A methodology for scheduling overlapped design activities based on dependency information

The practice of overlapping activities is becoming a requirement for fast-tracking complex construction projects. The amount, timing, and nature of the information exchanged between pairs of activities determine the degree to which pairs of activities may be overlapped. This paper presents a four-step process for scheduling the design phase of fast-tracked construction projects while taking into consideration information exchange among project activities. The process starts with capturing and quantifying this exchange of dependency information. A contemporary scheduling tool, the dependency structure matrix (DSM), aids in generating the shortest (overlapped) schedule based on dependencies among the different design disciplines. An algorithm is designed to calculate the shortest possible schedule for the design phase of a construction project. The developed scheduling algorithm is unique as it includes information exchange alongside task durations. The algorithm is validated in the context of a real-world case study, a fast-tracked multi-billion dollar educational facility project in the Arabian Peninsula.     

基于计算机视觉的结构系统识别

结构系统识别是土木工程结构健康监测的重要组成部分,传统的结构系统识别通过有线或无线的测量系统进行数据采集,布置传感器以及数据采集设备的过程繁琐、费时。为了提高结构系统识别的效率,提出一种无需人工靶点、基于计算机视觉的非接触式测量方法,以消费级相机为采集设备,采用基于点匹配的特征光流技术实现目标的运动跟踪,获得目标的位移时程,进而实现结构系统识别。使用消费级摄像机对振动台试验中的结构模型进行测量,与传统拉线式位移传感器的测量结果进行对比。研究结果表明,采用基于计算机视觉的非接触式测量方法,在频域中具有较高的测量精度,并且能够准确识别出结构的自振频率、振型等动力特性,具有良好的应用前景。     

基于外部单目视觉的仿生扑翼飞行器室内定高控制

针对扑翼飞行器的定高飞行,设计了基于外部单目视觉的室内定高控制系统:通过外部单目相机获取扑翼飞行器的飞行图像,基于Qt编写的地面站软件接收图像并利用基于OpenCV的图像处理算法检测扑翼飞行器上的发光标识点,获得标识点在图像上的像素坐标;基于卡尔曼滤波器(KF)建立标识点像素坐标的运动状态估计器,降低环境噪声干扰并解决了标识点被短暂遮挡的问题;分别建立常规PID和单神经元PID控制系统,通过蓝牙控制扑翼飞行器的电机转速,实现了基于图像的扑翼飞行器室内定高飞行.对比实验结果表明,本文设计的定高飞行控制系统可以使扑翼飞行器标记点的图像坐标保持在外部单目相机图像的中心横线处.针对阶跃响应信号,单神经元PID控制系统的响应速度比常规PID控制系统响应速度稍慢一些,但是控制精度明显优于常规PID控制器,最大相对误差为3%.     

Integration of geographic information systems and computer vision systems for pavement distress classification

The main objective of this research work was to investigate the potential of integration of geographic information system (GIS), global positioning system (GPS) and computer vision system (CVS) for the purpose of flexible pavement distresses classifications and maintenance priorities. The classification process included distress type, distress severity level and options for repair. A system scheme that integrated the above-mentioned systems was developed. The system utilized the data collected by GPS and a PC-based vision system in a GIS environment. GIS Arcview software was used for the purpose of data display, query, manipulation and analysis.The developed system provided a safer pavement condition data collection technique, flexible data storage, archiving, updating and maintenance priorities updating. Maintenance priorities were assigned based on priority indices values computed by priority index (PI) or available budget criterion. This technique was cost-effective and offered wise-based decision making for different maintenance activities and programs.Using average daily traffic (ADT), distance from maintenance unit (R), pavement section area and pavement age, statistical models were developed to forecast pavement distress quantities. It was found that ADT and pavement age variables were the most significant factors in the distresses quantification.     

基于计算机视觉方法的古建筑变形监测

针对古建筑整体变形和局部变形监测需要,提出基于计算机视觉方法的古建筑变形监测系统。考虑到古建筑变形微量、缓变,监测过程相机布设受限等特点,引入张正友相机标定法消除相机光轴需垂直目标的局限性,实现将任意倾斜图像转至三维坐标系进行分析,并利用亚像素插值技术提高了监测精度,测试的归一化精度达到99.5%。利用该系统分别进行了实验室振动台缩尺古建筑模型的二维平面振动监测、北京故宫博物院咸福宫井亭简化模型静态监测试验,以验证该系统用于古建结构变形监测的可行性。结果表明：基于计算机视觉方法的古建筑变形监测系统可用于古建筑受长期荷载和偶然荷载下结构变形的无损监测,其支持有靶标和无靶标两种变形监测;在偶然荷载下有、无靶标结构变形监测误差均小于8%,在长期荷载下有靶标结构变形监测误差小于4%。     

Identification of parameters of vehicles moving on bridges

This paper presents a method for identifying the parameters of vehicles moving on bridges. Two vehicle models, a single-degree-of-freedom model and a full-scale vehicle model, are used. The vehicle–bridge coupling equations are established by combining the equations of motion of both the bridge and the vehicle using the displacement relationship and the interaction force relationship at the contact point. Bridge responses including displacement, acceleration, and strain are used in the identification process. The parameters of vehicles moving on the bridge are then identified by optimizing an objective function, which is built up using the residual between the measured response time history and predicted response time history using the Genetic Algorithm. A series of case studies have been carried out and the identified results demonstrate that the proposed method is able to identify vehicle parameters very accurately. Field tests have also been performed on an existing bridge in Louisiana, and the parameters of a real truck are predicted. Since it is able to identify the parameters of moving vehicles, the methodology can be applied to improve the current weigh-in-motion techniques that usually require a smooth road surface and slow vehicle movement to minimize the dynamic effects. The methodology can also be implemented in routine traffic monitoring and control.     

基于计算机视觉技术的结构表面裂缝检测方法研究

计算机视觉技术用于混凝土结构表面裂缝检测,具有现场检测方便、效率高、客观性强的特点,但图像数据分析是该技术的核心,其中裂缝提取与定量测量较为复杂。为提高裂缝图像处理效率和准确率,将深度学习和数字图像处理技术相结合,提出一种裂缝检测方法。建立基于深度卷积神经网络的裂缝识别模型,在图像上自动定位裂缝并结合图像局域阈值分割方法提取裂缝。在裂缝宽度定量测量方面,采用双边滤波算法和三段线性变换对裂缝图像进行预处理,提高了裂缝边缘识别的精确度。通过改进边缘梯度法,实现裂缝最大宽度的定位和裂缝最大宽度的自动获取。该研究为全自动识别裂缝图像及高精度测量裂缝宽度提供了一种解决方法。     

A deep‐learning‐based computer vision solution for construction vehicle detection

This paper aims at providing researchers and engineering professionals from the first step of solution development to the last step of solution deployment with a practical and comprehensive deep‐learning‐based solution for detecting construction vehicles. This paper places particular focus on the often‐ignored last step of deployment. Our first phase of solution development involved data preparation, model selection, model training, and model validation. Given the necessarily small‐scale nature of construction vehicle image datasets, we propose as detection model an improved version of the single shot detector MobileNet, which is suitable for embedded devices. Our study's second phase comprised model optimization, application‐specific embedded system selection, economic analysis, and field implementation. Several embedded devices were proposed and compared. Results including a consistent above 90% mean average precision confirm the superior real‐time performance of our proposed solutions. Finally, the practical field implementation of our proposed solutions was investigated. This study validates the practicality of deep‐learning‐based object detection solutions for construction scenarios. Moreover, the detailed information provided by the current study can be employed for several purposes such as safety monitoring, productivity assessments, and managerial decision making.     

基于无人机技术获取岩体结构面信息方法研究

岩质边坡的稳定性主要取决于坡体内部结构面的发育特征和性质。获取边坡岩体内部结构面的几何信息,特别是产状数据,对于研究结构面的组合规律及进一步评价边坡的稳定性具有非常重要的意义。传统的结构面采集方法工作效率极低,且对于高陡岩质边坡,技术人员无法到达。无人机摄影测量技术具有非接触、高效率的突出优势,能够有效弥补传统方法的不足。以长春市某高陡岩质边坡为研究对象,使用无人机进行航空影像数据采集,建立边坡的三维实景模型,并提取结构面产状数据。经与现场实测代表性结构面产状数据对比可知,新方法的精度较高。该方法为快速准确评价高陡岩质边坡稳定性提供了依据。     

基于计算机视觉技术的手势识别步骤与方法研究

计算机视觉技术在现代社会中获得了非常广泛的应用,加强对手势识别技术的研究有助于促进社会智能化的快速发展。目前,手势识别技术的实现需要完成图形预处理、手势检测以及场景划分以及手势识别3个步骤。此外,手势特征可以分为动态手势以及静态手势,在选用手势识别方法时要明确两者之间的区别,通常情况下选用的主要手势识别技术有运用模板匹配的方法、运用SVM的动态手势识别方法以及运用DTW的动态手势识别方法等。文章对此展开研究。     

Accident assessment of vehicles on long-span bridges in windy environments

Currently, there are very few systematic analyses of vehicle performance on bridges in windy environments. There are thus no scientific data to support bridge management in this regard, such as when to close traffic on bridges. This paper presents a framework of vehicle accident analysis model on long-span bridges in windy environments. In the accompanying paper, a three-dimensional analysis of the coupled bridge-vehicle-wind system is developed. Each vehicle is modeled as a combination of several rigid bodies, axle mass blocks, springs, and dampers. Dynamic interaction analysis is then conducted on the vehicle-bridge system to predict the “global” bridge and vehicle dynamic responses without considering accident occurrences. The results of the global bridge-vehicle vibrations serve as the basis for the present accident analysis of the “local” vehicle vibrations. With the global vibrations as inputs of the accident model, the lateral response, yaw response of the vehicle, and the reaction forces of each individual wheel are obtained and the stability condition of the vehicles are analyzed. The vehicle accidents on long-span bridges are then identified with given accident criteria. The developed framework can be used in not only analyzing the vehicle performance on highways and on bridges, but also in predicting useful information for emergency preparedness agencies in developing evacuation plans.     

3D打印技术在胸腰椎骨折的椎弓根螺钉置入术中的应用效果

目的:探究3D打印技术在胸腰椎骨折的椎弓根螺钉置入术中的应用效果。方法:选取50例在本院行胸腰椎骨折的椎弓根螺钉置入术患者,将其随机分为研究组与对照组,研究组行3D打印技术辅助治疗,对照组行常规治疗。比较两组手术和术后恢复情况。结果:研究组手术时间、术中使用X线次数及术中出血量均明显低于对照组(P<0.05),且术后3个月,两组伤椎高度比及Cobb角均比术前有明显改善(P<0.05),但术后3个月两组伤椎高度比及Cobb角比较,差异均无统计学意义(P>0.05)。研究组一次性置钉成功率(96.00%)及置钉准确率(95.03%)均明显优于对照组(76.00%、80.98%),差异均有统计学意义(P<0.05)。研究组术后3个月VAS评分为(3.16±0.22)分,明显优于对照组的(3.38±0.19)分,差异有统计学意义(P<0.05)。结论:对胸腰椎骨折的椎弓根螺钉置入术中使用3D打印技术辅助治疗,能够有效提高术中置钉成功率,并降低术中X线使用频率,提高手术效率,且该治疗方法能够在保证治疗效果的同时有效降低患者术后疼痛情况,值得推广。     

A new methodology for damage assessment of bridges through instrumentation: application to the Sorraia River Bridge

Bridge Management Systems (BMSs) provide an efficient means of manipulating information about a bridge in order that its long-term health is assured and maintenance programmes can be formulated in line with budgetary constraints and funding limitations. However, some weak points remain unsolved and thus limit the possibilities of BMSs. Since accurate material deterioration and damage evolution models are not yet fully developed, one of the weaknesses of a BMS is how to decide when to act and which level of intensity should be used in maintenance/repair/strengthening operations. A high level of uncertainty is associated with the decision of undertaking these operations as the available deterioration models (chloride ingress, carbonation, alkali?–?silica reaction) are still not completely accurate due to the many variables involved (environmental, material, loading). Structural monitoring is a possible way of dealing with such a problem. Normally, in situ measurements have been used just to update deterioration models included in the damage modules of a BMS. However, in this paper a different approach is presented. Data from the instrumentation are used not to feed the damage models, but are directly used in a new module of the BMS, the so-called monitoring/control module with the objective of detecting degradation when incipient so the decision module of the BMS may respond appropriately. This module should perform damage detection in a fast, effective and accurate way. In order to achieve that, a new methodology, Interval Analysis, and a new algorithm were developed. They have been checked in laboratory tests where the potential for damage detection has been compared to other techniques. They are now being applied for the first time in a prestressed concrete bridge in Portugal. The follow-up of this application will be the basis for the adoption of the new monitoring/control module in a Portuguese BMS.     

Applications of computer vision on tile alignment inspection

Subjective visual inspection is the main quality measure for tile alignment acceptance because of a lack of standard operation procedures in Taiwan. Without quantitative specifications for tile alignment, inspectors can easily manipulate the outcome; therefore, fine craftsmanship is not valued, resulting in considerable quality variation in tile installation works. This paper proposes an automated tile installation quality assurance prototype system that uses computer vision technologies. The system receives digital images of finished tile installation and has the images processed and analyzed to capture the geometric characteristics of the finished tile surface. The geometric characteristics are subsequently evaluated to determine the quality level of the tiling work. Application of the proposed automated system can effectively improve the tile alignment inspection practice and simultaneously reduce improper manipulation during acceptance procedures.     

A new method based on the theory of fuzzy sets for obtaining an indication of risk

This paper concludes that traditional methods used in risk analysis have to be modified for adaption to the civil engineering industry. The main reason is that civil engineering systems are humanistic systems while traditional methods have been developed for mechanical systems. Consequently, the proposed method, indication of risk, is based on traditional methods such as fault tree analysis but modified according to the needs of the civil engineering industry. For humanistic systems, the method is based on the theories of possibility and fuzzy sets instead of the traditional theory of probability. The method is intended to be used to identify critical phases of the analysed systems and for optimizing system control. The method presented is exemplified by a risk analysis of a computer calculation. It is concluded that the method fulfils its intentions and deserves to be developed and examined further.     

沉降控制复合桩基在桥头跳车问题中的应用(英文)

首次将基于沉降的桩基设计方法应用到桥梁桩基的设计实践中。分别通过调整桩长和桩数,使桩基沉降从桥梁主跨往边跨逐步增大,而在路桥连接处使边跨桥墩沉降与桥坡填土沉降基本一致,实现路桥沉降协同,从而开辟了解决桥头跳车问题的新途径。按此设计而成的某桥梁,建成后对桥梁桩墩及桥坡沉降进行了长期监测,结果表明最初的设计意图得以实现。设计实践表明沉降控制桩基对于简支桥梁是完全可行的,并能同时减少桥坡处理、桩基工程以及后期维修费用,因而具有较大的推广应用的价值。     

节理岩桥裂纹扩展的热红外前兆信息研究

由于岩质边坡内部锁固段岩桥应力聚集较高,含节理的岩质边坡易发生突发性失稳。对含不同岩桥长度花岗岩试件开展单轴试验,采用红外热像仪全程监测,研究岩质边坡破裂前的热红外热像和温度变化特征,并借助声发射和高速摄像机分析裂纹开展源、裂纹扩展趋势、声发射特征及演变机制。研究表明:岩桥试件破裂前存在两种热红外前兆,未来破裂处热像异常前兆和热红外平均温度-时间曲线异常;热红外前兆出现时间提前于声发射前兆,随着岩桥长度的增加,热红外前兆提前性变得更为突出;下部预制节理裂隙尖端处的热像变化可以预测未来裂纹扩展方向,定位表面裂纹开展源头;利用断裂力学应变能密度因子理论,揭示了单轴应力状态下岩桥长度对起裂扩展的影响机制。热红外前兆相较于其他前兆形式更提前可靠,采用红外热像仪监测岩桥试件破裂前的变化特征,研究结果为节理岩质边坡的防治提供理论依据。     

A methodology for the prediction of structure level costs based on element condition states

The determination of work programmes for bridges that maximise benefit to all stakeholders requires consideration of not only the condition of the elements of which a bridge is comprised, but also the performance of the structure as a whole. This is required because although some costs can be related to the condition of the elements, others, such as the costs of travelling over the bridge, cannot. One possible methodology to do this involves linking relevant costs to structure performance states (SPS) that are determined from the element condition states (CSs). However, even a bridge with a moderate number of elements and element CSs results in a large number of possible SPSs and an unwieldy amount of required work to estimate the costs associated with each. This work can be drastically reduced, however, by exploiting the almost linear system behaviour of the bridge that can occur between many combinations of element CSs. This article presents a methodology for relating SPSs to element CSs for the purpose of determining structure level costs. This methodology is demonstrated in several examples, wherein the effects of exploiting the linearity of the system behaviour to reduce the computational effort are also explored.