Noncontact cable force estimation with unmanned aerial vehicle and computer vision

Cables and hangers are critical components of long‐span bridges, tension forces of them are needed to be accurately measured for ensuring the safety of bridges. Traditionally, cable tension forces are measured by attached accelerometers or elastomagnetic (EM) sensors, however, applying these sensors into engineering practice are time‐consuming, labor‐intensive, and highly dangerous. To address these problems, an unmanned aerial vehicle (UAV)‐based noncontact cable force estimation method with computer vision technologies was proposed in this article. Basic concept of the proposed method is to use the UAV‐installed camera for capturing vibration images of cables from a certain distance and cable dynamic properties are extracted by analyzing captured images. It includes two aspects: (a) a line segments detector (LSD) was employed for detecting cable edges from captured video and a line matching algorithm was further proposed for extracting dynamic displacements; (b) the frequency difference of adjacent higher modal frequencies identified from relative displacements of the cable was employed for cable force calculation to avoid the difficulty of extracting fundamental frequency from UAV‐captured video. It should be noted that relative displacement herein refers to the difference between displacements of two points on the same cable. Advantages of the proposed method lie in that the proposed LSD and matching algorithm are more robust than traditional correlation‐based algorithm for calculating dynamic displacements of bridge cables and it does not need to adjust predefined parameters (i.e., subset size in correlation‐based algorithms). In addition, the combination of relative displacement and frequency difference‐based cable force estimation has the capability of enhancing the Fourier spectrum magnitude of bridge cables and reducing the effect of UAV motion on extraction of cable vibration frequencies. The effectiveness and robustness of the proposed method was verified by using an experimental inclined cable and field‐testing data of a long‐span suspension bridge. Results show that calculated cable forces with UAV technology have a good agreement with reference values measured by attached accelerometers and fixed camera, demonstrating correctness and robustness of the proposed method for cable force estimation.     

Long-term performance assessment of the Telegraph Road Bridge using a permanent wireless monitoring system and automated statistical process control analytics

The purpose of this study is to advance wireless sensing technology for permanent installation in operational highway bridges for long-term automated health assessment. The work advances the design of a solar-powered wireless sensor network architecture that can be permanently deployed in harsh winter climates where limited solar energy and cold temperatures are normal operational conditions. To demonstrate the performance of the solar-powered wireless sensor network, it is installed on the multi-steel girder bridge carrying northbound I-275 traffic over Telegraph Road (Monroe, Michigan) in 2011; a unique design feature of the bridge is the use of pin and hanger connections to support the bridge main span. A dense network of strain gauges, accelerometers and thermometers are installed to acquire bridge responses of interest to the bridge manager including responses that would be affected by long-term bridge deterioration. The wireless monitoring system collects sensor data on a daily schedule and communicates the data to the Internet where it is stored in a curated data repository. Bridge response data in the repository are autonomously processed to extract truck load events using machine learning, compensate for environmental variations using nonlinear regression and to quantitatively assess anomalous bridge performance using statistical process control.     

Integrated multi‐type sensor placement and response reconstruction method for high‐rise buildings under unknown seismic loading

Structural health monitoring system has been implemented on high‐rise buildings to provide real‐time measurement of structural responses for evaluating their serviceability, safety, and sustainability. However, because of the complex structural configuration of a high‐rise building and the limited number of sensors installed in the building, the complete evaluation of structural performance of the building in terms of the information directly recorded by a structural health monitoring system is almost impossible. This is particularly true when seismic‐induced ground motion is unknown. This paper thus proposes an integrated method that enables the optimal placement of multi‐type sensors on a high‐rise building on one hand and the reconstruction of structural responses and excitations using the information from the optimally located sensors on the other hand. The structural responses measured from multi‐type sensors are fused to estimate the full state of the building in the modal coordinates using Kalman filters, from which the structural responses at unmeasured locations and the seismic‐induced ground motion can be reconstructed. The optimal multi‐type sensor placement is simultaneously achieved by minimizing the overall estimation errors of structural responses at the locations of interest to a desired target level. A numerical study using a simplified finite element model of a high‐rise building is performed to illustrate the effectiveness and accuracy of the proposed method. The numerical results show that by using 3 types of sensors (inclinometers, Global Positioning System, and accelerometers), the proposed method offers an effective way to design a multi‐type sensor system, and the multi‐type sensors at their optimal locations can produce sufficient information on the response and excitation reconstruction.     

Vibration testing of a steel girder bridge using cabled and wireless sensors

Being able to significantly reduce system installation time and cost, wireless sensing technology has attracted much interest in the structural health monitoring (SHM) community. This paper reports the field application of a wireless sensing system on a 4-span highway bridge located in Wayne, New Jersey in the US. Bridge vibration due to traffic and ambient excitation is measured. To enhance the signal-to-noise ratio, a low-noise high-gain signal conditioning module is developed for the wireless sensing system. Nineteen wireless and nineteen cabled accelerometers are first installed along the sidewalk of two neighboring bridge spans. The performance of the wireless sensing system is compared with the high-precision cabled sensing system. In the next series of testing, 16 wireless accelerometers are installed under the deck of another bridge span, forming a 4 × 4 array. Operating deflection analysis is successfully conducted using the wireless measurement of traffic and ambient vibrations.     

Estimation of gross weight,suspension stiffness and damping of a loaded truck from bridge measurements

Particle filter method (PFM) based on Bayesian inference gives a reliable estimate of hidden parameters from the noisy measured signal. A new method of vehicle parameter identification based on measured bridge response has been proposed using PFM. An uncoupled iterative technique is utilised for solving bridge vehicle interaction problem which has been used as a forward solution of the PFM. A field test under moving truck has been conducted on an existing pre-stressed concrete bridge to collect response data at different locations. Based on the extracted bridge natural frequencies and measured peak acceleration responses at five sensor locations, finite element model of the tested bridge has been updated using response surface-based model updating technique. In addition to estimation of test truck parameters using measured bridge response, dynamic wheel load induced in the bridge has been determined. Excellent agreement has been found between the measured and reconstructed bridge response using estimated parameters.     

Evaluation of a strain monitoring system for existing steel railway bridges

The old steel bridges that integrate the existing railway lines are structures built with materials that are no longer used and whose knowledge has being lost over the years, often presenting severe problems of deterioration and subjected to loading environments very different from those for which they were designed. In this context, adequate strain monitoring is a crucial tool in supporting the behavior characterization and safety assessment of these structures.This article presents and discusses the monitoring systems installed in the Trezói Bridge, within a research project aimed at developing and applying procedures for evaluation of the structural integrity of steel railway bridges. The field observations of the structural behavior were accomplished by using two different types of sensors: electric and fiber optic strain sensors. The electric monitoring system was designed and installed on the bridge to supply the experimental data for the research project, while the fiber optic monitoring system was firstly applied to evaluate the reliability of the former and to check its efficiency, and secondly to provide some redundancy of the measurements at critical locations. The obtained results are analyzed to characterize the bridge behavior and the capabilities and limitations of both types of sensors to acquire the relevant data for the bridge service condition and fatigue assessment are discussed, namely in what concerns the ability to accurately capture the static and dynamic components of the structural response and the frequency content of interest.     

铰接车辆模型识别粗糙桥梁频率和振型的数值分析

根据车桥耦合振动理论和桥梁间接测量法基本原理,对实际工程某连续梁桥建立桥梁模型,采用2辆单轴1/4车辆模型模拟测量车辆,1辆双轴半车模型模拟牵引车辆提供额外桥梁激励,三车前后铰接建立车辆模型。基于分离法原理与车辆动力学理论,利用约束方程实现任意时刻车轮与桥面接触点的位移协调关系,采用APDL编程实现铰接车辆过桥的耦合动力时程响应分析。提取前后测试车辆匀速通过不同等级粗糙桥面时车辆振动加速度时程响应,对通过桥梁同一位置处的前后测试车辆加速度数值进行相减处理并应用快速傅里叶变换识别桥梁频率。采用带通滤波技术与汉宁窗相结合的处理方法提取分离出与桥梁固有频率相关的桥频分量响应,利用桥频分量响应及其希尔伯特变换构造出与每阶固有频率相对应的振型。结果表明:在A、B、C级桥面不平整度条件下,采用铰接车辆模型识别出的桥梁前3阶频率相对误差均在1%以内; 对加速度时程响应数据加窗处理后识别出的桥梁前3阶振型MAC值均在0.95以上,满足工程精度需求; 研究结果可以为移动传感间接测量方法在桥梁检测工程中的应用提供理论参考。     

实际车辆荷载作用下的预应力混凝土连续梁桥动力响应分析及验证

以一座三跨单箱单室预应力混凝土连续箱梁桥为对象,利用车辆-桥梁耦合振动关系建立单梁车辆、桥梁运动微分方程,通过二者变形协调、相互作用力协调关系实现车辆-桥梁的耦合关系;修正了自编的桥梁动力响应计算程序,通过建立在桥梁上的高速弯板称重系统实现对实际过桥交通荷载的识别,并将识别出的实际车辆荷载信息输入已建立的桥梁动力响应计算程序,快速计算出在实际车辆荷载作用下的桥梁动力响应,并利用ANSYS软件进行静力验证,用实际过桥车流产生的动应变进行动力验证。     

Investigation of vortex-induced vibration of a suspension bridge with two separated steel box girders based on field measurements

This paper investigates the vortex-induced vibration of a twin steel box girder suspension bridge with a centre span of 1650 m based on field measurements. Two ultrasonic anemometers, two tri-axial accelerometers and 52 wind pressure sensors are installed at the quarter span section. The other 20 pressure sensors are installed in another 5 sections, and each section has 4 pressure sensors. Four vortex-induced oscillation events are measured. The analytical results indicate that the vortex-induced vibration more likely occurs in a low wind speed range of 6-10 m/s, with the wind direction nearly perpendicular to the bridge line, and low turbulence intensity. The mean pressure distribution on the surface of the bridge deck is obtained and the characteristics of fluctuant pressures are analysed by proper orthogonal decomposition (POD) method. Moreover, the spatial-temporal evolution of flow around the bridge deck is investigated. The results indicate that in the beginning stage of vortex-induced resonance, the regular vortex shedding phenomena occur only in the gap of the deck and at tailing region of downstream deck; however, when in the lock-in stage, the vortex shedding is strengthened due to the dramatic vibration, and the regular vortex shedding phenomena extend to the entire lower surface of downstream deck and the tail of upstream deck, the vortex shedding regions in the gap and lower surface link together. In the lock-in range, the span-wise correlation of the wind pressure is analysed, and the correlations of wind pressure along the bridge line are very high and do not decrease with the increase in distance.     

A filtering-based bridge weigh-in-motion system on a continuous multi-girder bridge considering the influence lines of different lanes

A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges, and in some extreme cases, it will directly lead to a bridge failure. Bridge weigh-in-motion (BWIM) system as a high performance and cost-effective technology has been extensively used to monitor vehicle speed and weight on highways. However, the dynamic effect and data noise may have an adverse impact on the bridge responses during and immediately following the vehicles pass the bridge. The fast Fourier transform (FFT) method, which can significantly purify the collected structural responses (dynamic strains) received from sensors or transducers, was used in axle counting, detection, and axle weighing technology in this study. To further improve the accuracy of the BWIM system, the field-calibrated influence lines (ILs) of a continuous multi-girder bridge were regarded as a reference to identify the vehicle weight based on the modified Moses algorithm and the least squares method. In situ experimental results indicated that the signals treated with FFT filter were far better than the original ones, the efficiency and the accuracy of axle detection were significantly improved by introducing the FFT method to the BWIM system. Moreover, the lateral load distribution effect on bridges should be considered by using the calculated average ILs of the specific lane individually for vehicle weight calculation of this lane.     

Damage Identification of a Composite Beam Using Finite Element Model Updating

Abstract:   The damage identification study presented in this article leveraged a full-scale sub-component experiment conducted in the Charles Lee Powell Structural Research Laboratories at the University of California, San Diego. As a payload project attached to a quasi-static test of a full-scale composite beam, a high-quality set of low-amplitude vibration response data was acquired from the beam at various damage levels. The Eigensystem Realization Algorithm was applied to identify the modal parameters (natural frequencies, damping ratios, displacement and macro-strain mode shapes) of the composite beam based on its impulse responses recorded in its undamaged and various damaged states using accelerometers and long-gage fiber Bragg grating strain sensors. These identified modal parameters are then used to identify the damage in the beam through a finite element model updating procedure. The identified damage is consistent with the observed damage in the composite beam.     

现有铁路钢桥应变监测系统评估

现有铁路线中旧式钢桥所用的是目前已不再使用的材料,常常会出现老化问题,使用中常遇到与设计荷载完全不同的荷载情况。因此,应变监测是保障结构性能和进行安全评估的重要工具。介绍并讨论了安装在Trezói大桥的应变监测装置系统,用该系统评估铁路钢桥结构。采用两种不同的传感器(电子传感器和光纤传感器)进行结构性能的现场观测。所设计的电子监控系统安装在桥梁上,为研究项目提供试验数据,光纤光学显示器系统用于评估系统的可靠性以确保其安全,并对试验点的测量值进行筛选。对结果进行分析,描述桥梁特性和性能,讨论两种传感器在获得桥梁使用情况和疲劳评估相关数据方面的局限性,也即关注其精确采集结构的静态与动态响应及频率的能力。     

Wireless Monitoring of a Multispan Bridge Superstructure for Diagnostic Load Testing and System Identification

Abstract: This article focuses on the deployment of a wireless sensor system (WSS) developed at Clarkson University for structural monitoring purposes. The WSS is designed specifically for diagnostic bridge monitoring, providing independent conditioning for accelerometers, strain transducers, and temperature sensors in addition to high‐rate wireless data transmission and is capable of supporting large‐scale sensor arrays. A three‐span simply supported structure was subjected to diagnostic load testing as well as ambient vibration monitoring. A total of 90 wireless and several wired sensors, including accelerometers and strain transducers were used in the deployment. Strain measurements provided capacity and demand characteristics of the structure in the form of neutral axis locations, load distributions, and dynamic allowances which ultimately produced an inventory and operating load rating for the structure. Additionally, modal characteristics of the structure, including natural frequencies and mode shapes, were derived from measured accelerations and discussed briefly.     

Vehicle-bridge coupled vibrations in different types of cable stayed bridges

Numerical analyses of the coupled vibrations of vehicle-bridge system and the effects of different types of cable stayed bridges on the coupled vibration responses have been presented in this paper using ANSYS. The bridge model and vehicle model were independently built which have no internal relationship in the ANSYS. The vehicle-bridge coupled vibration relationship was obtained by using the APDL program which subsequently imposed on the vehicle and bridge models during the numerical analysis. The proposed model was validated through a field measurements and literature data. The judging method, possibility, and criterion of the vehicle-bridge resonance (coupled vibrations) of cable stayed bridges (both the floating system and half floating system) under traffic flows were presented. The results indicated that the interval time between vehicles is the main influence factor on the resonance excitation frequency under the condition of equally spaced traffic flows. Compared to other types of cable stayed bridges, the floating bridge system has relatively high possibility to cause vehicle-bridge resonance.     

Active learning structural model updating of a multisensory system based on Kriging method and Bayesian inference

Model updating techniques are often applied to calibrate the numerical models of bridges using structural health monitoring data. The updated models can facilitate damage assessment and prediction of responses under extreme loading conditions. Some researchers have adopted surrogate models, for example, Kriging approach, to reduce the computations, while others have quantified uncertainties with Bayesian inference. It is desirable to further improve the efficiency and robustness of the Kriging-based model updating approach and analytically evaluate its uncertainties. An active learning structural model updating method is proposed based on the Kriging method. The expected feasibility learning function is extended for model updating using a Bayesian objective function. The uncertainties can be quantified through a derived likelihood function. The case study for verification involves a multisensory vehicle-bridge system comprising only two sensors, with one installed on a vehicle parked temporarily on the bridge and another mounted directly on the bridge. The proposed algorithm is utilized for damage detection of two beams numerically and an aluminum model beam experimentally. The proposed method can achieve satisfactory accuracy in identifying damage with much less data, compared with the general Kriging model updating technique. Both the computation and instrumentation can be reduced for structural health monitoring and model updating.     

桥梁施工控制技术(续)

（续上期） 根据上述分析,该系统可通过安装在桥墩上的高精度角位移传感器,将采集的角度信号经信号调整装置送至计算机,经数据处理后给出大桥各墩的水平位移值。再者,顶推过程中测力装置将测得的油压信号也传送计算机,经换算给出顶推力。计算机实时监测墩顶位移和顶推力,并在屏幕上显示这些数据。图8为角位移与线位移关系及测量原理图。     

Performance Evaluation of TMD under Typhoon Using System Identification and Inverse Wind Load Estimation

Abstract: The typhoon behavior and performance of a tuned mass damper (TMD) are presented based on the system identification and the inverse modal wind load estimation. The TMD was installed on a 39‐story, 184.6‐m steel building located in Incheon, Korea with a monitoring system consisting of an anemometer, accelerometers, and internet‐based data logging system. On September 2, 2010, the building experienced the Kompasu Typhoon, in which the peak wind speed, measured by an anemometer installed on the roof floor, was 49.7 m/s. To analyze the behavior of the building during the typhoon, the dynamic properties of building and TMD are identified from the measured responses. The modal wind load is then inversely estimated from the TMD and building accelerations using a Kalman filter, and the vibration reduction performance of the TMD is evaluated. The analysis results show that the typhoon‐induced vibration was reduced significantly due to the installation of TMD.     

Local finite element model updating with forced vibration measurements

Finite element (FE) model updating based on the method of selective sensitivity analysis is applied to a girder bridge. The response patterns are chosen in accordance with the selective sensitivity criteria and result in a set of four independent local girder bridge response patterns. The excitation of these patterns is conducted with a four-shaker system. This effectively reduces the degrees of freedom of the corresponding FE model from 486 to 7. Excitations and responses are measured at three nodes of each selective sensitive pattern. Local finite element model updating is conducted by minimising the influence of the rest of the structure and by maximising the relative sensitivities with the inclusion of the fourth shaker. This excitation is shown to be model independent; therefore, updating is separated from the measurement process. An independent verification shows the ability of the proposed method to identify submodel parameters. The sensitivities of the accelerometers used were very small, which impacted the data quality. Updating results are discussed considering these limits.     

Statistical analysis of online strain response and its application in fatigue assessment of a long-span steel bridge

This paper covers reliability assessment of the fatigue life of a bridge-deck section based on the statistical analysis of the strain–time histories measured by the structural health monitoring system permanently installed on the long-span steel bridge under study. Through statistical analysis of online strain responses in the frequency domain using multiple linear regression, a representative block of daily cycles of strain history is obtained. It is further assumed that all cycles of online strain response during bridge service are repetitions of the representative block. The rain-flow counting method is then used to determine the stress spectrum of the representative block of daily cycles. The primary assessment of fatigue life at a given value of failure probability is undertaken for the sample component in a bridge-deck section by using the classification of details for welded bridge components and the associated statistical fatigue model provided by the British Standard BS5400. In order to evaluate bridge fatigue at any value of failure probability, a modified probability model is proposed based on BS5400. The fatigue life of the considered component in the bridge-deck section is then evaluated for some other values of probability of failure which are not included in BS5400 by use of the modified probability model. The analytical results show that the modified model is practical for reliable evaluation of the service life of existing bridges under random traffic loading.     

Multi-scale fatigue damage prognosis for long-span steel bridges under vehicle loading

Fatigue damage prognosis for long-span steel bridges is of the utmost importance in bridge maintenance and management. In this study, a multi-scale fatigue damage prognosis algorithm is developed to calculate the trans-scale fatigue damage accumulation of newly-built long-span steel bridges under vehicle loading. The necessity and procedure of establishing a multi-scale finite element (FE) model of a newly-built long-span bridge for fatigue damage prognosis are first introduced. The future vehicle loading on the bridge is forecasted using the recorded weigh-in-motion (WIM) data and the agent-based traffic flow micro-simulation method. Then, the multi-scale fatigue damage prognosis algorithm is developed based on the multi-scale FE model and using the future vehicle loading. Finally, the proposed algorithm is applied to a newly-built long-span cable-stayed bridge for the time period from 2010 to 2020. The results show that the macro-scale fatigue damage accumulation and micro-scale short crack evolution of the critical components of the bridge can be simultaneously predicted and visualized. The proposed algorithm can be used as a numerical tool for fatigue damage prognosis of steel bridges where (or near where) WIM station is installed.