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Structural health monitoring (SHM) is widely used to monitor and assess the condition and performance of engineering structures such as, buildings, bridges, dams, and tunnels. Owing to sensor defects, data acquisition errors, and environmental interference, abnormal data are often collected and stored in monitoring systems. The abnormal data in this study are essentially different from so-called “abnormal state data,” which result from structural physical damage or performance degradation. Abnormal data are totally related to the external interference rather than changes in the inherent structural features. However, abnormal data can significantly affect the performance assessment of engineering structures. It is imperative to detect and remove abnormal data from measurements to avoid misjudging structural performance in SHM. This paper summarizes abnormal data detection in the SHM field and discusses relevant challenges. Moreover, background knowledge regarding abnormal data detection is introduced. Abnormal data detection methods are then classified into statistical probability methods, predictive models, and computer vision methods. The advantages, disadvantages, and scope of each method are investigated. An example of detecting abnormal monitoring data for a cable-stayed bridge is introduced. In addition, the issues of existing studies are summarized, and future study interests are discussed.

Inspired by state-of-the-art material science, computer techniques, artificial intelligence, and automatic control, new-generation transportation infrastructures are becoming digitalized and intelligent. Many major developed countries around the globe are actively promoting the application of innovative intelligence-based technologies in transportation infrastructures in accordance with local conditions. This review begins with a brief discussion on the basic definition, scientific foundation, and development process for the intellectualization of transportation infrastructures. Then, following the whole life-cycle chain of design, construction, operational maintenance, and elimination, the current research status and major challenges presented by intellectualization technologies are systematically investigated. Subsequently, recent achievements in intellectual technologies are comprehensively presented by selecting the Beijing–Zhangjiakou High-Speed Railway—the world’s first railway built based on the concept of intelligent construction—as an example. Finally, a discussion on the future development of the intellectualization of transportation infrastructures is provided from the three dimensions of standard systems, theoretical methods, and talent training.

For a practical structural health monitoring (SHM) system, the traditional single objective methods for optimal sensor placement (OSP) cannot always obtain the optimal result of sensor deployment without sacrificing other targets, which creates obstacles to the efficient use of the sensors. This study mainly focuses on establishing a bi-objective optimization method to select the sensor placement positions. The practical significance of several single-objective criteria for OSP is firstly discussed, based on which a novel bi-objective optimization method is proposed based on the Pareto optimization process, and the corresponding objective functions are established. Furthermore, the non-dominated sorting genetic algorithm is introduced to obtain a series of the Pareto optimal solutions, from which the final solution can be determined based on a new defined membership degree index. Finally, a numerical example of a plane truss is applied to illustrate the proposed method. The Pareto optimization-based bi-objective OSP framework presented in this study could be well suited for solving the problem of multi-objective OSP, which can effectively improve the efficiency of the limited sensors in SHM system.

Wind action is one of the environmental actions that has significant static and dynamic effects on long-span bridges. The lateral wind speed is the main factor affecting the lateral displacement of the main girder of the bridge. The main objective of the paper is to use the improved multi-rate fusion method to correct the monitoring data so that accurate correlation modeling of wind speed-displacement can be achieved. Two Kalman gain coefficients are introduced to improve the traditional multi-rate fusion method. The fusion method is verified by the results of simulated data analysis in time domain and frequency domain. Then, the improved multi-rate fusion method is used to fuse the monitoring lateral displacement and acceleration data of a bridge under strong wind action. The corrected lateral wind speed and displacement data is further applied to establish the correlation model through the linear regression. The improved multi-rate fusion method can overcome the inaccuracy of the high frequency stage of a Global Positioning System (GPS) sensor and the low frequency stage of acceleration sensor. The correlation coefficient of wind speed-displacement after fusion increases and the confidence interval width of regression model decreases, which indicates that the accuracy of the correlation model between wind speed and displacement is improved.

An experimental study of plain concrete specimens of water-cement ratio 0.55, subjected to 0, 15, 25, 40, 50 and 75 cycles of freeze-thaw was completed. The dynamic modulus of elasticity (DME), weight loss, compressive strength, tensile strength, flexural strength, cleavage strength and stress-strain relationships of plain concrete specimens suffering from freeze-thaw cycles were measured. The experimental results showed that the strength decreased as the freeze-thaw cycles were repeated. A concise mathematic formula between DME, weight loss, mechanical properties and number of freeze-thaw cycles was also established. The influences of freeze-thaw cycles on the DME, weight loss and mechanical properties were analyzed. The experimental results serve as a reference for the maintenance, design and life prediction of dams, hydraulic structures, offshore structures, concrete roads and bridges in cold regions.

In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed by several processing parameters, including the type of wavelet, decomposition level, thresholding method, and threshold selection rules. To overcome the disadvantages of the traditional hard- and soft-thresholding methods, an improved thresholding technique called the sigmoid function-based thresholding scheme is presented. The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment. The performance of the proposed method is evaluated by computing the signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) after denoising. Results reveal that the proposed method offers superior performance than the traditional methods no matter whether the signals have heavy or light noises embedded.

Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems.

Nondestructive testing technology is essential in the quality inspection of repair, alteration, and renovation of the existing engineering, especially for concrete structure in severe environment. The objective of this work is to deal with the behavior of ultrasonic velocity and mechanical properties of plain concrete and air-entrained concrete subjected to freeze-thaw cycles (F-T-C). The ultrasonic velocity and mechanical properties (tensile strength, compressive strength, cubic compressive strength, and splitting strength) of C30 air-entrained concrete and plain concrete with different water-cement ratio (water-cement ratio was 0.55, 0.45, and 0.50, resp.) after F-T cycles were measured. The influences of F-T cycles on ultrasonic velocity and mechanical properties of C30 air-entrained concrete and plain concrete were analyzed. And the relationship between mechanical properties and ultrasonic velocity was established. The experimental results can be useful for the design of new concrete structure, maintenance and life prediction of existing concrete structure such as offshore platform and concrete dock wall.

Thermal load is an important factor that must be taken into account during the procedure of bridge design and structural condition evaluation especially for those statically indeterminate bridges and cable-supported bridges. This paper presents an overview of current research and development activities in the field of thermal load in bridge, in which emphasis is placed on the thermal load models established by numerical analysis and field measurement. The theoretical formulations and boundary conditions of heat transfer in bridge are firstly outlined. And then, the states of the art of numerical solutions for temperature distribution in bridge including finite difference method and finite element method are reviewed in detail. Following that, the progress on thermal load in three types of representative bridges that are concrete bridge, steel-concrete composite bridge, and steel bridge based on field measurement data is discussed extensively. Finally, some existing problems and promising research efforts about thermal load in bridge are remarked.

Wireless sensor networks (WSNs), which are a promising technology for the implementation of long-span bridge health monitoring, have gained increasing attention from both the research community and actual users. The limited energy of sensor emphasizes the importance of performance optimization of WSNs. In this paper, a methodology and strategy of node arrangement are developed to improve the performance of WSN for long-span bridge health monitoring, including balancing energy consumption, increasing data capacity, and reducing deployment cost. A composite WSN organized by sensor nodes and relay nodes is introduced for structural health monitoring. The energy consumption model of the composite WSN is firstly presented. And then, the data acquisition efficiency (DAE) defined as data capacity per unit deployment cost is suggested to evaluate the performance of WSN. Subsequently, the node arrangement is divided into two phases of sensor node arrangement and relay node arrangement. An improved general genetic algorithm is proposed to configure sensor nodes, and a nonuniform node arrangement method is developed to distribute relay nodes. Based on the DAE, the theoretical formulae of nonuniform node arrangement are deduced. The process of two-phase node arrangement is also provided for practical bridge engineers.

This paper presents a nonuniform node configuration of wireless sensor networks (WSNs) for long-span bridge health monitoring. The methodology and strategy of two-phase node arrangement for nonuniform WSN configuration are firstly presented, and then numerical examples are carried out by a long-span suspension bridge. Three cases, which are four sensor nodes distributed on one side of the girder, ten sensor nodes distributed on one side of the girder, and eight sensor nodes distributed averagely on two sides of the girder, are employed. In case I and case II, three schemes that are the nonuniform node configuration arranged by the two-phase node arrangement method, the uniform nodes configuration, and the independent sensor nodes configuration are used for comparison. And in case III, two schemes that are nonuniform nodes configuration and the independent sensor nodes configuration are adopted. The results indicate that the nonuniform node configuration can balance energy consumption, eliminate “energy hole,” and maximize network performance effectively, which shows the most outstanding performance when compared with other conventional node configurations. So, the efficiency of the two-phase node arrangement method is validated.

For use in fire resistance calculations, the relevant thermal properties of high-performance concrete (HPC) with fly ash were determined through an experimental study. These properties included compressive strength, cubic compressive strength, cleavage strength, flexural strength, and the ultrasonic velocity at various temperatures (20, 100, 200, 300, 400 and 500∘C) for high-performance concrete. The effect of temperature on compressive strength, cubic compressive strength, cleavage strength, flexural strength, and the ultrasonic velocity of the high-performance concrete with fly ash was discussed according to the experimental results. The change of surface characteristics with the temperature was observed. It can serve as a reference for the maintenance, design, and the life prediction of high-performance concrete engineering, such as high-rise building, subjected to elevated temperatures.

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods’ effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

One of the most damaging actions affecting concrete is the abrupt temperature change (freeze-thaw cycles). The types of deterioration of concrete structures by cyclic freeze-thaw can be largely classified into surface scaling (characterized by the weight loss) and internal crack growth (characterized by the loss of dynamic modulus of elasticity). The present study explored the durability of concrete made with air-entraining agent subjected to 0, 100, 200, 300, and 400 cycles of freeze-thaw. The experimental study of C20, C25, C30, C40, and C50 air-entrained concrete specimens was completed according to “the test method of long-term and durability on ordinary concrete” GB/T 50082-2009. The dynamic modulus of elasticity and weight loss of specimens were measured after different cycles of freeze-thaw. The influence of freeze-thaw cycles on the relative dynamic modulus of elasticity and weight loss was analyzed. The findings showed that the dynamic modulus of elasticity and weight decreased as the freeze-thaw cycles were repeated. They revealed that the C30, C40, and C50 air-entrained concrete was still durable after 300 cycles of freeze-thaw according to the experimental results.

It is important to clarify the variational rules between dynamic characteristics and gust response factors (GRFs) of an ultra high-voltage (UHV) transmission tower for the structural design. In this paper, the synchronous multisensors on-site monitoring has been carried out under field wind conditions, which includes field fluctuating wind velocity, acceleration responses, and base bending strains on parts of the just-built transmission tower. The dynamic characteristics of tested transmission tower were investigated by a modal identification method (MIM) and validated those results with a finite-element method (FEM). Similarly, the GRFs based on the top displacement or base dynamic bending stains are calculated and compared by means of a measurement data statistical method and some different quasistatic methods, respectively. The results have shown that the dynamic characteristics obtained from the measurement data analysis with the MIM agree with those from the FEM, which confirms that the FEM and the MIM for dynamic characteristics are consistent and correct. In turn, the GRFs form the measurement displacement analyses have some differences from those calculated with the quasistatic method, and it is necessary to further identify and verify their causations.

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale civil infrastructures. This paper outlines an overview of current research and development in the field of OSP problems in a perspective of both researchers and engineers. The paper begins with a definition of the model of sensor placement and provides the basic issues covering relevant methodologies. The primary evaluation criteria and main sensor placement methods are then discussed in details. Following that, the linkage between several influential sensor placement methods is described. Finally, existing problems and promising research efforts in the OSP problem of civil SHM are discussed.

An experimental study of C20, C25, C30, C40, and C50 big mobility concrete cubes that came from laboratory and construction site was completed. Nondestructive testing (NDT) was carried out using impact rebound hammer (IRH) techniques to establish a correlation between the compressive strengths and the rebound number. The local curve for measuring strength of the regression method is set up and its superiority is proved. The rebound method presented is simple, quick, and reliable and covers wide ranges of concrete strengths. The rebound method can be easily applied to concrete specimens as well as existing concrete structures. The final results were compared with previous ones from the literature and also with actual results obtained from samples extracted from existing structures.