•A review on motion magnification-based vibration measurement of structures is presented.•Basic principles of the motion magnification methods commonly used are reviewed.•Major challenges and the ...research works to address these challenges are summarized.•Representative applications of motion magnification techniques are reviewed.•Research prospects for motion magnification-based vibration measurement are introduced.
Vibration measurement plays an important role in the inspection and monitoring of civil structures. In recent years, the computer vision (CV)-based method has gained significant popularity in the field of vibration measurement for civil structures due to its inherent advantages, such as non-contact, low cost, long-distance measurement, and ease of implementation. However, those traditional CV-based methods are only suitable for situations with large vibration amplitude. The vibration of some civil structures is usually small especially under environmental excitation, which poses challenges for the traditional CV-based methods. The motion magnification (MM) technique has emerged as an effective solution for small-amplitude vibration measurement. Therefore, this study comprehensively reviews the MM technique for video-based vibration measurement of civil structures. First, the principles and characteristics of some representative MM techniques are introduced. Then, three major challenges encountered in vibration measurement of civil structures using MM techniques are summarized, and the research work to address these challenges is reviewed. Finally, the applications of MM techniques on various civil structures including bridges, cables, buildings, wind turbines and dams are summarized. This review can provide guidance to researchers and engineers in selecting suitable MM methods for vibration measurement of civil structures.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•A prediction model for fatigue properties of welded structures is proposed.•The model is based on SPDTRS-CS-BPNN hybrid algorithm.•A multi-scale fatigue database for EH36 steel is created and the ...model is applied.•Comparisons with experimental results establish the reliability of the model.•The model can guide the fatigue design of welded structures in industries.
This paper proposes a prediction model of welded joint fatigue properties based on single-parameter decision-theoretic rough set (SPDTRS)-cuckoo search (CS)-artificial neural network (ANN) hybrid algorithm. To establish the fatigue performance database of EH36 steel, the preprocessing and data cleaning are carried out by analytic hierarchy process (AHP) and box-plot method to obtain reliable fatigue properties prediction. Therein, the SPDTRS theory is used to analyze the weight of fatigue properties influencing factors, the CS algorithm is used to avoid the over-fitting and local optimization of ANN. During process, the influencing factors are regarded as input and the material related parameters C and m are conducted as output to realize the fatigue properties prediction, which improves the accuracy and stability of the present prediction method. According to the comparisons between the experimental and predicted results, it is found that the predicted S-N curves are within ± 1.1 error band of the experimental results, the average error of fatigue life is less than 10%, and can be within ± 1.2 error band. As a result, the fatigue properties prediction model reasonably shows the fatigue properties of welded structures, and provides a certain reference for fatigue design of welded structures.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Conventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template ...matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into a software package for real-time displacement extraction from video images. By simply adjusting the upsampling factor, better subpixel resolution can be easily achieved to improve the measurement accuracy. The performance of the vision sensor is first evaluated through a laboratory shaking table test of a frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Satisfactory agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. Then field tests are carried out on a railway bridge and a pedestrian bridge, through which the accuracy of the vision sensor in both time and frequency domains is further confirmed in realistic field environments. Significant advantages of the noncontact vision sensor include its low cost, ease of operation, and flexibility to extract structural displacement at any point from a single measurement.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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•Discrete and distributed fibre optic sensors for real-time strain data streams.•Deep learning algorithms for damage prognosis and decision making.•Reported over 97% prediction ...accuracy in acquisition & analysis of large data volumes.•Intelligent safety systems for bridges, buildings, and pipelines.
Structural health monitoring (SHM) systems in civil engineering structures have been a growing focus of research and practice. Over the last few decades, optical fibre sensor (OFS) technology has advanced rapidly, and various types of OFS technologies have found practical uses in civil engineering. Due to recent advances in optical sensors and data-driven solutions, the SHM systems are gaining prominence. Because of its superior ability to detect damage and flaws in civil engineering structures, deep learning (DL) gradually gained substantial attention among researchers in recent years. The main goal of this paper is to review the most recent publications in SHM related to bridges, buildings, and pipelines using emerging OFS and DL-based applications, and to provide readers with an overall knowledge and understanding of various SHM applications. Finally, current research trends and future research needs have been identified.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
At the time of designing structures up to date, the density and magnitude of the load have increased, and the requirements for regulation have also become more stringent. To ensure the essential ...requirements, especially the mechanical resistance and stability, the numerical modelling of the structure is carried out according to the current regulations. Due to various assumptions, idealization, discretization, and parameterizations that are introduced numerical modelling, obtained numerical model may not always reflect the actual structural behavior. It is known that these structures have a hidden resistance that can be determined by combining experimental investigations (static or/and dynamic tests) and finite element model updating methods to minimize the differences between the actual and predicted structural behavior. This paper provides a review of the FEMU process and methods used and summarizes the FEMU approach to help future engineers to select the appropriate method for solving some discussed issues. First, the main terms important for understanding FEMU are introduced. The whole process of model updating is described step by step: selection of updating parameters (design variables), definition of the model updating problem, its solution using different FEMU methods. An overview of the following methods is given: sensitivity-based, maximum likelihood, non-probabilistic, probabilistic, response surface and regularization methods. Each of the method is presented with the corresponding mathematical background, implementation steps, and examples of studies from the literature.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Old mild steels have a strong correlation between the parameters of the Paris-law.•The stress ratio influences the Paris-exponent in historical steels.•Considering the stress ratio has an impact of ...the fatigue assessment of structures.
At the beginning of the 20th century, a large number of steel structures were built in Europe. Many of these buildings—especially railway bridges—are still in use. These structures are mainly composed of rimmed steel. In addition to the stress–life concept, fracture mechanics is often used to assess the safety of these structures in terms of fatigue failure. Based on crack propagation calculations, it is possible to determine inspection intervals and, thus, ensure safe operation. For these calculations, suitable parameters of the Paris law, along with threshold values, are needed. The aim of this study is to experimentally determine a wide range of fracture mechanics parameters for old mild steel with reference to the stress ratio R. The experimental results were compared with values from the literature. Furthermore, the experimental results were fitted to several models considering the stress ratio R during crack growth. The investigated models were compared on the basis of the results for simulated crack growth calculations. The models are assessed according to how closely they represent the experimental results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Despite the rapid advancement of technology and the increasing complexity of systems, conventional accident analysis techniques developed many years ago are still used in numerous sectors. On the ...other hand, these approaches are limited in detecting all underlying causes of accidents in complex socio-technical systems. In recent years, system theory-based novel accident analysis techniques have been proposed to address this issue. Systems-Theoretic Accident Model and Processes (STAMP) is one of these innovative analytic techniques with a strong detection capability. The method has the ability for analyzing human, organization, hardware, software, external factor components, and their interactions in a dynamic structure. However, despite the method's strong analysis capacity, it is a shortcoming that STAMP is a qualitative method. This study aims to present a hybrid quantitative methodology for complex system accidents based on a system engineering perspective to fill this gap. In this context, a real catastrophic marine diesel engine incident was analyzed to prove the applicability and effectiveness of the methodology. According to the analysis results, the main causes of the case incident were systematically determined as 80% human factor, 13% hardware & software factor, and 7% external factor.
•A modified methodology for complex process accident analysis based on a system engineering perspective is presented.•The proposed methodology is based on STAMP and rule-based fuzzy FMEA approaches.•A real catastrophic engine failure is chosen to show the implementation of the intended methodology.•The main reasons of the M/V Guroni Incident are due to 80% human, 13% hardware & software, and 7% external factors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story ...structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthquakes. Identifying and retrofitting buildings with such irregularities—generally termed as soft-story buildings—is, therefore, vital in earthquake preparedness and loss mitigation efforts. Soft-story building identification through conventional means is a labor-intensive and time-consuming process. In this study, an automated procedure was devised based on deep learning techniques for identifying soft-story buildings from street-view images at a regional scale. A database containing a large number of building images and a semi-automated image labeling approach that effectively annotates new database entries was developed for developing the deep learning model. Extensive computational experiments were carried out to examine the effectiveness of the proposed procedure, and to gain insights into automated soft-story building identification.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•Finite element model updating (FEMU) problem is formulated and further implemented as a game theory problem.•Three different game models (non-cooperative, cooperative and evolutionary) have been ...considered to cope with FEMU problem.•The performance (accuracy and simulation time) of the different game models has been compared when they are implemented to perform the FEMU of a laboratory footbridge.•Direct determination of the optimal solution for the FEMU problem reducing the simulation time (it is not necessary either to compute the Pareto front or to solve the subsequent decision-making problem) without compromising the accuracy of the solution.
Finite element modelling is performed to numerically predict the behaviour of civil engineering structures. Due to the different assumptions adopted during the modelling phase, this initial model does not always reflect adequately the actual structural behaviour. In this context, the results of experimental structural dynamic properties can be used to improve initial numerical model via the implementation of the so-called finite element model updating method. After this process, the updated model better reflects the actual structural behaviour. Due to its simplicity, for practical engineering applications, the updating process is usually performed considering the maximum likelihood method. According to this approach, the updating problem may be formulated as the combination of two sub-problems: (i) a bi-objective optimization sub-problem; and (ii) a decision-making sub-problem. The bi-objective function is usually defined in terms of the residuals between the experimental and numerical modal properties. As optimization method, nature-inspired computational algorithms have been usually considered due to their high efficiency to cope with non-linear optimization problems. Despite this extensive use, this method presents two main limitations: (i) the high simulation time required to compute the Pareto optimal front; and (ii) the necessity of solving a subsequent decision making problem (the selection of the best solution among the different elements of the Pareto front). In order to overcome these limitations, in this paper game theory has been adopted as computational tool to improve the performance of the updating process. For this purpose, the updating problem has been re-formulated as a game theory problem considering three different game models: (i) non-cooperative; (ii) cooperative; and (iii) evolutionary. Finally, the performance of proposal has been assessed when it is implemented for the model updating of a laboratory footbridge. As result of this study, game theory has been shown up as efficient tool to improve the performance of the updating process under the maximum likelihood method since it allows a direct estimation of the solution reducing the simulation time without compromising the accuracy of the result.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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