光纤健康监测方法在土木工程中的研究与应用进展

在土木工程领域，光纤智能健康监测方法是对建筑物或构筑物的健康状况进行检测的一种新方法。本文首先论述了光纤智能健康监测系统的构成，然后对国内外光纤健康监测系统在土木结构中的研究与应用进行了回顾，介绍了光纤传感器的种类、原理、特点和当前应用的状况，重点介绍了光纤位移传感器和布拉格光栅（Bragg grating)应变传感器，最后展望了光纤智能健康监测方法在土木结构中的应用前景。     

基础隔震结构健康监测系统的设计与实现(Ⅱ):系统实现

作为保障工程安全和研究结构灾变机理的重要手段,结构健康监测为研究基础隔震技术在实际工程应用中的问题提供了技术保证。基于"基础隔震结构健康监测系统的设计与实现(Ⅰ):系统设计"中的设计方法,研究某超长基础隔震结构健康监测系统的总体设计、传感器选型与测点布设、数据采集与传输方案及数据库结构设计,并对该系统已获取的监测数据进行初步分析。分析结果表明,该基础隔震结构健康监测系统协调运行状态良好,能实现其预期功能。基于性能状态评价指标对该结构状态进行评价,表明该基础隔震结构性能状态良好。     

基于NEESit的结构健康监测系统软件框架研究

为满足结构健康监测系统实际应用的需要,本文设计了一套基于NEESit的结构健康监测系统软件框架.在实际健康监测系统设计和实现的基础上研究了系统的集成技术,结合软件框架开发技术给出了本软件框架的设计和实现的方法,同时介绍了NEESit的组成和运行机制,并提出采用NEESit的相应功能模块来实现本软件框架.本软件框架具有良好的通用性,不仅可以用于各种健康监测系统的开发,同时还可以使实际结构与NEES进行数据共享、互相访问以及协同实验.     

苏通大桥结构健康监测系统设计

介绍了苏通大桥结构健康监测系统研究的主要成果,分析了大跨径桥梁健康监测研究的关键问题.苏通大桥结构健康监测系统主要由四个子系统组成:(1)传感器系统(SS);(2)数据采集与传输系统(DATS);(3)数据管理与控制系统(DMCS);(4)结构健康评估系统(SHES).其中,结构健康评估系统是苏通大桥结构健康监测和安全评价系统的核心内容.结构健康评估系统由五个模块组成:(1)桥梁评级系统;(2)适用性评估;(3)损伤诊断和预测;(4)耐久性评估;(5)安全性评估.文中较为系统地论述了目前大跨桥梁健康监测系统建立与研究中的主要问题,指出了研究结构健康评估系统的主要技术途径,阐述了大跨桥梁健康监测系统存在的问题和发展方向.     

土木工程结构安全性评估、健康监测及诊断述评

阐述了土木工程结构的安全性评估、健康监测及损伤诊断的必要性和迫切性，系统论述了结构健康监测和诊断的概念、理论和方法，重点讨论了传感器的优化布置、损伤识别等健康监测中的关键问题，介绍了光纤等新型传感器的应用情况，最后指出了值得进一步研究的问题。     

深圳市民中心屋顶网架结构支撑钢牛腿瞬时应力场的识别

结构健康智能监测是当前国内外土木工程界新的研究热点和难点，具有重要的理论和工程应用价值。本文以深圳市民中心屋顶网架结构的智能监测系统为实际应用背景，系统地阐述了网架结构支撑钢牛腿基于神经网络的瞬时应力场识别方法及关键点工作状态评估与多级报警的方法。     

基础隔震结构健康监测系统的设计与实现(Ⅰ):系统设计

在医院、教学楼等建筑中广泛采用隔震技术,能降低地震对上部结构的破坏作用。虽然隔震技术经过几十年的发展已趋于成熟,但环境及其他荷载对隔震结构性能的影响规律、结构设计的合理性以及震后结构状态评估等问题,仍需建立隔震结构健康监测系统对施工、运营期的结构响应进行监测,并对其进行评估与验证。首先,针对基础隔震结构的特点,研究了基础隔震结构的主要监测内容;在此基础上提出基础隔震结构健康监测系统的总体设计要求及原则,根据不同监测对象(整体与局部监测量)给出基础隔震结构传感器布置原则和数据采集系统软硬件设计原则,提出基础隔震结构设计验证与安全评定方法;最后给出基础隔震结构健康监测值得进一步研究的问题。     

声发射技术在桥梁结构健康监测中的应用研究进展

声发射技术作为一种被动的、动态的监测手段,在工程和材料领域得到了广泛的应用,正日益受到桥梁结构健康监测研究者的关注。本文回顾了近年来国内外基于声发射技术的桥梁结构健康监测研究状况。首先,简要介绍了声发射的基本原理和声发射信号处理方法;其次,详细分析了声发射技术在桥梁结构健康监测中的研究成果,包括钢筋混凝土桥、钢结构桥、桥梁结构关键构件和无线声发射传感器及其网络等;最后,分析了声发射技术在桥梁结构健康监测领域应用中存在的一些问题,并对声发射技术的应用前景进行了探讨。     

桥梁健康监测及诊断研究综述

本文分析了桥梁结构健康监测和诊断的必要性和紧迫性，对桥梁结构损伤探测的方法进行了详细的分类及论述。提出了桥梁健康监测和诊断的研究新领域——无线监测系统。最后指出了桥梁健康监测和诊断中存在的问题及发展趋势。     

基于结构振动信息的损伤识别研究综述

随着传感技术、信号采集与处理和系统建模等技术的发展,基于结构振动信息的损伤识别已经成为土木工程结构健康监测与损伤检测领域的研究热点。本文系统地综述了近20年来国内外基于振动信息的结构损伤识别的研究和应用现状,评述了各类方法的优缺点,并针对土木工程结构损伤识别的特点,对有待于进一步研究的问题进行了展望。     

LMS‐based structural health monitoring of a non‐linear rocking structure

A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. This research directly identifies changes in structural stiffness due to modelling error or damage for a post‐tensioned pre‐cast reinforced concrete frame building with rocking beam column connections and added damping and stiffness (ADAS) elements. A structural health monitoring (SHM) method based on adaptive least mean squares (LMS) filtering theory is presented that identifies changes from a simple baseline model of the structure. This method is able to track changes in the stiffness matrix, identifying when the building is (1) rocking, (2) moving in a hybrid rocking–elastic regime, or (3) responding linearly. Results are compared for two different LMS‐based SHM methods using an L ₂ error norm metric. In addition, two baseline models of the structure, one using tangential stiffness and the second a more accurate bi‐linear stiffness model, are employed. The impact of baseline model complexity is then delineated. The LMS‐based methods are able to track the non‐linearity of the system to within 15% using this metric, with the error due primarily to filter convergence rates as the structural response changes regimes while undergoing the El Centro ground motion record. The use of a bi‐linear baseline model for the SHM problem is shown to result in error metrics that are at least 50% lower than those for the tangential baseline model. Errors of 5–15% with this L ₂ error norm are fairly stringent compared to the greater than 2 × changes in stiffness undergone by the structure, however, in practice the usefulness of the results is dependent on the resolution required by the user. The impact of sampling rate is shown to be negligible over the range of 200–1000Hz, along with the choice of LMS‐based SHM method. The choice of baseline model and its level of knowledge about the actual structure is seen to be the dominant factor in achieving good results. The methods presented require 2.8–14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2005 John Wiley & Sons, Ltd.     

润扬斜拉桥有限元模拟及模态分析

本文主要研究润扬长江大桥北汊斜拉桥以结构健康监测和状态评估为目标的空间有限元模型建立过程中的一些基础性问题。在建模过程中,尽可能多地考虑了一些影响全桥有限元模型精度的因素:如斜拉索的几何非线性(重力垂度和初始应力),将构造正交各向异性钢箱梁桥面板用复合材料力学的方法等效为物理正交各向异性板等。然后应用所建立的有限元模型进行模态分析,最后将有限元模态计算结果与环境振动试验结果进行比较,验证了润扬斜拉桥有限元模型的有效性。由此建立的有限元模型可以为该桥的结构健康监测和状态评估提供分析的基础。     

Design and application of structural health monitoring system in long-span cable-membrane structure

Cable-membrane structures have small rigidity and are highly sensitive to wind. Structural health monitoring is necessary to ensure the serviceability and safety of the structure. In this research, the design method of a structural health monitoring system is using the characteristics of a cable-membrane structure. Taking the Yueyang Sanhe Airport Terminal as an example, a finite element model is established to determine the critical structural components. Next, the engineering requirements and the framework of the monitoring system are studied based on the results of numerical analysis. The specific implementation of the structural health monitoring is then carried out, which includes sensor selection, installation and wiring. The proposed framework is successfully applied to the monitoring system for the Yueyang Airport terminal building, and the synchronous acquisition of fiber Bragg grating and acceleration sensor signals is implemented in an innovative way. The successful implementation and operation of structural health monitoring will help to guarantee the safety of the cablemembrane structure during its service life.     

1D system identification of buildings during earthquakes by seismic interferometry with waveform inversion of impulse responses—method and application to Millikan library

Two new algorithms have been introduced as a further development of a robust interferometric method for structural health monitoring (SHM) of buildings during earthquakes using data from seismic sensors. The SHM method is intended to be used in an automatic seismic alert system, to issue a warning of significant damage during or immediately after the earthquake, and facilitate decision making on evacuation, to avoid loss of life and injury from possible collapse of the weekend structure during aftershock shaking. The method identifies a wave velocity profile of the building by fitting an equivalent layered shear beam model in impulse response functions (virtual source at roof) of the recorded earthquake response. The structural health is monitored by detecting changes in the identified velocities in moving time windows, the initial window being used as reference. Because the fit involves essentially matching phase difference between motion at different floors, the identified velocity profile is not affected by rigid body rocking, and soil-structure interaction in general, as demonstrated in this paper. Consequently, detected changes in wave velocity during an earthquake are not affected by changes in the soil-foundation system, which is a major advantage over SHM by detecting changes in the observed modal frequencies. Further, the method is robust when applied to real buildings and large amplitude earthquake response, as demonstrated in previous work. The new fitting algorithms introduced are the nonlinear least squares (LSQ) fit and the time shift matching (TSM) algorithms. The former involves waveform inversion of the impulse responses, and the latter - iterative matching of the pulse time shifts, both markedly reducing the identification error as compared to the previously used direct ray algorithm, especially for more detailed models, i.e., with fewer floors per layer. Results are presented of identification of the NS, EW and torsional responses of the densely instrumented Millikan Library (9-story reinforced concrete building in Pasadena, California) during a small earthquake.     

Modeling of environmental influence in structural health assessment for reinforced concrete buildings

One branch of structural health monitoring (SHM) utilizes dynamic response measurements to assess the structural integrity of civil infrastructures. In particular,modal frequency is a widely adopted indicator for structural damage since its square is proportional to structural stiffness. However,it has been demonstrated in various SHM projects that this indicator is substantially affected by fluctuating environmental conditions. In order to provide reliable and consistent information on the health status of the monitored structures,it is necessary to develop a method to filter this interference. This study attempts to model and quantify the environmental influence on the modal frequencies of reinforced concrete buildings. Daily structural response measurements of a twenty-two story reinforced concrete building were collected and analyzed over a one-year period. The Bayesian spectral density approach was utilized to identify the modal frequencies of this building and it was clearly seen that the temperature and humidity fluctuation induced notable variations. A mathematical model was developed to quantify the environmental effects and model complexity was taken into consideration. Based on a Timoshenko beam model,the full model class was constructed and other reduced-order model class candidates were obtained. Then,the Bayesian modal class selection approach was employed to select the one with the most suitable complexity. The proposed model successfully characterizes the environmental influence on the modal frequencies. Furthermore,the estimated uncertainty of the model parameters allows for assessment of the reliability of the prediction. This study not only improves the understanding about the monitored structure,but also establishes a systematic approach for reliable health assessment of reinforced concrete buildings.     

Disbond detection with piezoelectric wafer active sensors in RC structures strengthened with FRP composite overlays

The capability of embedded piezoelectric wafer active sensors (PWAS) to perform in-situ nondestructive evaluation (NDE) for structural health monitoring (SHM) of reinforced concrete (RC) structures strengthened with fiber reinforced polymer (FRP) composite overlays is explored. First, the disbond detection method were developed on coupon specimens consisting of concrete blocks covered with an FRP composite layer. It was found that the prescnce of a disbond crack drastically changes the electromecbanical (E/M) impedance spectrum measured at the PWAS terminals. The spectral changes depend on the distance between the PWAS and the crack tip. Second, large scale experiments were conducted on a RC beam strengthened with carbon fiber reinforced polymer (CFRP) composite overlay. The beam was subject to an acccleratcd fatigue load regime in a three-point bending configuration up to a total of807,415 cycles. During these fatigue tests, the CFRP overlay experienced disbonding beginning at about 500,000 cycles. The PWAS were able to detect the disbonding before it could be reliably seen by visual inspection. Good correlation between the PWAS readings and the position and extent of disbond damage was observed. These preliminary results demonstrate the potential of PWAS technology for SHM of RC structures strengthened with FRP composite ovcrlays.     

Application of wavelet transform in structural health monitoring

Earthquake Engineering and Engineering Vibration - Structural health monitoring (SHM) is a process of implementing a damage detection strategy in existing structures to evaluate their condition to...