桥梁结构的荷载与损伤识别研究进展

世界范围内频频发生的桥梁工程事故引起了人们对于桥梁结构＂健康＂问题的重视,而桥梁的荷载识别与损伤识别则是诊断结构健康状况的重要手段和方法.文中分别就结构荷载识别与损伤识别问题的研究现状进行了总结,指出了当前结构荷载识别与损伤识别研究中亟待解决的问题,并对进一步研究桥梁荷载与损伤的问题进行了讨论.     

桥梁结构连续倒塌研究方法与现状

为了深入探究桥梁结构连续倒塌的分析方法、失效准则,得到有效的桥梁倒塌控制方法,本文结合国内外已有的研究成果,从数值模拟、理论研究两方面对桥梁倒塌进行了总结和评述,并介绍了各类桥梁结构倒塌控制方法和研究现状。     

桥梁支座常见病害与养护方法研究

桥梁支座可以将上部结构的荷载传递到下部结构,有效改善桥梁结构的受力情况。通过对桥梁支座病害成因进行分析,可以为养护维修提供参考依据。本文对桥梁支座常见病害的养护方法进行研究,并提出改进措施,以有效解决桥梁支座病害带来的质量问题。     

复杂桥梁结构分析与施工安全监控的发展现状

研究了复杂桥梁结构分析与施工安全监控的国内外发展现状与研究要点,阐述了进行复杂桥梁结构分析与施工安全监控的必要性,并针对存在的关键问题和主要研究领域,提出了可行的技术路线和研究方法,以期为复杂桥梁的结构分析理论发展与工程实践提供指导。     

国内V形支撑结构桥梁设计与研究综述

通过查询相关文献及部分设计图纸,总结了我国V形支撑结构桥梁的建设成就,研究了目前V形支撑结构桥梁的几种结构形式,分析了主梁和V形支撑的设计参数,对V形支撑结构桥梁的研究现状进行概括,主要有以下几个方面:V形支撑结构桥梁的受力特性研究现状、V形支撑结构桥梁的施工方法及施工控制、V形支撑的混凝土施工步骤、V形支撑结构的旧桥加固以及V形支撑结构桥梁的动力特性。通过总结分析和归纳概括,为今后该类桥型的设计提供参考,为该类桥型的深入研究指明方向。     

公路桥梁与城市桥梁技术状况评定方法的区别

针对公路桥梁依据的JTG/T H21—2011公路桥梁技术状况评定标准与城市桥梁主要依据的CJJ 99—2017城市桥梁养护技术标准两本规范中的桥梁评定方法进行研究和分析,探讨两种方法的主要区别。阐述了两种桥梁技术状况评定方法,分别从桥梁类型的划分、等级的划分、桥梁结构组成权重、构件的扣分方法及其他方面对两种方法进行对比和分析,并结合实例,对两种桥梁评定方法的评定结果进行分析。     

环境因素与疲劳荷载耦合作用下预应力混凝土结构性能研究现状与展望

预应力混凝土结构广泛地应用于桥梁工程中。随着车辆通行量的日益增加、环境的逐渐恶化,预应力混凝土桥梁服役性能日渐劣化。对环境因素与荷载(尤其疲劳荷载)作用下预应力混凝土桥梁结构服役性能的研究成为热点。从材料、结构构件、研究方法等方面介绍了环境与荷载共同作用下预应力混凝土桥梁结构服役性能以及研究方法、寿命预测方法的研究现状以及存在的问题。在此基础上,探讨了环境与荷载耦合作用下预应力混凝土桥梁结构服役性能研究的发展方向。     

基于动力特性试验桥梁结构技术状况评定研究

动载试验是研究桥梁结构动力特性的重要方法之一,结构动力特性是桥梁承载力评定和识别桥梁结构工作性能的重要参数。文章开展了桥梁结构动力特性参数(频率、振型和阻尼比)的研究,通过对结构动力特性的测试,分析结构动力反应,了解车辆荷载对桥梁的动力作用,进而对桥梁的状态进行较全面的评估,并为今后桥梁结构安全营运提供可靠的技术资料。     

桥梁抗震设计与分析

从影响桥梁抗震分析的地震作用与本构关系出发,结合现行相关抗震规范对桥梁进行抗震设计与分析首先,对非线性阶段的钢筋和混凝土材料的本构关系、钢筋混凝土结构的有限元模型,以及UCFyber软件的模拟方法进行了介绍;其次,对桥梁不同构件进行了抗震性能的验算分析。为类似桥梁的分析研究工作提供参考。     

桥梁技术状况退化模型研究现状与展望

桥梁结构在服役期间由于在使用荷载和自然环境长期作用下,会引发结构的老化、损伤等耐久性问题,进而影响桥梁结构的使用寿命。对桥梁的结构性能退化趋势进行预控,及时采取有效的养护措施对公路桥梁的安全运营意义重大。因此,首先分析了当前桥梁管理中所采用的退化预测方法,总结了基于统计数据的桥梁退化预测模型;然后讨论了桥梁技术状况退化模型的应用现状,指出了现阶段桥梁技术状况退化模型中存在的不足。分析认为,根据实际结构形式,需要采用不同的技术状况退化预测方法对退化预测模型进行优化,才能弥补单一预测方法和模型的局限性,使结果更加接近桥梁真实的退化状态,且随着智能技术的发展,传统的预测方法与智能模型的结合将会是桥梁技术状况退化预测模型新的发展方向。     

Performance of Vibration-Based Damage Detection Methods in Bridges

Abstract:   The important advances achieved in the modal identification, sensors, and structural monitoring of bridges have motivated the bridge engineering community to develop damage detection methods based on vibration monitoring. Some of these methods have already been demonstrated under certain conditions in bridges with deliberate damage. However, the performance of these methods for damage detection in bridges has not been fully proven so far and more research needs to be done in this direction. In this article, six damage detection methods based on vibration monitoring are evaluated with two case studies. First, the dynamic simulation and modal parameters of a cracked composite bridge are obtained. Here, the damage detection methods are evaluated under different crack depth, extension of the damage, and noise level. Second, damage is identified in a reinforced concrete bridge. This bridge was deliberately damaged in two phases. In this example, damage detection methods, which do not require comparison between different structural conditions, were applied. In the first case study, evaluated damage detection methods could detect damage for all the damage scenarios; however, their performance was notably affected when noise was introduced to the vibration parameters. In the second case study, the evaluated methods could successfully localize the damage induced to the bridge.     

基于神经网络的连续梁桥结构损伤识别

探讨了神经网络技术对连续桥梁的损伤位置和损伤程度识别的方法,用有限元软件ANSYS的模态分析技术对连续梁结构的损伤情况进行模拟,得到损伤标示量并将其作为神经网络训练样本,数值仿真结果表明,该方法对于实际工程结构的损伤识别具有一定的参考意义。     

Structural health monitoring of a cable-stayed bridge with Bayesian neural networks

In recent years, there has been an increasing interest in permanent observation of the dynamic behaviour of bridges for long-term monitoring purpose. This is due not only to the ageing of a lot of structures, but also for dealing with the increasing complexity of new bridges. The long-term monitoring of bridges produces a huge quantity of data that need to be effectively processed. For this purpose, there has been a growing interest on the application of soft computing methods. In particular, this work deals with the applicability of Bayesian neural networks for the identification of damage of a cable-stayed bridge. The selected structure is a real bridge proposed as benchmark problem by the Asian-Pacific Network of Centers for Research in Smart Structure Technology (ANCRiSST). They shared data coming from the long-term monitoring of the bridge with the structural health monitoring community in order to assess the current progress on damage detection and identification methods with a full-scale example. The data set includes vibration data before and after the bridge was damaged, so they are useful for testing new approaches for damage detection. In the first part of the paper, the Bayesian neural network model is discussed; then in the second part, a Bayesian neural network procedure for damage detection has been tested. The proposed method is able to detect anomalies on the behaviour of the structure, which can be related to the presence of damage. In order to obtain a confirmation of the obtained results, in the last part of the paper, they are compared with those obtained by using a traditional approach for vibration-based structural identification.     

现役公路桥梁结构损伤检测与评估

阐述了公路现役桥梁结构损伤检测及安全评估的重要性,介绍了目前国内外采用的桥梁检测、安全评估及剩余寿命预测的主要方法,特别是基于振动测试的结构损伤识别方法,指出桥梁损伤检测和安全评估对桥梁发展具有重要意义。     

基于神经网络的桥梁损伤识别研究综述

对人工神经网络的基本原理、特点以及与损伤识别的关系作了简要介绍,并重点介绍了损伤识别中常用的BP 神经网络的原理及其改进方法,以及国内外在基于神经网络的桥梁损伤识别应用方面的主要研究成果,最后对神经网络在桥梁损伤识别中的发展和应用作了展望。     

Multi-source information fusion applied to structural damage diagnosis

This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve its validity. Two structural damage identification methods based on MSIF are put forward, one of which is to fuse two or more structural damage detection methods by MSIF and another of which is the improved modal strain energy method by multi-mode information processing based on MSIF. Through a concrete plate experiment it is proved that, if two methods are integrated by character-level information fusion, structural initial damages can be more accurately identified than by a single method. In a simulation of a concrete box beam bridge, it is indicated that the improved modal strain energy method has a nice sensitivity to structural initial damages and a favorable robusticity to noise. These two structural damage diagnosis methods based on MSIF have good effects on structural damage identification and good practicability to actual structures.     

磁测法在桥梁隐蔽病害检测中的研究进展

桥梁隐蔽病害形式各异、成因复杂、不易察觉，且病害产生的结构破坏具有突发性，因此对隐蔽病害的准确检测以将其扼杀在萌芽阶段具有现实意义。系统梳理了磁测法用于钢筋锈蚀、拉吊索腐蚀断丝、钢筋应力、体内预应力、钢结构疲劳损伤等桥梁隐蔽病害检测的现状及瓶颈，分析了其有效性和适用范围，探讨了磁测法的发展趋势，可为桥梁隐蔽病害检测的精准化，实用化和装备化提供有益参考。     

Long-term bridge health monitoring and performance assessment based on a Bayesian approach

This study presents a damage detection approach for the long-term health monitoring of bridge structures. The Bayesian approach comprising both Bayesian regression and Bayesian hypothesis testing is proposed to detect the structural changes in an in-service seven-span steel plate girder bridge with Gerber system. Both temperature and vehicle weight effects are accounted in the analysis. The acceleration responses at four points of the bridge span are utilised in this investigation. The data covering three different time periods are used in the bridge health monitoring (BHM). Regression analyses showed that the autoregressive exogenous model considering both temperature and vehicle weight effects has the best performance. The Bayesian factor is found to be a sensitive damage indicator in the BHM. The Bayesian approach can provide updated information in the real-time monitoring of bridge structures. The information provided from the Bayesian approach is convenient and easy to handle compared to the traditional approaches. The applicability of this approach is also validated in a case study where artificially generated damage data is added to the observation data.     

土木工程结构损伤诊断研究现状与展望

阐述了结构损伤诊断技术在土木工程结构中的重要性，在综述结构损伤诊断研究现状的基础上，重点介绍了用于土木工程结构的各种损伤诊断方法，并对相关问题进行了讨论和评述，最后对土木工程结构损伤诊断的未来研究方向提出了建议与展望。     

基于动力特性桥梁损伤诊断方法研究

基于桥梁结构的动力特性,结合人工神经网络,探讨了分步进行探伤、定位和量估的桥梁损伤诊断方法,以襄荆高速公路某一简支梁桥为算例,采用ANSYS程序建立了三维有限元模型进行模拟损伤分析,验证了所述方法的可行性。