Dynamic behavior of bridge-erecting machine subjected to moving mass suspended by wire ropes

The dynamic behavior of a bridge-erecting machine, carrying a moving mass suspended by a wire rope, is investigated. The bridge-erecting machine is modelled by a simply supported uniform beam, and a massless equivalent ＂spring-damper＂ system with an effective spring constant and an effective damping coefficient is used to model the moving mass suspended by the wire rope. The suddenly applied load is represented by a unitary Dirac Delta function. With the expansion method, a simple closed-form solution for the equation of motion with the replaced spring-damper-mass system is formulated. The characters of the rope are included in the derivation of the differential equation of motion for the system. The numerical examples show that the effects of the damping coefficient and the spring constant of the rope on the deflection have significant variations with the loading frequency. The effects of the damping coefficient and the spring constant under different beam lengths are also examined. The obtained results validate the presented approach, and provide significant references in the design process of bridgeerecting machines.

Seismic fragility analysis of bridges by relevance vector machine based demand prediction model

A relevance vector machine(RVM)based demand prediction model is explored for efficient seismic fragility analysis(SFA)of a bridge structure.The proposed RVM model integrates both record-to-record variations of ground motions and uncertainties of parameters characterizing the bridge model.For efficient fragility computation,ground motion intensity is included as an added dimension to the demand prediction model.To incorporate different sources of uncertainty,random realizations of different structural parameters are generated using Latin hypercube sampling technique.Mean fragility,along with its dispersions,is estimated based on the log-normal fragility model for different critical components of a bridge.The effectiveness of the proposed RVM model-based SFA of a bridge structure is elucidated numerically by comparing it with fragility results obtained by the commonly used SFA approaches,while considering the most accurate direct Monte Carlo simulation-based fragility estimates as the benchmark.The proposed RVM model provides a more accurate estimate of fragility than conventional approaches,with significantly less computational effort.In addition,the proposed model provides a measure of uncertainty in fragility estimates by constructing confidence intervals for the fragility curves.

Design and Research of Class 900 t Railway Box-girder Bridge Erecting Machine

In this article, the current railway box girder bridge erecting machines at home and abroad are briefly introduced and analyzed, the research & design situation of class 900t railway box girder bridge erecting machines is described, and also the principle for determining the overall plan and a series of issues much concerning the design of key components of class 900t railway box girder bridge erecting machines are described.

Structural Damage Identification System Suitable for Old Arch Bridge in Rural Regions: Random Forest Approach

A huge number of old arch bridges located in rural regions are at the peak of maintenance.The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge,owing to the absence of technical resources and sufficient funds in rural regions.There is an urgent need for an economical,fast,and accurate damage identification solution.The authors proposed a damage identification system of an old arch bridge implemented with amachine learning algorithm,which took the vehicle-induced response as the excitation.A damage index was defined based on wavelet packet theory,and a machine learning sample database collecting the denoised response was constructed.Through comparing three machine learning algorithms:Back-Propagation Neural Network(BPNN),Support Vector Machine(SVM),and Random Forest(R.F.),the R.F.damage identification model were found to have a better recognition ability.Finally,the Particle Swarm Optimization(PSO)algorithm was used to optimize the number of subtrees and split features of the R.F.model.The PSO optimized R.F.model was capable of the identification of different damage levels of old arch bridges with sensitive damage index.The proposed framework is practical and promising for the old bridge’s structural damage identification in rural regions.

ML and CFD Simulation of Flow Structure around Tandem Bridge Piers in Pressurized Flow

Various regions are becoming increasingly vulnerable to the increased frequency of floods due to the recent changes in climate and precipitation patterns throughout the world.As a result,specific infrastructures,notably bridges,would experience significant flooding for which they were not intended and would be submerged.The flow field and shear stress distribution around tandem bridge piers under pressurized flow conditions for various bridge deck widths are examined using a series of three-dimensional(3D)simulations.It is indicated that scenarios with a deck width to pier diameter(Ld/p)ratio of 3 experience the highest levels of turbulent disturbance.In addition,maximum velocity and shear stresses occur in cases with Ld/p equal to 6.Results indicate that increasing the number of piers from 1 to 2 and 3 results in the increase of bed shear stress by 24%and 20%respectively.Finally,five machine learning algorithms,including Decision Trees(DT),Feed Forward Neural Networks(FFNN),and three Ensemble models,are implemented to estimate the flow field and the turbulent structure.Results indicated that the highest accuracy for estimation of U,and W,were obtained using AdaBoost ensemble with R2=0.946 and 0.951,respectively.Besides,the Random Forest algorithm outperformed AdaBoost slightly in the estimation of V and turbulent kinetic energy(TKE)with R2=0.894 and 0.951,respectively.

A Novel Half-Bridge Power Supply for High Speed Drilling Electrical Discharge Machining

High Speed Drilling Electrical Discharge Machining (HSDEDM) uses controlled electric sparks to erode the metal in a work-piece. Through the years, HSDEDM process has widely been used in high speed drilling and in manufacturing large aspect ratio holes for hard-to-machine material. The power supplies of HSDEDM providing high power applica-tions can have different topologies. In this paper, a novel Pulsed-Width-Modulated (PWM) half-bridge HSDEDM power supply that achieves Zero-Voltage-Switching (ZVS) for switches and Zero-Current-Switching (ZCS) for the dis-charge gap has been developed. This power supply has excellent features that include minimal component count and inherent protection under short circuit conditions. This topology has an energy conservation feature and removes the need for output bulk capacitors and resistances. Energy used in the erosion process will be controlled by the switched IGBTs in the half-bridge network and be transferred to the gap between the tool and work-piece. The relative tool wear and machining speed of our proposed topology have been compared with that of a normal power supply with current limiting resistances.

Experimental investigation of damage identification for continuous railway bridges

Considering the issue of misjudgment in railway bridge damage identification, a method combining the step- by-step damage detection method with the statistical pattern recognition is proposed to detect the structural damage of a railway continuous girder bridge. The whole process of damage identification is divided into three identification sub- steps, namely, damage early warning, damage location, and damage extent identification. The multi-class pattern clas- sification algorithm of C-support vector machine and the regression algorithm of c-support vector machine are engagedto identify the damage location and damage extent, respectively. For verifying the proposed method, both of the pro- posed method and the optimization method are used to deal with the measured data obtained from a specific railway continuous girder model bridge. The results show that the proposed method can not only identify the damage location correctly, but also obtain the damage extent which is consistent with the experimental results accurately. By uncou- pling finite element analysis and damage identification, normalizing the index, and seeking the separation hyper plane with maximum margin, the proposed method has more favorable advantages in generalization and anti-noise. As a re- sult, it has the ability to identify the damage location and extent, and can be applied to the damage identification in real bridge structures.

跨线转体桥施工抗倾覆技术研究现状及展望

在我国交通强国战略背景下,伴随公共交通建设力度的进一步提升,交叉线路变得越来越频繁。在跨越既有铁路开展桥梁工程建设时,为不影响铁路线路的正常运营,大多选用桥梁转体施工方案。为保障转体桥梁施工的安全,亟需系统梳理和总结桥梁转体施工抗倾覆难点及现有抗倾覆关键技术。通过调研国内外平转型转体桥工程实例及对相关文献进行分析与研究,分别从桥梁结构不平衡因素、转体结构所受外荷载影响及转体桥梁的施工工艺三方面进行研究,分析现有跨线转体桥梁施工技术抗倾覆难点,结合当前最新研究成果及较为先进的施工工法,总结专家学者提出的桥梁转体施工抗倾覆关键技术。最后对桥梁转体施工抗倾覆新技术进行展望,提出基于北斗技术下桥梁转体姿态实时动态监测技术与基于机器学习算法下,对转体桥梁的动态位移及结构损伤快速且精确识别的构思,为平转型桥梁转体施工抗倾覆研究的进一步发展提供了一定的研究思路,对平转型桥梁转体工程建设抗倾覆具有一定参考与借鉴意义。

基于声发射的钢桥面板焊接气孔缺陷在线识别

为实现正交异性钢桥面板机器人智能化焊接过程中缺陷的在线监测,提出了一种基于快速傅里叶变换和支持向量机的气孔缺陷声发射识别方法.通过开展机器人焊接实验,揭示了钢桥面板焊接及缺陷产生过程的声发射特征.无损伤与气孔缺陷2种工况信号的幅值、振铃计数、峰值频率和中心频率等参数重叠交叉严重、相关性不显著,而气孔缺陷信号的傅里叶频谱存在更多高频能量分布,因此以频谱为输入建立2种工况的径向基核支持向量机模型.实验结果表明,与朴素贝叶斯、随机森林和线性核支持向量机模型相比,径向基核支持向量机模型拥有更高的正确率(95.4%)和召回率(94.3%),能够用于焊接过程气孔缺陷的在线识别,具有较强的鲁棒性和实用性.

超宽公路架桥机优化设计与应用:以贵州省新平河特大桥为例

针对在超宽梁架设过程中,由于桥墩的墩顶直径较小,使得前支腿间距过窄,横梁会与架桥机前支腿产生干涉,并且现有架桥机无法满足喂梁和架设要求这一问题,提出了超宽公路架桥机前支腿内收开合的设计方案。通过理论分析,三维建模以及有限元分析的方法,提出了架桥机双前支腿独立运动方案,将架桥机前支腿由传统的纯箱式结构改造为具有主支腿,液压升降支腿,副支腿的新型前支腿结构,通过前支腿的内收可以使架桥机前支腿架设在普通直径的桥墩上;通过前支腿开合结构设计,可以使超宽梁通过前支腿,不造成干涉。成功解决贵州省钢-混桥梁实际施工建设中的技术难点,实现了超宽连续超宽钢主梁的整孔高效架设,并以贵州省都匀—安顺高速公路新平河特大桥铺设为例,进行了有限元分析与现场应力、挠度监测,验证了所提出架桥机的结构安全性能,为超宽公路架桥的应用提供参考。

基于域矩阵因子分解机的点击通过率预估增强网络

有效的特征交互,对于工业推荐系统中点击通过率(click-through-rate,CTR)预估的准确性起着至关重要的作用。以往并行结构的CTR预估模型通过将独立的浅层模型和深层模型并行连接,以此来学习特征的低阶交互和高阶交互。但是,这些模型存在浅层模型准确性低、未考虑特征交互时的多语义问题、参数过多、深层模型过度泛化等问题。基于上述问题,提出了一种基于域矩阵因子分解机的点击通过率预估增强网络,通过引入域矩阵优化浅层模型中的交互,提高运算效率,并在深层模型的DNN层与层之间增加了桥接模块,在每层高阶交互后增强对原始特征的记忆能力,将浅层模型和深层模型的结果相加并归一化得到预测值。该模型在Criteo、KKBox、Frappe和MovieLens数据集上进行了大量实验,展现了优秀的预测能力。

基于高光谱成像的桥梁混凝土表面露筋病害识别

桥梁作为交通关键节点,承担与日俱增的交通流量压力,相当一部分桥梁尚未达到设计使用年限就出现较多的病害,技术状况不容乐观。高光谱成像运用光电技术检测物体对光谱波段信号的辐射和吸收情况,将该信号转换成图像和图形,可基于吸收峰的位置和强度分析被测物体的物理性质和物质组成,因此本文提出基于高光谱成像的桥梁混凝土表面露筋病害识别方法。利用线阵高光谱相机集成匀速步进滑轨装置,形成高光谱成像测试系统,采集桥梁混凝土表面露筋病害图像;基于桥梁露筋病害高光谱图像谱线与空间特征,结合预处理——平滑滤波-多元散射校准(Savizky-Golay-Multivariate scattering calibration,SG-MSC)、特征空间变换——光谱导数法(First derivative,FD)、特征变量选择算法——竞争自适应重加权抽样(Competitiveadapativereweighted sampling,CARS),将原始光谱曲线数据经特征空间转换提取相应特征值并显示波段;以光谱曲线特征向量构建数据集,基于支持向量机形成露筋病害识别预测模型。以某跨江大桥为例,以高光谱成像测试系统对实际桥梁混凝土露筋病害进行识别,将原始光谱数据经平滑特征空间变换与特征提取后放大差异,将254个波段数据维度降低到23个波段数据,模型预测精度达到94.6%,对比可见光成像高光谱成像具有更高维度信息可有效表征物质属性,表明高光谱成像对复杂表面环境下的桥梁病害识别具有可行性和广泛应用前景。

桥梁面相学及其研究进展

为了探索更加实效、经济、便捷、可信的桥梁安全状态检(监)测新方法,受中医望、闻、问、切诊断人体健康状态理念启迪,提出了依据桥梁外观形态变化来获知结构近期安全状态的桥梁面相学;总结了10多年来基于桥梁面相学的桥梁安全状态检(监)研究进展;介绍了基于定点相机平转+竖转拍摄的桥梁动静影像全息性态监测系统、基于激光雷达+全景数码相机拍摄的WWWQ-G桥梁安全巡检车、基于普通摄像头拍摄的常规跨径桥梁安全监测系统和基于定点旋转测量装置的拉索性态远距全域视频检测系统的构成理论,以及各系统应用于桥梁构件损伤检测的试验研究案例和实际工程应用案例;展望了融合“测点传感器+机器视觉”实现桥梁结构状态的“精+密”监测方法及其应用前景。

基于机器视觉的大跨长联桥上无缝线路小阻力扣件纵向服役状态监测研究

以福厦高铁渔溪特大桥为例,提出一种基于机器视觉的小阻力扣件纵向服役状态监测方案,以获取大跨长联桥上无缝线路钢轨纵向变形与复合垫板窜出的时变特征;同时,结合梁轨温度与梁端位移测试结果,分析梁体温度、钢轨温度、梁端累积位移、梁轨相对位移与垫板窜出量之间的相关性。研究结果表明:根据图像识别结果,钢轨在监测阶段将随温度变化产生不同方向的伸缩,且钢轨位移略大于垫板窜出量。钢轨昼夜温差要显著大于桥面气温以及连续梁梁内气温、顶板温度、腹板温度,且梁体温度变化幅度显著比钢轨的小,其原因在于钢轨的比热容较小,在同等热量输入输出时产生的温度变化幅度较大。梁端纵向位移随温度变化幅度较小,最大日位移为0.15 mm;在监测周期内,梁端累积位移呈波动减小趋势,即梁体发生了缓慢收缩,其原因在于夏季到秋季时气温逐渐降低,且最大平均位移变化速率为0.09 mm/d。梁体温度、钢轨温度、梁端累积位移、梁轨累积相对位移和垫板窜出量之间的相关系数均大于0.8,说明其相关性较大,且均呈较好的正相关关系。通过基于机器视觉的小阻力扣件状态监测方法,可见小阻力扣件在福厦高铁渔溪特大桥区段具有较好的纵向服役状态,且监测周期内线路状态均正常,验证了此类方案在小阻力扣件现场监测中的适用性。

基于金属磁记忆检测的正交异性钢桥面板疲劳应力检测

钢箱梁作为被广泛应用的桥梁建设结构,正交异性钢桥面板的连接焊缝多,受到车轮载荷的影响,容易产生疲劳应力和疲劳裂纹,进而可能造成严重安全事故,针对此类涉及正交异性钢桥面板疲劳应力检测的问题,提出了一种基于金属磁记忆检测的正交异性钢桥面板疲劳应力检测方法。首先,通过建立一个金属磁记忆检测系统,实现正交异性钢桥面板的金属磁记忆信号的时域、频域和时频域特征的提取;然后,建立各个信号特征与材料疲劳应力的极限学习机模型;最后,通过极限学习机模型对材料的疲劳应力进行相关估算。结果表明:该系统和极限学习机模型对正交异性钢桥面板的疲劳应力检测是有效的,且疲劳应力估算精度较高。研究结果可作为正交异性钢桥面板应力检测的一种重要技术手段。

基于机器学习的堵漏颗粒粒径推荐方法

井漏是油气勘探领域的重大技术难题。桥接堵漏是最常用的堵漏技术手段,其中架桥颗粒粒径是关键参数,直接影响堵漏成败,目前架桥颗粒粒径的选择主要依赖经验,缺乏科学有效的方法。研究了一种基于机器学习算法的堵漏颗粒粒径推荐方法。该方法基础数据为塔里木盆地库车山前区域126口完钻井的测井、录井及防漏堵漏施工数据,其输入层为基于皮尔森算法筛选出的23项主要参数,输出层为0~750μm、750~1 500μm、1 500~4 000μm、4 000μm以上等4个架桥颗粒粒径区间。训练测试了10种常用的机器学习算法在测井数据、录井数据及测井+录井数据等三类数据集上的准确率,测井+录井数据集上各算法得分普遍高于测井和录井数据集。在测井+录井数据集上,支持向量机和极限随机树算法的F1得分最高,达到0.9以上。基于支持向量机和极限随机树算法的架桥颗粒粒径推荐模型在库车山前一口井上验证2井次,两种算法模型的架桥颗粒粒径预测结果与现场实际堵漏效果一致,在桥堵粒径级配科学优选上具有良好的应用前景。

桥式转载机的密封式中间架结构设计与研究

由于煤矿掘进巷道高度低、空间狭小,巷道内需要安放掘进机、桥式转载机、通风管道等大型设备,存在安装困难、设备互相干扰等问题。将传统桥式转载机的刚性架设计成了一种矩形密封式刚性中间架结构。该密封式中间架可以作为通风管道使用,对该结构进行有限元分析,结果表明矩形密封式中间架受力弯曲变形较小,结构设计具有合理性和可靠性。

闸站枢纽泵站前池流态及其改善数值模拟研究

分析了沙集闸站前池泥沙淤积成因,并试图改造在下游新建清污机桥,应用桥墩改善前池流态、减少泥沙淤积,采用三维建模软件UG NX建立河道流场三维模型,基于ICEM CFD进行计算域网格划分,并使用ANSYS CFX进行数值计算。计算结果表明:现状抽水工况下,导流墙内侧存在大范围低速区,因而产生大范围泥沙淤积。将泵站下游两侧导流墙延长至60 m,在导流墙头部新建清污机桥,应用桥墩导流,导流墙内侧低速淤积区范围大大减小,泵站进水流态大为改善。

JQJ180型架桥机架设210 m小半径曲线桥25 m预制T梁施工技术

结合某高速公路增设北互通工程210 m小半径曲线桥25 m长预制T梁架设实践,对双导梁在小半径桥梁中采用拨轨道、搭设临时支2种方法完成前移转向的比较,分析双导梁架桥机在大跨径小半径曲线桥架设的可行性。重点介绍架桥机拼装、架桥机前移、喂梁、T梁安装和架桥机过孔转向等施工工艺。

基于角点校准的暗光下桥梁位移监测研究

基于机器视觉的数字图像方法监测结构物变形具有非接触性等优点,但受到暗光环境及人工标志物变形等因素的影响导致其应用受限.在现有模板匹配测量基础上,提出了暗光环境下基于Harris角点检测校准和Retinex暗光增强网络的桥梁位移监测方法和系统,以提高桥梁结构在复杂环境下的位移监测精度.进一步通过试验验证,结果显示10 m距离的暗光环境下桥梁位移监测最大绝对误差小于0.3 mm,在靶标偏转角度在0.6°至1.2°情况下,基于角点校准后的平均精度相比未校准提高了44%,说明该系统具备在暗光环境下进行工程结构位移监测的实用性.