Health monitoring of flexural steel structures based on distributed fibre optic sensors

In our previous study, a distributed long-gauge fibre optic sensing system (with the ability to obtain effective average strain, or macro-strain, distributions) for practical adaptation in civil structural health monitoring was developed and verified. The present paper is devoted to proposing an integrated health monitoring scheme for elastic beam-like structures, where flexure dominates structural responses, based on static testing and measurements using the developed sensors. A series of experimental investigations on steel beams with different levels of damage are first carried out. The static strain measurements from distributed sensors are characterised and some concerns on the data processing and feature extraction are discussed. On the basis of the extracted features, structural health monitoring (SHM) investigations are deployed in three parts: damage identification with no requirement for a structural analytical model, parametric estimation based on finite element (FE) models, and evaluation of structural global behaviour. By comparing to traditional transducers such as linear variable displacement transducers (LVDTs) and foil ‘point’ strain gauges, the ability and ascendancy of the sensors developed here for SHM purposes are verified. A comprehensive health monitoring strategy for steel flexural structures based on the distributed strain sensors array is proposed finally.     

Planning and executing construction inspections with unmanned aerial vehicles

Unmanned aerial vehicles (UAV) are increasingly recognised as a utility for inspection applications in construction. In order to create measurable benefit over traditional inspection methods, an inspection concept for UAVs must be integrated and automated. This work is the result of an ongoing effort to create a workflow for the structured planning, simulation and execution of inspection tasks. An application was developed that allows the operator to plan inspections in a 3D environment. The application automatically generates collision-free flight paths based on Building Information Modelling (BIM) data. A realistic simulation environment provides a good understanding of the flight dynamics caused by inhibiting factors, such as disturbances of the positioning system. A case study confirms the hypothesis of the inspection concept and hints at technical limitations of autonomous UAVs that need to be overcome in subsequent development efforts.     

无人机遥感技术在土地违法监测中的应用研究

针对传统土地变更调查工期长、误差大、费用高的问题,同时方便土地执法部门及时对土地违法情况进行整顿,文章提出了一种利用无人机遥感进行土地违法监测的思路和方法。通过对无人机遥感技术进行概述,在试验区进行航飞实验,采用Inpho软件对无人机影像进行处理生成正射影像。在eCognition中采用基于面向对象的分类方法,通过绿叶指数(Green leaf index,GLI)进行两期无人机正射影像的对比,实现变化图斑的自动提取,并经过野外验证得到图斑识别的正确率为81.8%,从而形成了一套无人机遥感技术应用于土地违法监测的完整方案。     

Image‐based crack assessment of bridge piers using unmanned aerial vehicles and three‐dimensional scene reconstruction

Crack assessment of bridge piers using unmanned aerial vehicles (UAVs) eliminates unsafe factors of manual inspection and provides a potential way for the maintenance of transportation infrastructures. However, the implementation of UAV‐based crack assessment for real bridge piers is hindered by several key issues, including the following: (a) both perspective distortion and the geometry distortion by nonflat structural surfaces usually appear on crack images taken by the UAV system from the pier surface; however, these two kinds of distortions are difficult to correct at the same time; and (b) the crack image taken by a close‐range inspection flight UAV system is partially imaged, containing only a small part of the entire surface of the pier, and thereby hinders crack localization. In this paper, a new image‐based crack assessment methodology for bridge piers using UAV and three‐dimensional (3D) scene reconstruction is proposed. First, the data acquisition of UAV‐based crack assessment is discussed, and the UAV flight path and photography strategy for bridge pier assessment are proposed. Second, image‐based crack detection and 3D reconstruction are conducted to obtain crack width feature pair sequences and 3D surface models, respectively. Third, a new method of projecting cracks onto a meshed 3D surface triangular model is proposed, which can correct both the perspective distortion and geometry distortion by nonflat structural surfaces, and realize the crack localization. Field test investigations of crack assessment of a real bridge pier using a UAV are carried out for illustration, validation, and error analysis of the proposed methodology.     

Web-Based Structural Health Monitoring of an FRP Composite Bridge

Abstract:   To develop an understanding of the long-term performance of fiber reinforced polymer (FRP) composite bridge structures, a health monitoring scheme utilizing wireless technology was implemented on the Kings Stormwater Channel Bridge. The bridge, which is located on a major state highway in California, utilizes FRP composite girders and deck panels. The data collected by a comprehensive array of sensors are transmitted wirelessly, and processed in real-time remotely. Computer-based automated analysis algorithms process the incoming data to provide an assessment of structural response. Effects, due to time-based deterioration, and irregularities are determined using modal parameters, in terms of damage localization indices and an estimated damage severity. The results, made available via a web-based interface, enable appropriate action to be authorized for preliminary maintenance or emergency response prior to actual on-site inspection. It is expected that such systems will not only give engineers a valuable tool in monitoring the structural performance of critical bridge systems, but will also provide important information related to durability, design criteria, and long-term response of FRP composite structures.     

High-resolution model reconstruction and bridge damage detection based on data fusion of unmanned aerial vehicles light detection and ranging data imagery

Damage detection is essential for the maintenance of transportation infrastructure that experiences high daily traffic levels in potentially extreme environments and changes in use patterns. However, traditional physical inspection is always labor-intensive, subjective, and biased, lacking the objective perspective required for a comprehensive and reliable assessment. Recently, unmanned aerial vehicles (UAVs) combined with emerging high-performance sensor(s) have been intensively researched. Here, we present an aerial bridge surface survey method that can be used to assess damage. Existing damage detection methods focus on single types of damage and are limited in locating global damage, whereas our method detects two types of damage on the surface and marks them in a panoramic image. The workflow involves three steps: data acquisition using a meticulous UAV flight strategy that covers the entire surface, data processing using image-based and point-cloud models after polynomial rectification, and data output (i.e., damage detected by the combined models). To verify the method, a field test detected damage to two real bridges. A UAV equipped with a camera and light detection and ranging (LiDAR) equipment was employed. Experiments demonstrate the effectiveness of the proposed method, which is capable of producing accurate outputs and detecting damage with an average position error of 13.37 mm and a relative size error of 25.25%. Owing to the data fusion model taking advantage of two-dimensional (2D) images and 3D LiDAR data, it outputs a high-resolution 3D model and avoids environmental disturbances. After decision-making-level damage fusion, all position and size properties of damage information are computed into a panoramic damage image. This panoramic image showing all detecting damage helps technicians perform maintenance; the image can be zoomed to focus on any issue individually.     

Investigation concerning structural health monitoring of an instrumented cable-stayed bridge

In Hong Kong, a sophisticated long-term structural health monitoring system has been devised by the Highways Department of HKSAR Government to monitor the structural performance and health conditions of three cable-supported bridges. On-structure instrumentation systems for two new long-span bridges are also being implemented. The implementation of these monitoring systems highlights the necessity for developing a monitoring-based structural health evaluation paradigm for long-span bridges. This paper describes the research directed towards this that has been conducted in the Hong Kong Polytechnic University. Taking the instrumented cable-stayed Ting Kau Bridge as a paradigm, the research covers the development of an index system and a database system for monitoring data management, the modelling of the environmental variability of measured modal properties with the intention of eliminating environmental effects in vibration-based damage detection, and the feasibility of using measured modal properties from the deployed vibration sensors for structural damage identification.     

基于分布式传感网络的结构模态识别方法

结构的模态参数识别是结构健康监测系统的基本任务。随着工程结构的日益大型化和复杂化,振动测试时需要布置大量的传感器。传统的集中采集和处理技术将难以胜任海量数据的处理要求,采用无线智能传感器的结构健康监测系统正是应运而生的新方向,而分布式采集和处理是其特点。在无线智能传感网络拓扑结构中采用分布式算法求解结构整体振型,利用随机子空间法识别各子结构模态,结合粒子群优化算法调整子振型获取结构整体振型。通过混凝土钢管拱桥模型试验验证了分布式算法的可行性,并利用模态置信度(MAC)对比分析了由分布式模态识别方法和集中式模态识别方法得到的结果,结果表明两种算法吻合较好。     

A New Approach for Health Monitoring of Structures: Terrestrial Laser Scanning

Abstract:   A new approach is presented for health monitoring of structures using terrestrial laser scanning (TLS). Three-dimensional (3D) coordinates of a target structure acquired using TLS can have maximum errors of about 10 mm, which is insufficient for the purpose of health monitoring of structures. A displacement measurement model is presented to improve the accuracy of the measurement. The model is tested experimentally on a simply supported steel beam. Measurements were made using three different techniques: (1) linear variable displacement transducers (LVDTs), (2) electric strain gages, and (3) a long gage fiber optic sensor. The maximum deflections estimated by the TLS model are less than 1 mm and within 1.6% of those measured directly by LVDT. Although GPS methods allow measurement of displacements only at the GPS receiver antenna location, the proposed TLS method allows measurement of the entire building's or bridge's deformed shape, and thus a realistic solution for monitoring structures at both structure and member level. Furthermore, it can be used to create a 3D finite element model of a structural member or the entire structure at any instance of time automatically. Through periodic measurements of deformations of a structure or a structural member and performing inverse structural analyses with the measured 3D displacements, the health of the structure can be monitored continuously.     

Unmanned aerial vehicle inspection of the Placer River Trail Bridge through image-based 3D modelling

Unmanned aerial vehicles (UAV) are now a viable option for augmenting bridge inspections. Utilising an integrated combination of a UAV and computer vision can decrease costs, expedite inspections and facilitate bridge access. Any such inspection must consider the design of the UAV, the choice of cameras, data acquisition, geometrical resolution, safety regulations and pilot protocols. The Placer River Trail Bridge in Alaska recently served as a test bed for a UAV inspection methodology that integrates these considerations. The end goal was to produce a three-dimensional (3D) model of the bridge using UAV-captured images and a hierarchical Dense Structure-from-Motion algorithm. To maximise the quality of the model and its benefits to inspectors, this goal guided UAV design and mission planning. The resulting inspection methodology integrates UAV design, data capture and data analysis together to provide an optimised 3D model. This model provides inspection documentation while enabling the monitoring of defects. The developed methodology is presented herein, as well as analyses of the 3D models. The results are compared against models generated through laser scanning. The findings demonstrate that the UAV inspection methodology provided superior 3D models with the accuracy to resolve defects and support the needs of infrastructure managers.     

应用压电陶瓷传感器于桥墩的损坏诊断

该研究主要为运用压电传感器进行宜兰牛斗桥现地混凝土桥墩结构的健康诊断。所使用的压电传感器为利用压电陶瓷材料所制成,利用基本波动力学及压电材料可发射应力波亦可接收应力波的特性,进行现地混凝土桥墩结构的健康诊断研究。结构健康诊断为将压电传感器埋入RC桥墩结构内,当试体受到破坏时,由压电传感器发射应力波及由不同位置的压电传感器来撷取应力波,利用应力波振幅随着结构破坏程度、裂缝增加而减少振幅的特性,可知RC桥墩结构物的损坏程度。利用数值分析得到损坏指针,即可判断出结构物损坏程度,其量测结果随着结构物的损坏程度越严重,损坏指标也越高。当桥墩结构物达到严重破坏程度时,所量测到的损坏指标也相当接近最大值。该研究为压电传感器第一次应用于现地桥墩结构,除可验证压电材料用于实际结构物检测的可行性,判断混凝土结构的健康程度,另实为土木结构非破坏检测上的一种新的检测方法。     

无人机用于形态复杂实验对象量测的精度分析

采用大疆精灵4RTK无人机,设计3种不同的飞行方案,模拟倾斜摄影测量技术,运用Context Capture三维建模软件进行处理,实现对形态复杂的雕塑景观进行三维重建,得到雕塑实验对象的三维模型.利用RTK采集实验对象的地面控制点坐标,进行实验对象三维场景的平面精度、高程精度和特定边长精度分析,并结合三维模型纹理目视解...     

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.     

Development of an integrated structural health monitoring system for bridge structures in operational conditions

This paper presents an overview of development of an integrated structural health monitoring system. The integrated system includes vibration and guided-wave based structural health monitoring. It integrates the real-time heterogeneous sensor data acquiring system, data analysis and interpretation, physical-based numerical simulation of complex structural system under operational conditions and structural evaluation. The study is mainly focused on developing: integrated sensor technology, integrated structural damage identification with operational loads monitoring, and integrated structural evaluation with results from system identification. Numerical simulation and its implementation in laboratory show that the system is effective and reliable to detect local damage and global conditions of bridge structures.     

Health monitoring system of a self-anchored suspension bridge (planning,design and installation/operation)

Recent advances in sensing technologies make it feasible and practic al to install sensors on expensive civil infrastructures, such as bridges, for safety monitoring during construction and long-term assessment of the structures condition. This paper presents a case study of a structural health monitoring (SHM) and bridge management system (BMS) installed in Yeongjong Bridge in South Korea. This is a self-anchored suspension bridge on the expressway that links Seoul to Incheon International Airport. Experimental data have been collected from the bridge for two years, since its completion in 2000. This paper presents a list of examples where the structural health monitoring system can be applied and provides general guidelines and recommendations for deploying a monitoring system in terms of (1) sensing and instrumentation, (2) data collection and signal processing, and (3) information processing.     

土木结构的光纤光栅与布里渊共线测试技术

针对目前分布式应变测试技术存在精度和空间分辨率均较低、采样频率低、系统造价高等缺点,以及高精度的单点应变测试技术无法解决范围广、距离长、变形大、位置隐蔽等特征的结构损伤监测问题,考虑实际工程传感器布设占据结构健康监测系统造价的极大比例,提出将光纤布里渊全尺度传感技术和准分布式高精度光纤布拉格光栅测试技术相结合构建融合全尺度分布式和局部高精度共线的智能监测方法与集成系统,并研制开发出支持该技术方便实施的高强、高耐久性传感探头,即无焊点超长尾纤光纤光栅—纤维增强聚合物复合智能筋,通过三点弯曲钢筋混凝土梁应变分布试验和实体平行钢丝拉索索力测试试验,验证了该系统的有效性和突出优点。该技术有望为实际大规模、大跨度复杂结构提供理想的损伤监测手段。     

Case studies of high-sensitivity monitoring of natural and engineered slopes

High-sensitivity monitoring solutions are crucial for early warning systems of earth structures. In this paper, we discuss the design and implementation of such systems for natural and engineered slopes using two case studies. At the Gradenbach Observatory, one key element of the monitoring system is a large fiber optic strain rosette embedded in the slope. We demonstrate that the strain rosette can depict landslide deformations much earlier than geodetic sensors like GPS or total stations and is therefore well suitable for an early warning system. In a second application we report the construction of a reinforced earth structure using geogrids. A distributed fiber optic measurement system was installed to measure the current operating grade of the geogrids within the earth structure. About 2 km of Brillouin sensing cables were installed in the project area. It is demonstrated that the developed monitoring system is well suited for assessing the current state of health of reinforced earth structures.     

Numerical evaluation of multi-metric data fusion based structural health monitoring of long span bridge structures

This work focuses on structural health monitoring of long span bridges for damage detection. A feature extraction level data fusion based damage isolation strategy is presented using multi-metric sensing. The multi-metric sensing uses two types of sensors, namely strain sensors and accelerometers. The methodology combines the advantages offered by each type of sensors, while at the same time overcomes their limitations. The flexibility index method is applied and the flexibility matrices based on the strain and displacement data are combined after performing co-ordinate transformation. A study has been carried out on a simulated finite element model of the Great Belt East Bridge where realistic damage scenarios like damage in the girder, breaking of hanger cables, pier settlement, and loss of cable pretension were introduced on the structure. The study indicates that multi-metric sensing is indeed necessary as it reduces the possibility of false detections and increases the sensitivity and robustness of the methodology.     

光纤传感器在土木工程健康监测中的应用

总结了当前土木工程结构健康监测的研究和发展趋势。重点回顾了光纤传感器在各种主要土木结构中的健康监测,包括建筑物、桩、桥、管道、隧道和大坝。描述了光纤传感器的三种用途。最后,讨论了在土木结构健康监测中封装和实现光纤传感器存在的问题和有前途的研究方向。     

Extreme value theory-based structural health prognosis method using reduced sensor data

This paper presents an extreme value theory (EVT)-based structural health prognosis method that can be used for estimating the quantile values of remaining useful life (RUL) of monitored structure with reduced sensor data. Massive sensor data generated from online structural health monitoring system can be utilised to provide more refined prognosis results such as statistical distribution of RULs. By using the moment estimator from EVT, only a small portion of the full sensor data-set is actually used for estimating the quantile values of the RUL. This can considerably cut the computing time required for structural health prognosis. As a requirement for implementing the EVT-based prognosis, monotonicity relation between damage index (either measured or derived from sensor data) and RUL values has to be satisfied though. Common prognosis problems in civil engineering include fatigue cracking in steel structures and steel rebar corrosion in reinforced concrete structures. To illustrate the EVT-based prognosis, the monotonicity condition is shown for the selected degradation models in two case studies involving fatigue life estimation and pitting corrosion life of steel reinforcing rebar, respectively. The results show that EVT-based structural health prognosis method is computationally efficient without loss of much accuracy.