Showing papers in "Journal of Civil Structural Health Monitoring in 2018"

Review of machine-vision based methodologies for displacement measurement in civil structures

Abstract: Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video-processing procedures in this paper are summarised as a three-component framework: camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields, bridge deformation and cable vibration measurement, are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented, e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions.

Bridge inspection: human performance, unmanned aerial systems and automation

Abstract: Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification.

Health assessment and ambient vibration testing of the “Ponte delle Torri” of Spoleto during the 2016–2017 Central Italy seismic sequence

Abstract: The Ponte delle Torri is a large medieval masonry bridge, one of the main architectural heritage of Spoleto, Italy. The location of the bridge is less than 50 km from the main epicenters of the recent Central Italy earthquakes (Mw > 5.0) that occurred between August 2016 and February 2017. In addition, some minor quakes of the sequence (Mw between 3.0 and 4.0) occurred within 10 km from the bridge, causing some damages and fear among the population around Spoleto. In this context, the present paper aims at contributing to understand the effects on the structural health of the bridge by analyzing the ambient vibration data acquired before, during and after the seismic sequence, as changes in the dynamic behavior of the structure might indicate the evolution of the state of damage of the monument. In particular, vibration data were processed by modal analysis techniques for mutual validation of the extracted modal parameters. Environmental and vibration data were simultaneously acquired to take into account the seasonal effects on the dynamic behavior. Through a preliminary finite-element model (FEM) the modal shapes were obtained to choose the positions where to locate the sensors for the vibration spot acquisition session of June 2015. The same positions were acquired in October 2016 and at the end of May 2017. Subsequently, a more detailed FEM was produced based on a 3D reconstruction by structure-from-motion stereo-photogrammetry technique with high-resolution photos from unmanned aerial vehicle of the bridge. The model was validated through comparison with the damage pattern experienced by the bridge and then used for assessing the seismic safety by means of both, nonlinear dynamic and static push-over analyses.

Continuous monitoring of a challenging heritage tower in Monza, Italy

Abstract: A recent survey of the historic complex of “Santa Maria del Carrobiolo” in Monza (Italy) highlighted that two sides of the bell-tower are directly supported by the load-bearing walls of the apse and South aisle of the neighbouring church. After the discovery of the weak structural arrangement of the building, a network of 10 displacement transducers, integrated by five temperature sensors, was installed in the tower to check the opening variation of the main cracks. Subsequently, ambient vibration tests were performed and closely spaced modes with similar mode shapes were clearly identified: since the dynamic characteristics of the tower are quite different from those obtained in past experimental studies of similar structures and conceivably related to the construction sequence, a simple dynamic monitoring system was installed in the tower to complete the health monitoring aimed at the preservation of the historic structure. The paper—after a brief description of the tower and a summary of selected evidences provided by on-site survey, historic research and static monitoring—focuses on the dynamic characteristics identified in the preliminary ambient vibration tests and the main results of 1-year dynamic monitoring. In order to assess the effects of changing temperature on the natural frequencies of the investigated tower, especially in view of the removal of those effects needed for an effective performance assessment, simple correlation studies between modal frequencies and temperature are presented and discussed.

An impedance-based structural health monitoring approach for looseness identification in bolted joint structure

Abstract: The task of structural safety has been always vital throughout the life span of a structure. The situation deteriorates, when it is subject to repeated loading as seen in cases of railway joints. Generally, the bolted joints are frequently used connections for mainteinance of structural integrity. The most common type of fault observed in bolted joints is looseness of the nuts and bolts which leads to a damaging change by contact pressure that may cause an untoward incident. To avoid such incidents, it is required to monitor the bolted joints very meticulously and regularly. This study presents an investigational work for the looseness assessment of bolted butt joint structure using glued piezoelectric transducer and the implementation of an analytical approach based on the electro-mechanical impedance (EMI) method. For the purpose of investigation, the experiments are being conducted in pristine condition of the structure, wherein the plate bars and girder beam are bolted with four similar bolts without being pressed adequately and no part of the joint is glued. The test measurement of undamaged state and loosed state has been conducted using impedance-based monitoring approach. To study the effectiveness of the proposed method, an experimental investigation is conducted using the impedance chip AD5933 on a bolted joint structure. The results provide cogent indication about the use of piezoelectric lead zirconate titanate sensor based on EMI method for monitoring the status of the bolted joint structures.

A numerical–experimental study for structural damage detection in CFRP plates using remote vibration measurements

Abstract: The performance and behavior of composite structures can be significantly affected by degradation and damage. Degradation can be caused by exposure to environmental conditions and damage can be caused by handling conditions, such as impact and loading. Such damages are not always visible on the surface and could potentially lead to catastrophic structural failures. This paper addresses the specific challenge of using numerical simulations to assess damage detection techniques applied to composite laminated plates. This study aims to solve the direct and inverse problem of damage detection by combining numerical and experimental data. Finite element analysis was carried out to analyze the direct problem of mechanical response. Heuristic optimization techniques were used to solve the direct and inverse problem by combining data from a model with that of the experiment to identify structural damage. This study also sought to update the finite element model by minimizing the objective function. The structure studied was constituted of a composite plate. Two damage models were used: (i) circular hole and (ii) delamination (local stiffness reduction). The results of the optimization algorithms show good efficacy in the detection of structural damage, identifying the damaged location on the structure and also quantifying the size of the damage in real composite structures. A method has been proposed to identify the damage in CFRP plates using remote vibration measurements. Furthermore, the numerical simulation and experimental tests have been used to verify the method.

Post-earthquake controls and damage detection through structural health monitoring: applications in l’Aquila

Abstract: The paper presents structural health monitoring (SHM) activities performed on some representative cultural heritage (CH) buildings in the city of l’Aquila after the strong earthquake (Mw = 6.3) that struck the Abruzzo region (central Italy) on April 6, 2009. The severity and the extent of damages caused by the earthquake to historical buildings and monument were never reached before in the recent Italian earthquake history. Emergency activities started immediately after the earthquake to protect CH structures, including damage survey and design/implementation of temporary safety measures. Some historic buildings were soon equipped with monitoring systems in order to assess the level of damage and verify the effectiveness of the executed provisional interventions. The paper focuses in particular on two case studies, i.e. the Spanish Fortress and the Civic Tower. The results of preliminary investigations are reported, including damage survey and operational modal analysis for modal parameter identification using ambient vibration tests. 3-year static and dynamic monitoring features, automatically extracted from raw data acquired by continuous monitoring systems, were then processed using a data-driven approach based on regression analysis to filter out the environmental effects. Following this approach data are decomposed into their reversible and irreversible components, the latter being associated with active damaging processes and the residual structural performance of the two buildings assessed.

Machine-learning-based approach for post event assessment of damage in a turn-of-the-century building structure

Abstract: The work presented in this article describes development of a machine learning (ML)-based platform for condition assessment of building structures in the aftermath of extreme events. The methods employed in the study include support vector machines, neural networks, and Gaussian Naive Bayes techniques for training of the structural health monitoring model. The ML platform relates the change in stiffness, and strains in various structural components of the system to the intensity and location of damage. Evaluation of the proposed method was accomplished by using it for the characterization of damage in a turn-of-the-century, six-story building with timber frames and masonry walls. The building was damaged due to differential settlement of its foundation. Application of the proposed method in the building required load testing of selected structural elements, and use of the strains acquired from the field tests as input to the ML model.

Evaluating the damage degree of cracking in facades using infrared thermography

Abstract: The study of facade cracking is of great importance in the investigation of pathologies and degradation, as well as in the rehabilitation processes of buildings. Cracking is one of the major defects in facades; so assessing damage severity is necessary to define the best maintenance and rehabilitation strategies. The infrared thermography has been increasingly used as an inspection technique to identify and map facade defects and their severity. The use of hygrothermal simulation to understand the dynamics of the heat flux allows to observe important references that can help in the interpretation of the thermogram under different heating or cooling conditions. This study investigates the use of the quantitative passive thermography to measure the damage degree of cracks in a building facade. The crack depth was evaluated by the Delta-T values investigated in the three cracked regions. For the width, the variation of the studied temperature in a line transversal to the crack was used. The analysis was performed at a distance of 33 m from the facade. The conclusions corroborated the importance of the hygrothermal simulation as a pre-thermography technique, which made it possible to limit the period of investigation focusing on the phenomena of interest. It is also observed that it is possible to obtain quantitative values of the degree of damage by thermographic investigation. The measurement of the damage degree, in turn, brings important contribution to the application of the inspection technique.

Structural performance monitoring of buried pipelines using distributed fiber optic sensors

Abstract: In this study, a method involving the use of distributed fiber optic temperature and strain sensors is presented to quantitatively assess the structural performance for buried pipelines by considering both longitudinal bending load and axial thermal load. The monitoring scheme of distributed strain and temperature sensors is proposed based on the pipeline structural analysis, and the assessment approach is formulated using the distributed monitoring data. The time-spatial variation in the bending strain and temperature of the burial pipelines are monitored using distributed fiber optic sensors. The structural performance of the pipeline is then assessed with the monitored data in conjunction with the pipe parameters and internal pressure. A field application was performed on a buried gas pipeline to investigate the availability of the proposed method and the results from the site application demonstrate that the proposed method effectively assesses the structural performance of the burial pipelines with the distributed strain and temperature data.

Study of FRP bars under tension using acoustic emission detection technique

Abstract: Acoustic emission (AE) signal has proved to be a useful tool for monitoring structures reinforced with FRP composites such as Fiber Reinforced Polymer (FRP) reinforced beams, carbon FRP (CFRP) sheets, or steel fiber reinforced concrete. This work focuses on studying the behavior of pultruded FRP bars, which have been manufactured using continuous fibers. Different configurations of CFRP and glass FRP (GFRP) bar specimens subjected to tensile load were monitored using AE technique. Several algorithms were used for signal processing to analyze AE signals in the time domain and in the time–frequency domain. The signal processing techniques extracted the amplitude, cumulative events, duration, energy, rise time, number of counts, cumulative counts, and frequency peaks of the acoustic signals. The frequency maxima were determined for different amplitude signals using short-time Fourier transform (STFT). Cumulative counts of AE signals showed significant changes in the slope during the tension test, while the stress–strain relationship of the FRP rods showed virtually no deviation from linearity. CFRP bars recorded higher amplitude signals and lower duration, than GFRP bars. The acoustic emission characteristics presented in this work show strong correlations with ultimate load and may prove useful for damage prediction.

Structural health monitoring techniques implemented on IASC–ASCE benchmark problem: a review

Abstract: Various structural health monitoring techniques have been developed over the years. Due to the lack of a common platform to test the efficiency of these methods, the damage analysis models have been tested on different structures selected according to the choice of researches. Therefore, perfect comparison among the models was not possible. In light of this event, a benchmark structure was developed providing a common ground to analyse the effectiveness of the damage detection strategies. This structural damage analysis consists of different damage patterns, major damages and minor damages. The damage detection algorithms were tested for the detection of these different damage patterns and the effectiveness against noise contamination. Also the amount of data required for the algorithms to effectively detect damage was also recorded, which indicated the efficiency of the method applied. The paper deals with the application of different damage detection techniques on the ASCE benchmark Phase-I and Phase-II structure and studies their efficiency against the other structures. A brief comparison has been made among different damage detection models such as Bayesian model, neural network, autoregressive models, and model update. These methods have been successfully implemented on the benchmark structure and their efficiencies have been measured in terms of noise contamination, the amount of data required to measure the damage and the detection of damage (major and minor). Out of all the techniques discussed, model update technique, wavelet approach, autoregressive technique, convolution neural network and synchrosqueezed wavelet transform have proved to a robust damage analysing tool.

Dynamic characterisation of a historic bell-tower using a sensitivity-based technique for model tuning

Abstract: The most relevant results of the vibration-based investigations performed on a historic masonry tower in Italy namely the Santa Maria a Vico bell-tower is here presented. The first part of the study involves preliminary full-scale ambient vibration measurements in operational conditions and dynamics-based finite element (FE) modelling. At first, a manual tuning of the uncertain parameters of the model was carried out to adjust material properties, soil-structure interaction and constraining effect of the neighbouring structures. Then, based on the sensitivity analysis, only the most sensitive parameters were chosen as updating parameters. Finally, a model updating technique based on a sensitivity-based method was used to minimise the error between experimental vibration data and numerical response values. To this aim, a residual vector defined as the weighted difference between the measured quantities and calculated quantities was used. The uncertain structural parameters of the FE model were identified by minimising a robust penalty function. The calibrated model was used as an important tool for the seismic assessment of the structure using pushover analysis. Since the assumed value of the masonry compressive strength is the most sensitive parameter of non-linear behaviour, a sensitivity analysis was performed considering reference values in the range of interest. The seismic safety corresponding to increasing levels of the seismic hazard was finally investigated.

Making good use of structural health monitoring systems of long-span cable-supported bridges

Abstract: Many long-span cable-supported bridges have emerged in recent years, but are exposed to harsh environment conditions. The installation of long-term structural health monitoring (SHM) systems to the bridges has become a trend to monitor their loading conditions, assess their performance, detect their damage, and guide their maintenance with the utmost goals of ensuring their functionality, safety and sustainability. Nevertheless, it is not very clear how to make good use of SHM systems toward these goals. This paper takes the Tsing Ma suspension bridge in Hong Kong as an example and recapitulates the relevant works done by the author and his colleagues and students in the past 20 years to manifest how the SHM system installed in the bridge has been utilized since 1997. The SHM system installed in the bridge is briefly introduced first. How to use the SHM system for investigating highway loading, railway loading, wind characteristics, and temperature effects is then presented. Identification of time-varying natural frequencies and modal damping ratio of the bridge under strong winds using the data recorded by the SHM system is also demonstrated. Toward the performance assessment and damage detection of the bridge, SHM system-based computer simulation and damage assessment are targeted and some typical examples are given. The establishment of SHM system-based bridge rating system for bridge maintenance is also briefly introduced.

A generalized flexibility matrix-based model updating method for damage detection of plane truss and frame structures

Abstract: Nowadays, many non-destructive damage detection methods for determining the location and severity of damage in the field of health monitoring are considered in order to reduce the cost of maintenance and improve safety and reliability of structure. In this paper, damage specification is obtained by sensitivity-based updating approach. By applying changes on sensitivity matrix and using measured flexibility data, it is concluded that the results of proposed method are more accurate and efficient than the old modal flexibility methods. The mass modeling error and measurement error of flexibility and natural frequency are calculated in order to ensure the accuracy and robustness of proposed method for 2-D finite element truss and frame model. Close index, measuring the performance of the method, and the coefficient of variation, which represents the distribution of response, are used. Compared with Wang method, the proposed method is capable of accurately localizing and quantifying damage in all scenarios.

Automated, strain-based, output-only bridge damage detection

Abstract: This paper presents a framework for automated damage detection using a continuous stream of structural health monitoring data. The study utilized measured strains from an optimized sensor set deployed on a double track, steel, railway, truss bridge. Stringer–floor beam connection deterioration, a common deficiency, was the focus of this study; however, the proposed methodology could be used to assess the condition of a wide range of structural elements and details. The framework utilized Proper Orthogonal Modes (POMs) as damage features and Artificial Neural Networks (ANNs) as an automated approach to infer damage location and intensity from the POMs. POM variations, which are traditionally input (load) dependent, were ultimately utilized as damage indicators. Input variability necessitated implementing ANNs to help decouple POM changes due to load variations from those caused by deficiencies, changes that would render the proposed framework input independent, a significant advancement. To develop an automated and efficient output-only damage detection framework, data cleansing and preparation were conducted prior to ANN training. Damage “scenarios” were artificially introduced into select output (strain) datasets recorded while monitoring train passes across the selected bridge. This information, in turn, was used to train ANNs using MATLABs Neural Net Toolbox. Trained ANNs were tested against monitored loading events and artificial damage scenarios. Applicability of the proposed, output-only framework was investigated via studies of the bridge under operational conditions. To account for the effects of potential deficiencies at the stringer–floor beam connections, measured signal amplitudes were artificially decreased at select locations. It was concluded that the proposed framework could successfully detect artificial deficiencies imposed on measured signals under operational conditions.

Study on the dynamic properties of a suspended bridge using monocular digital photography to monitor the bridge dynamic deformation

Abstract: This study makes use of monocular digital photography, based on the IM-STBP (image matching-space time baseline parallax) method, to monitor bridge dynamic deformation to study bridge dynamic properties. A bridge was first photographed when traffic light was red (i.e., when the bridge was not influenced by dynamic vehicle load) to generate the zero image (a.k.a. the reference image), and then photographed every 3 s when the traffic light was green (i.e., when the bridge was influenced by dynamic vehicle load) to produce image sequences as successive images. Relative deformation values of deformation points were obtained based on the IM-STBP method. The results show that the measurement accuracy of the IM-STBP method reaches a sub-pixel level (0.445, 0.470 and 0.705 pixels in the X, Z and comprehensive directions, respectively) and that maximal deflections of the bridge monitored by cameras 1 and 3 (37.22 and 47.40 mm, respectively) are within bridge deflection tolerance (75 mm). The monocular digital photography presented in this study has proved effective in monitoring bridge dynamic deformation even when the photographing direction is not perpendicular to the bridge plane and useful in assessing the situation of a bridge by monitoring the instantaneous dynamic global deformation of a bridge when the traffic light is green. Deformation curves in real time can also provide warning of any possible danger on the bridge. These global deformation curves of a bridge play a key role in studying the dynamic properties of a bridge influenced by dynamic vehicle load.

Automated long-term dynamic monitoring using hierarchical clustering and adaptive modal tracking: validation and applications

Abstract: Historical buildings demand constant surveying because anthropogenic (e.g., use, pollution or traffic vibration) and natural or environmental hazards (e.g., environmental changes or earthquakes) can endanger their existence and safety. Particularly, in the Andean region of South America, earthen historical constructions require special attention and investigation due to the high seismic hazard of the area next to the Pacific coast. Structural Health Monitoring (SHM) can provide useful, real-time information on the condition of these buildings. In SHM, the implementation of automatic tools for feature extraction of modal parameters is a crucial step. This paper proposes a methodology for the automatic identification of the structural modal parameters. An innovative and multi-stage approach for the automatic dynamic monitoring is presented. This approach uses the Data-Driven Stochastic Subspace Identification method complemented by hierarchical clustering for automatic detection of the modal parameters, as well as an adaptive modal tracking procedure for providing a clear visualization of long-term monitoring results. The proposed methodology is first validated in data acquired in an emblematic sixteenth century historical building: the monastery of Jeronimos in Portugal. After proving its efficiency, the algorithm is used to process almost 5000 events containing data acquired in the church of Andahuaylillas, a sixteenth century adobe building located in Cusco, Peru. The results in these cases demonstrate that accurate estimation of predominant modal parameters is possible in those complex structures even if relatively few sensors are installed.

Extending the life-span of cultural heritage structures

Abstract: Monuments and historic buildings represent our historic heritage, the witnesses of the history that have arrived up to our age. We have inherited them from the previous generations, and it is our duty to preserve and to transfer them to the future generations. Therefore, we must preserve our cultural heritage from the natural ageing and the natural catastrophes, such as earthquakes. This can be done by means of a continuous monitoring and periodic controls, using non-destructive techniques. The recent applications of structural health monitoring to cultural heritage structures are introduced in this paper. They present some interesting cases, which are examples of good practise for the future.

Thermal performance analysis of a long-span suspension bridge with long-term monitoring data

Abstract: Thermal performance analysis such as calculating thermal stress from monitoring data is important for structural safety evaluation. These temperature characteristics of long-span bridges are more complicated due to their temperature distribution, structural configuration and boundary conditions. In this study, the method of structural thermal performance analysis is proposed by processing and analyzing the long-term monitoring data and it is applied to study the thermal and mechanical behavior of a long-span suspension bridge under daily operating conditions. First, statistical analysis of strain data and temperature data is performed on the main girder. Second, thermal analysis and temperature-induced stress calculation are proposed, in which the different kinds of thermal loads including uniform temperature, linear/nonlinear temperature gradient and partial constraints in axial/rotation directions are considered. Other parameters such as restrained stiffness, deformation, etc., are derived. Third, the proposed method is verified and used in the temperature-induced stress calculation on the studied bridge.

Drive-by damage detection with a TSD and time-shifted curvature

Abstract: ‘Drive-by’ damage detection is the concept of using sensors on a passing vehicle to detect damage in a bridge. The newly developed traffic speed deflectometer (TSD) is a device used for pavement velocity/deflection measurements and is investigated here in numerical simulations as a means of bridge damage detection. A TSD vehicle model containing five displacement sensors is simulated crossing a simply supported finite element beam containing damage simulated as a loss in stiffness of one of the elements. Time-shifted curvature is derived from the displacements and is proposed as a novel damage indicator, which removes the influence of the road profile and all vehicle motions except for pitch. Results show that the time-shifted curvature can be reliably used as a damage indicator in the presence of noise and changes in transverse position of the vehicle on the bridge.

Detection of mortar defects in ballastless tracks of high-speed railway using transient elastic wave method

Abstract: In the multi-layered track structure, the defects of cement-emulsified asphalt (CA) mortar are hidden and difficult to detect. There is still no effective detection method yet. Thus, this paper discusses the feasibility of mortar defect detection by transient elastic wave method. First, a finite-element model (FEM) was created by the LS-DYNA for a section of the multi-layered structure of the ballastless tracks, and the features of elastic waves were investigated in ballastless tracks with and without defects. Then, three identification parameters were presented and the spectra of measuring points were analysed in detail. Moreover, the IE method was adopted to detect the defects in the entity models of ballastless tracks. It is shown that the internal defects of the mortar layer can be pinpointed by comparing the waveforms of various frequencies in the frequency domain, different peaks of resonance frequency, and diverse power density values.

Population-based structural identification for reserve-capacity assessment of existing bridges

Abstract: Transportation networks provide an essential contribution to addressing the needs of reliable and safe mobility in urban environments. The core of these networks is made up of infrastructure such as roads and bridges that often, have not been designed to meet current needs. Optimal management requires an accurate knowledge of how existing structures behave. This helps avoid unnecessary replacement and expensive interventions when cheaper and more sustainable alternatives are available. Structural-model updating takes advantage of measurements and more qualitative observations to identify suitable behaviour model classes and values for parameters that influence real behaviour. Error domain model falsification (EDMF) has been proposed as a robust population-based methodology to identify sets of models by comparing finite-element model predictions with measurements at sensor locations. This paper introduces a methodology, which is compatible with EDMF, to assess the reserve capacity of bridges for serviceability and ultimate limit states. A case study—the structural identification of a reinforced-concrete bridge in Singapore—illustrates the framework developed for the estimation of reserve capacity. Several analyses with increasing levels of model detail using design and updated values of relevant parameters are presented. Traffic-load specifications of design-stage codes (British Code—1978) and current codes (Eurocodes) are compared. Results show that typical conservative practices carried out during design and construction have led to an as-built reserve capacity of 60%. A large proportion of the as-built reserve capacity has been exploited to accommodate dramatically increased values of traffic-load specifications that are provided by current Singapore codes which have caused a reduction in reserve capacity to 20%. Such a reduction may be less significant in countries where code specifications have not changed as much. Finally, it is shown that advanced methods of analysis and assessment are more suitable than design-stage approaches to quantify the reserve capacity.

Monitoring-based analysis of the static and dynamic characteristic of wind actions for long-span cable-stayed bridge

Abstract: Wind action is one of the environmental actions which has substantial static and dynamic effects on the long-span bridges. The main objective of the paper is to reveal the static and dynamic characteristics of the regular wind and typhoon condition. A monitoring-based investigation has been carried out to analyze the characteristics of the wind actions. The static characteristics of regular wind and typhoon condition are investigated by analyzing the average wind speed. Moreover, the dynamic characteristics of the two conditions of wind actions are studied by analyzing the parameters of turbulence intensity and gust factors. The correlation analysis is performed between the lateral wind speed and the lateral girder displacement to reveal the static effects of the wind actions on the bridge structures. It is concluded that static and dynamic characteristics of regular wind and typhoon conditions are quite different, and the dynamic effects of wind actions obtained based on monitoring data need to be further studied.

Seismic performance assessment of isolated bridges for different limit states

Abstract: This study aims to evaluate the seismic performances of bridges isolated by the friction pendulum system (FPS) bearings considering the seismic hazard of Sant’Angelo dei Lombardi site (Italy), to provide useful and preliminary recommendations in terms of health assessment for design or retrofit of new or existing bridges, respectively. Single- and two-degree-of-freedom models are considered to describe the isolated bridge behavior taking into account an infinitely rigid deck and the isolated bridge behavior having an infinitely rigid deck with the elastic pier, respectively. In both models, a velocity-dependent rule for the FPS isolators is assumed. Seismic excitations are properly modeled as non-stationary stochastic processes having different intensities corresponding to different limit states and with frequency contents related to the medium soil condition, representative of the soil type in Sant’Angelo dei Lombardi site (Italy). The statistics of deck and pier responses of the isolated bridge are evaluated for different system parameters such as mass ratio, isolation period, pier period and friction coefficient of the FPS considering both Life Safety and Collapse Prevention limit states according to Italian seismic codes. The results, deriving mainly from the two-degree-of-freedom (2dof) model analyses, show that particular values of the friction coefficient allow to minimize the response of the pier depending on the different system properties and the different limit states. In particular, the optimum friction coefficient of the FPS ranges from 0.01 to 0.04 and from 0.01 to 0.05 for Life Safety and for Collapse Prevention limit state, respectively, depending on the structural properties.

Crack detection in prestressed concrete structures by measuring their natural frequencies

Abstract: When inspecting the health of a civil structure, it is important to have efficient techniques to detect the possible presence of structural damage. This work deals with the detection of damage in prestressed concrete structures, which are widely used in road bridges and long span slabs, among others. Concrete structures can be affected by different pathologies, with the transverse cracks beingone of the most dangerous damages, since they involve a localized reduction of the flexural rigidity of the structure. Such cracks change both the static and dynamic behavior of the structure. In this paper, an inverse method of damage detection is applied on two experimental beams built in the laboratory, from the measurement of the first three natural frequencies of vibration. An algorithm for solving the system of equations has been developed by the authors. Explicit equations were obtained to calculate both the crack position and its depth. The predicted damages by the algorithm have been in good agreement with the real damages of the experimental models. An important aspect of this methodology for crack detection is the simplicity of its experimental implementation.

MCrack-Dam: the scale-up of a method to assess cracks on concrete dams by image processing. The case study of Itaipu Dam, at the Brazil–Paraguay border

Abstract: Inspection and maintenance of civil infrastructures require structural assessment, usually performed based on the monitoring of critical sections. For concrete structures, the identification and characterization of the crack patterns is an important task to a rigorous evaluation of the structural performance. In the case of concrete dams, the timely detection and correction of structural problems can avoid major accidents. Despite the significance of crack monitoring and the recent innovations using image processing, the inspection of dams is usually simply based on visual inspections. This results in sketching crack patterns and also includes hand-held measurements, using crack width rulers and measuring tape. Thus, the development of automatic methods based on image processing to assess cracks in concrete dams has significant advantages. In this scope, most of the methods were applied in the laboratorial environment, and a gap to scale-up them to onsite assessment is clearly identified. In this paper, a method named MCrack-Dam, resulting from the scale-up of the method MCrack, previously developed and validated in controlled laboratorial conditions, is presented. The method is based on image processing and designed to automatically monitoring cracks in concrete dams. The MCrack-Dam relies on a predefined systematic acquisition of images: pre-processing those images for ortho-rectification; processing of the latter to identify and model cracks; and post-processing procedure to characterize the crack key parameters. The method was applied to a predefined region of the Itaipu Dam, at Brazil–Paraguay border. The results validate the ability of MCrack-Dam for performing a detailed characterization of cracks in concrete dams, not comparable to the traditional methods currently used. In addition, MCrack-Dam successfully works on surfaces with distinct features (‘noise’ for crack detection) such as drippings, sketched drawings, and smooth and rough textures, unlike other image processing methods when applied on ‘noise’ surfaces. Finally, the most relevant conclusions, and guidelines for the optimization of the exhaustive survey of the entire surface of the dam, are presented.

System identification and model updating of highway bridges using ambient vibration tests

Abstract: Vibration-based structural health monitoring (SHM) has received significant attention in the past. Due to the existence of some defect of implementation, the measured response of a structure and the response from its finite element model may not match. There are a number of methods available for updating the Finite Element (FE) model of a structure such that the response calculated from the model agrees with field measurements, and identifying the system parameters like stiffness and mass based on dynamic response of the structure. These methods are categorized into physics based and data driven. In this study, the FE models of a 16-span Pre-Stress Concrete Box (PSCB) girder bridge with the total length of 780 m, a 3-span Void Slab Bridge with the total length is of 65 m, and a Steel Box (STB) with 380 m length and 12 m width, with 8 spans of equal length of 47.5 m bridge are constructed and updated using the measured vibration data. The objective of this study is to identify the system properties of the bridges using physics-based and data-driven methods and update the corresponding models using the data from ambient vibration tests and determine the efficacy of each method. A well-known and effective physics-based method, the matrix update method, is used for correlating the models by solving the relevant inverse problem through constrained optimization. In data-driven methods, the Neural Network and Genetic Algorithms are applied to find the correlations between the structural frequencies and changes in the sectional properties of the bridge segments. The outputs of these models are compared with certain target frequencies based on the measured data in order to adjust the section properties of the bridge elements. It is found that while the physics-based method has a better performance than the data-driven model in identifying the modal properties, the physics-based model is difficult to implement and there is a need for developing a hybrid method to achieve a better result.

Estimation of scour depth at bridges with complex pier foundations using support vector regression integrated with feature selection

Abstract: This study aims at establishing machine learning models based on the support vector regression (SVR) for estimating local scour around complex piers under steady clear-water condition. A data set consisting of scour depth measurement cases has been collected to construct the prediction models. The data set includes eight influencing factors that consider aspects of pier geometry, flow property, and river bed material. Moreover, to enhance the performance of the SVR model, filter and wrapper feature selection strategies are used. The research finding is that all feature selection approaches can help to improve the prediction accuracy compared with the SVR model that uses all available features. Notably, the feature selection method based on the variable neighborhood search (VNS) algorithm achieves the best performance (MAPE = 21.65%, R2 = 0.85). Accordingly, the prediction model produced by SVR and VNS can be useful for assisting decision makers in the task of structural health monitoring as well as the design phase of bridges.

Composite panel structural health monitoring and failure analysis under compression using acoustic emission

Abstract: This paper documents an application of the acoustic emission (AE) method for structural health monitoring (SHM) of an integrally stiffened composite panel. The panel consists of a skin and two T-stringers and represents a typical part of the wing or fuselage structure. Similar design is used in civil structure parts. Quasi-static loading under compression was carried out to determine the initiation of the buckling modes. Two pieces of integral panels were tested up to failure. Both panels were monitored using 9 AE sensors in the same configuration throughout the test. The final stage of the test was recorded with a high-speed camera to obtain a detailed view of failure development. The velocity of the propagated AE elastic waves was determined experimentally before the test based on the best match of the computed and real positions of the Hsu–Nielsen sources. The determined velocity was subsequently used for AE source localization during the compression test. Different failure mechanisms were directly linked to different sources of AE using cluster analysis. Visualization of the AE location clusters was performed via the Kernel density estimation. High-speed camera images confirmed that the location of failure corresponds with the localization of a specific cluster of AE events. The AE method demonstrated the detection capability of the critical spot at 87% of the panel strength in compression. In conclusion, AE is suitable as an SHM method for damage monitoring of aerospace composite structures as well as for applications in civil structures.