed. On the basis of the extracted features, structural health monitoring (SHM) investigations are deployed in three parts: damage identification with no requirement for a structural analytical model, parametric estimation based on finite element (FE) models, and evaluation of structural global behaviour. By comparing to traditional transducers such as linear variable displacement transducers (LVDTs) and foil ‘point’ strain gauges, the ability and ascendancy of the sensors developed here for SHM purposes are verified. A comprehensive health monitoring strategy for steel flexural structures based on the distributed strain sensors array is proposed finally.     

Health monitoring system of a self-anchored suspension bridge (planning,design and installation/operation)

Recent advances in sensing technologies make it feasible and practic al to install sensors on expensive civil infrastructures, such as bridges, for safety monitoring during construction and long-term assessment of the structures condition. This paper presents a case study of a structural health monitoring (SHM) and bridge management system (BMS) installed in Yeongjong Bridge in South Korea. This is a self-anchored suspension bridge on the expressway that links Seoul to Incheon International Airport. Experimental data have been collected from the bridge for two years, since its completion in 2000. This paper presents a list of examples where the structural health monitoring system can be applied and provides general guidelines and recommendations for deploying a monitoring system in terms of (1) sensing and instrumentation, (2) data collection and signal processing, and (3) information processing.     

光纤传感器在土木工程健康监测中的应用

总结了当前土木工程结构健康监测的研究和发展趋势。重点回顾了光纤传感器在各种主要土木结构中的健康监测,包括建筑物、桩、桥、管道、隧道和大坝。描述了光纤传感器的三种用途。最后,讨论了在土木结构健康监测中封装和实现光纤传感器存在的问题和有前途的研究方向。     

福州海峡国际会展中心结构健康监测系统设计与分析研究

结构健康监测已成为重大建筑结构工程安全监测重要技术手段,是当前土木工程界研究热点。福州海峡国际会展中心结构健康监测系统包括了四大系统:传感器系统、数据采集和传输系统、数据处理及控制系统和结构健康评估系统。研究总体的设计原则和各子系统设计原则和方法,给出了基于钢屋盖结构体系的安全评估方法。     

Zuverlässigkeitsorientierte Bewertung von Bauwerken auf Grundlage der Bauwerksüberwachung

Reliability‐based system assessment of civil engineering structures based on structural health monitoring The safety and usability of transport infrastructure is of great importance for the entire society, because disturbances of traffic networks can have significant financial and environmental consequences. Especially in times when bad news about deteriorated structures and shortened public budgets are omnipresent, innovated solutions are in demand. Structural health monitoring (SHM) can help to assess the safety of deteriorated structures. With the help of suitable monitoring strategies the service life, which may elapse up to a renovation or a renewal without endangering the users, can be determined. So far however a regular monitoring of buildings – with few exceptions – did not become generally accepted yet, above all because it is time‐consuming and expensive. Owing to world‐wide research and development in this field however inspection and monitoring strategies can be optimized meanwhile in such a way becoming attractive for various applications. Innovative methods for structural health monitoring (SHM) are developed by the Collaborative Research Centre (CRC) 477 at the Braunschweig University of Technology. In project field A1 a framework for the probabilistic safety assessment of structures based on data from SHM is developed. This paper describes and explains the methodology of the framework and shows its application using a substitute structure of the CRC 477 as an example.     

智能结构系统--减灾防灾的研究前沿

具有仿人智能功能与生命特征的土建结构是人类长期的梦想,由于信息、材料与工程科技的进步,这一梦想可能变为现实.本文提出了智能结构系统的概念和定义,强调了它在减灾防灾中的重大意义与作用.概述了土建结构健康监测与结构响应控制的研究动向.简要介绍了重庆大学在这一领域中的研究工作,并提出了"十五"期间应当研究的主要课题.     

分布式光纤混凝土梁应变测试研究

分布式光纤由于其长距离、分布式、实时在线监测,适用于大坝、水闸等土木工程结构的健康监测。文中在梁纵向钢筋、混凝土梁外表面分别布置分布式光纤传感器,判定混凝土梁开裂荷载及裂缝分布。研究结果表明:分布式光纤传感器能够对RC梁结构应变、裂缝进行准确的监测;分布式光纤传感器进行结构健康监测是可行的。     

Image analyses for video-based remote structure vibration monitoring system

Video-based vibration measurement is a cost-effective way for remote monitoring the health conditions of transportation and other civil structures, especially for situations where accessibility is restricted and does not allow installation of conventional monitoring devices. Besides, video-based system is global measurement. The technical basis of video-based remote vibration measurement system is digital image analysis. Comparison of the images allow the field of motion to be accurately delineated. Such information is important to understand the structure behaviors including the motion and strain distribution. This paper presents system and analyses to monitor the vibration velocity and displacement field. The performance is demonstrated on a testbed of model building. Three different methods (i.e., frame difference method, particle image velocimetry, and optical Flow Method) are utilized to analyze the image sequences to extract the feature of motion. The Performance is validated using accelerometer data. The results indicate that all three methods can estimate the velocity field of the model building, although the results can be affected by factors such as background noise and environmental interference. Optical flow method achieved the best performance among these three methods studied. With further refinement of system hardware and image processing software, it will be developed into a remote video based monitoring system for structural health monitoring of transportation infrastructure to assist the diagnoses of its health conditions.     

Real-time remote monitoring: the DuraMote platform and experiments towards future,advanced, large-scale SCADA systems

The economic and social prosperity of our society depends much on the proper functioning of structures and civil infrastructure systems. Structural health monitoring has been long recognised as a vital tool to preclude and/or mitigate degradation effects and failures of structural systems. Along this line, the DuraMote platform is presented in this paper (named after Durable and Mote) together with real-life applications, laboratory and field experiments, which promote the effort to expand the existing concept of structural monitoring into remote, real-time, continuous and permanent performance monitoring of spatially extended systems. Successful implementation of this technology can improve the resilience and sustainability of large-scale complex infrastructure systems and lead to future, advanced Supervisory Control and Data Acquisition methodology that could be routinely used in a variety of structures and networks.