基于不完备损伤指标和遗传算法的特大桥损伤识别和传感器布点优化

特大桥健康监测系统不可能在所有自由度安放传感器,该文讨论了用由不完备振型建立的损伤指标的损伤识别和传感器布点优化方法。与过去用遗传算法优化传感器布点的适应度函数不同,该文用损伤指标最灵敏来建立适应度函数。对桥梁的单个损伤,该文用不完备模态柔度矩阵差和截断模态应变能变化率两个不完备损伤指标作为适应度函数来优化传感器布点,并与传统的COMAC指标对比,还改进了多种群遗传算法,以提高收敛速度和全局寻优能力。并以西堠门悬索桥有限元模型为例,识别不同部位的损伤。算例表明:该方法在损伤识别和传感器布点优化方面不仅可行而且有效。     

基于遗传算法的斜拉桥传感器优化布置研究

分析了传感器的类型、数量和位置在桥梁结构健康监测和诊断中的重要性,对桥梁结构传感器优化布点作了详细的分类及论述.分析了遗传算法的特点优点,并与传统优化算法作了比较.最后利用遗传算法搜索一座独塔不对称的协作梁大跨度斜拉桥结构的健康监测系统中传感器的最优布点.结果表明,用遗传算法进行传感器最优布点具有结果稳定可靠,收敛迅速的特点,能够满足系统的要求.     

大跨空间钢结构模态参数测试传感器优化布置

为了有效选择监控模态振型阶数,并使振型向量间夹角和测点振动能量同时尽可能大,提出了基于模态能量和白适应遗传算法的多目标传感器优化布置方法.首先,根据结构模态应变能的大小挑选出环境激励下结构的主要贡献模态,即优化时所取的监控模态.然后,根据单位刚度的模态运动能以及模态置信度矩阵构造新的适应度函数,利用自适应遗传算法对布点...     

斜拉桥传感器优化布点的研究

在振动模态试验中,传感器位置和数目的选择对试验结果的质量有很大的影响。首先回顾了近年来关于传感器最优布点方法的研究。然后以一座三跨预应力混凝土斜拉桥为研究对象,采用有效独立法和基于模态保证标准的算法这两种最优布点算法,对斜拉桥主梁上加速度传感器的最优布点进行了初步的探讨。结果表明:有限元模型和所监控模态振形的阶数对最优传感器布点的选取有较大的影响;用有效独立法对类似的斜拉桥进行优化布点计算时,能得到较为理想的布点方案。     

基于多目标遗传算法的传感器优化布点研究

针对目前桥梁模态试验中传感器布点优化都是基于单一准则下的研究的局限性,提出采用双准则或多准则下的传感器优化布点研究,该方法改进了以往布点优化中单一目标最优的限制,转而寻求多准则下的优化布点的满意解,而非真正严格数学意义上的最优解。采用Pareto遗传算法,设计了相应的遗传算子和编码方案,成功求解了双准则下传感器最优布点问题,优化结束时,成功给出了一组pareto最优解的前沿面,进而证明了提出的方法是可行的。     

润扬大桥悬索桥在线模态分析系统的设计与实现研究

介绍了润扬大桥悬索桥在线模态分析系统的设计思路.主要包括:设计策略、测点布置以及模态识别方法.对系统的设计与实现的关键技术问题进行了研究.在模态识别方法上将传统的基于环境激励的模态试验方法引入到在线模态分析中,并对传统频域峰值法做了改进,实现了模态分析的实时性和振型的完整性.对比系统识别结果和现场测试结果表明:系统运行稳定、识别结果可靠.系统的建立为该桥动力特性研究、预警以及评估提供了大量重要参数.     

基于模型试验的悬索桥结构损伤识别研究

通过整桥模型试验, 探讨了悬索桥结构损伤识别方法. 首先面向损伤识别研究设计制作了长10m的悬索桥试验模型, 并通过模型误差分析建立了相应的高精度有限元模型. 基于悬索桥结构健康监测和试验检测的主要常用参数以及这些参数对结构损伤的灵敏性和相关性研究, 确定损伤识别策略. 采用有限元模型模拟可能的损伤工况, 从而生成BP网络的训练样本数据. 再将试验模型作为“实际结构”通过损伤模拟试验生成网络测试数据. 就试验模拟的损伤情况而言, 对损伤位置的识别准确率达到了86%, 相应的损伤程度识别精度也达到可接受程度. 显示了该方法较好的应用前景, 对基于监测系统的悬索桥健康状态识别与评价具有参考意义.     

基于数据融合的传感器优化布置方法

传感器优化布置是结构健康监测研究的重要内容,传感器数量和位置的选择直接关系到模态参数识别的效果及模型修正的结果等。为了达到布置在结构上的有限传感器能够测量并得到用于模态参数识别的最佳信息的目标,提出了基于数据融合的传感器优化布置方法。该方法以距离测度作为数据融合的融合度,首先通过对距离测度矩阵、支持度矩阵的计算,得到待选测点的综合支持度;其次,根据待选测点的综合支持度大小来确定传感器优化布置的位置;最后,以网架结构的传感器优化布置为例,运用峰值法进行自振频率识别,通过已选测点与未选测点识别效果的对比,验证了该方法的有效性。     

随机子空间识别在悬索桥实验模态分析中的应用

为了从大型悬索桥的脉动实验结果得出精确的结构动力特性,以便进行结构的抗风、抗震研究和实时监测,本文利用随机子空间系统识别方法对虎门悬索桥进行了模态分析。这种时域识别方法基于状态空间模型,仅利用结构输出反应,避免了传统的人工识别和迭代过程,但必须利用稳定图形确定模型阶数。同有限元数值计算结果作比较后可看出,该法能识别出10个频率在0.5Hz以下的自振频率,并且可得到较好的结构阻尼,说明随机子空间系统识别方法是分析大型桥梁脉动实验特征参数的有力工具。     

基于改进遗传算法的桥梁结构传感器优化布置

为了解决桥梁结构健康监测中的传感器优化布置问题,提出一种基于二重结构编码遗传算法的传感器优化布置方法.首先改进了编码方法,采用二重结构编码进行种群的初始化、交叉和变异,然后选择时采用最优保存策略,交叉时采用自适应部分匹配交叉,变异时采用自适应逆位变异.该法克服了传统遗传算法应用于大型结构时收敛速度慢且易陷入局部最优的缺陷,大大加快了收敛速度,并确保能够搜索到最优解.最后通过一个桥梁工程的实例分析,证明了该法在搜索能力、计算效率和可靠性方面明显优于序列法,可广泛地应用于桥梁结构的健康监测.     

基于健康监测系统的大跨多荷载桥梁的 疲劳可靠度评估

考虑到火车、汽车与风荷载的长期作用以及多荷载的随机性,评估大跨多荷载桥梁的疲劳可靠度是一项富有挑战的任务。该研究基于健康监测系统提出了大跨多荷载悬索桥的疲劳可靠度分析框架,并应用到香港青马大桥。首先,定义了疲劳可靠度的极限状态函数,基于监测数据建立火车、汽车与风荷载的概率模型。基于概率模型和蒙特卡洛模拟方法,利用疲劳关键位置上多荷载的每日随机应力响应,估计每日应力幅m次方之和的概率分布。假设交通保持不变,可确定在给定时段内应力幅m次方之和的概率分布。最终得到桥梁不同疲劳关键位置不同时间点的疲劳失效概率。结果表明,在目前的交通状态下,青马大桥的疲劳健康状况可保持良好。     

Buffeting-induced fatigue damage assessment of a long suspension bridge

As modern suspension bridges become longer and longer, buffeting-induced fatigue damage problem for the bridges located in strong wind regions may have to be taken into consideration. Furthermore, there is a trend to install wind and structural health monitoring systems (WASHMS) to long suspension bridges for performance assessment. A systematic framework for assessing long-term buffeting-induced fatigue damage to a long suspension bridge is thus presented in this paper by integrating a few important wind/structural components with continuum damage mechanics (CDM)-based fatigue damage assessment method. By taking the Tsing Ma Bridge in Hong Kong as an example, a joint probability density function of wind speed and direction is first established based on wind data recorded by the WASHMS installed in the bridge. A structural health monitoring-oriented finite element model of the bridge and a numerical procedure for buffeting-induced stress analysis of the bridge are then used to identify stress characteristics at hot spots of critical steel members under different wind speeds and directions. The accumulative fatigue damage to the critical steel members at hot spots during the bridge design life is finally evaluated using a CDM-based fatigue damage evolution model. The proposed framework is found to be feasible and practical.     

基于结构多尺度模拟和分析的大跨斜拉桥应变监测传感器优化布置研究

该文以润扬大桥斜拉桥钢箱梁结构为研究对象,针对结构安全评估为目标的大跨桥梁结构健康监测系统中应变传感器的优化布置问题,提出了一个基于桥梁结构多尺度模拟和结构响应分析结果进行应变传感器优化布置的方法。通过斜拉桥脊骨梁模型来研究确定钢箱梁的关键截面,通过子模型方法实现钢箱梁结构的多尺度模拟和从结构整体到主要局部构件中的应力状态分析,据此进一步分析和确定斜拉桥健康监测系统中钢箱梁结构应变传感器的安装位置,并用在润扬斜拉桥上进行的静动载试验的测试结果验证了结构整体与局部响应分析结果,从而间接验证了应变传感器优化布置结果的正确性。     

Optimal sensor placement for enhancing sensitivity to change in stiffness for structural health monitoring

This paper focuses on optimal sensor placement for structural health monitoring (SHM), in which the goal is to find an optimal configuration of sensors that will best predict structural damage. The problem is formulated as a bound constrained mixed variable programming (MVP) problem, in which the discrete variables are categorical; i.e., they may only take on values from a pre-defined list. The problem is particularly challenging because the objective function is computationally expensive to evaluate and first-order derivatives may not be available. The problem is solved numerically using the generalized mixed variable pattern search (MVPS) algorithm. Some new theoretical convergence results are proved, and numerical results are presented, which show the potential of our approach.     

基于自适应引力算法的桥梁监测传感器优化布置

针对桥梁健康监测中传感器布置优化问题,提出了一种基于自适应引力算法的传感器优化布置方法。以模态置信准则为基础,构造满足传感器优化布置的适应度函数;针对引力搜索算法开发能力不足,对衰减因子α进行了自适应改进。搜索初期α较小,粒子以较大步长进行全局搜索,增强了算法的搜索效率;搜索后期α较大,粒子以较小的步长进行局部搜索,提高了算法的搜索能力,避免落入局部极值点。改进后的自适应引力算法通过双重编码的方式,使算法可以解决离散型的传感器布置问题;以马水河大桥为例,验证算法的可行性。结果表明,改进后的算法有很好的寻优能力,能够准确高效的确定传感器优化位置。     

Development of life extension strategies for Australian military aircraft, using structural health monitoring of composite repairs and joints

The DSTO Centre of Expertise for Structural Mechanics (COE-SM) has recently developed methodologies for simulating structural health monitoring (SHM) systems for adhesively bonded composite repairs to Australian military aircraft. System design, interrogation strategy, and sensor placement are discussed, with particular emphasis on the development of techniques for embedding optical fibre sensors for optimal SHM system response.     

Evaluation of fiber optic sensors for remote health monitoring of bridge structures

Health monitoring of civil infrastructure systems has recently emerged as a powerful tool for condition assessment of structural performance. With the widespread use of modern telecommunication technologies, structures could be monitored periodically from a central station located several miles away from the field. Sensors are placed at several critical locations along the structure, and send structural information to the central station. This remote capability allows immediate damage detection, so that necessary actions that ensure public safety are taken. The goal of this research work is to evaluate the use of Fiber Optic sensing technology as a tool for structural health monitoring. To perform this task, a case study involving installation of Fiber Optic Sensors on a selected bridge structure during its construction phase was conducted. The bridge is located in the state of Florida, USA and is considered the first smart structure in this state. Static and Dynamic testing of the bridge were performed using loaded SU4 trucks. A 3-dimensional analytical finite element model of the bridge was developed and its results were compared to the test data. The study confirmed the accuracy of the sensors in estimating the bridge behavior under heavy truck loads. In addition, the sensors were connected to a data acquisition system permanently installed on-site. The acquisition system could be accessed through remote communication, which permits the evaluation of the bridge behavior under live traffic loads. Currently, live structural data under traffic loading is being transmitted continuously to the central maintenance office. The study revealed that the proposed health monitoring technology will enable practical, cost-effective, and reliable maintenance of bridge structures.     

Probability of Detection and Optimal Sensor Placement for Threshold Based Detection Systems

This paper provides a probabilistic analysis of simple detection systems which are based on thresholding feature values extracted from a sensor signal. For such systems, this paper explains how to calculate the probability of detection as a function of range from the sensor to the object of interest. This function is important in that it enables optimal positioning of a group of sensors, either maximizing detection rates for a given number of sensors or informing the minimum number of sensors necessary to achieve a desired probability of detection throughout an area. An example case study is presented, based on a novel approach to passive acoustic diver detection in noisy environments.