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Modal identification is based on modal superposition theory. For structures with proportional damping, the structural responses are recognized as real modal shapes multiplied by real modal...

This paper presents a comprehensive review of moving force identification on simply supported bridges. When a vehicle moves on a bridge deck, there is a dynamic interaction force between the vehicle and the bridge deck. This dynamic interaction force is crucial for the design and condition assessment of bridges. However, this interaction force cannot be directly measured. Therefore, the indirect measurement method based on the bridge response, namely, the moving force identification method, has become an important issue in evaluating bridge condition. This paper provides a comprehensive review of current research and development activities in bridge moving force identification. First, the development and application of moving force identification are introduced. Next, the theoretical methods of bridge moving force identification are presented. Then, the robustness and accuracy of moving time-varying force identification methods are numerically simulated and compared. Finally, the characteristics of these methods are summarized, which provides a basis for selecting the suitable identification methods under different conditions and prospects of the further development of moving force identification.

Hinge joint damage is the main defect affecting the safety of assembled hollow slab bridges. The timely discovery of hinge joint damage is significant for guaranteeing the structural safety...

Detection of potential damage is of great significance for aging railway bridges. In this paper, a damage location method for beam railway bridges based on the rotation response to operatio...

Operational modal identification is indispensable in bridge health monitoring because it estimates modal parameters only from the multiple-channel responses of bridges under ambient excitat...

Modal parameters are widely recognized as valuable indicators for evaluating the performance of railway bridges in structural health monitoring. A major challenge in the mode-based performa...

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.

Structural modal identification for providing dynamic properties, including frequencies, damping ratios, and mode shapes, plays an important role in structural health monitoring and safety ...

Eliminating the bridge modal variability induced by temperature interference is crucial in vibration-based damage detection. In this paper, a novel localized thermal–frequency correlation ...

With an increase in bridge service time, damage will inevitably occur. Accurately identifying damage is of great significance to the operation and maintenance of a bridge. To realize a freq...

For high-speed railway bridges in operation, it is necessary to reveal the coupling dynamic performance of train–bridge systems in order to avoid extreme vibrations, which are not conducive to bridge safety. With the opening of long-span heavy-haul and complex-type bridges to traffic, the train–bridge interaction can hardly be explained by a mature and unified theory. Notably, field testing and monitoring analysis have become popular in tracking the dynamic performance of train–bridge systems. The vibration of railway bridges depends on the train-track configuration and the inherent characteristics of bridges. The inherent characteristics of bridges, which are reflected by the modal parameters, are extracted via operational modal analysis in this paper. In addition, the modal characteristics of bridges while the train is passing through are also investigated to explain the coupling dynamic effect with the help of the train configuration. Considering that the measured vibration responses are seriously polluted by non-white noise or excitation, the variational mode decomposition (VMD) technique is developed to extract the state-driven vibrations for modal analysis. Since VMD is a univariate technique that hardly ensures that the weak component can be obtained from each measuring channel, the multi-channel variational mode decomposition (MVDM) technique is extended in this paper. The field monitoring data of a high-speed railway bridge are taken for modal identification and vibration analysis. The results show that the weak structural modes can be tracked, even though the forced vibrations due to the passage of regularly spaced axles are dominant. In addition, the dynamic effects in train-induced vertical vibrations of bridges are closely related to the train speed, heavy axle loads and the span length.

Bearing displacement is a necessary monitoring index for a long-span bridge because abnormal bearing displacements could result from structural deterioration or damage. Therefore, an early...

The influence line is an important static property in bridges. The shape and magnitude of the girder bridge influence line contain stiffness information for the bridge supports and beam. Th...

Tie-down cables are critical components of uplift-restraint bearings in bridges. Damage of a tie-down cable substantially affects the safety of a bridge and driving conditions. In this stud...

Corrosion induced material loss in metallic structures is a widespread and urgent problem across multiple industries. In this paper, a novel corrosion monitoring method is proposed based on the lead zirconate titanate (PZT) based smart corrosion coupon (SCC) using electromechanical impedance (EMI). The basic idea of the corrosion monitoring method is that the corrosion induced thickness loss of the SCC will leads to the variation in the EMI signatures. The SCC was fabricated by bonding a PZT patch onto a corrosion coupon. The EMI signatures of the SCC under different corrosion amount were acquired and analyzed. Results showed that the peaks in the conductance signatures present a leftward shift and the peak frequencies decrease linearly with increase of the corrosion amount. To obtain more insight into SCC electromechanical system, the finite element analysis were also performed to study the EMI response and modal characteristics. The simulation results agreed well with experimental results. And it was found that the coupled bending modes are very sensitive to the corrosion induced thickness loss. The proposed smart corrosion coupon is cost effective, capable of determining corrosion amount quantitatively, and has promising application potential.

In civil engineering, structural modes are identified with the assumption of stationary white noise, which cannot be satisfied in practical engineering. This article proposes a new method, which contains the virtual impulse response and eigensystem realization algorithm. The formulation of virtual impulse response is derived from the inverse Fourier transform of the ratio of the cross-power to auto-power spectral density functions of the measurement responses, which is based on the concept of frequency response function. During the formulation derivation, a single point excitation is only considered. Frequency response function would not change with different excitations and responses, which means that the excitation cannot influence frequency response function. The impulse response is pointed out to only represent the behavior of superstructure. After obtaining impulse responses, eigensystem realization algorithm is then performed to identify the modes of superstructure. The proposed method is validated by a numerical example. The results show that virtual impulse response can have much better free decayed behavior than natural excitation technique and identify very precise modal parameters for superstructure.

The sensor placement methods for the modal identification are usually based on the prediction error between the measured and the structural model responses. Generally, the prediction errors, which are caused by the model error and the measurement noise, are assumed to be a Gaussian random vector together. This paper proposes a conditional information entropy based sensor placement method to separately investigate the influences of the measurement noise and the model error on the sensor placement. The changes in the element stiffness matrices are used to represent the model error. To quantify the uncertainty in the modal identification result, the conventional information entropy method is not suitable, due to the uncertainty in the Fisher matrix caused by the uncertain model error. This paper proposes a conditional information entropy index to quantify the uncertainty in the modal identification result with uncertain Fisher matrices. The optimal sensor placement corresponds to the one that maximizes the conditional information entropy index value over the set of all possible sensor placements. The conventional information entropy method can be seen as a special case of the proposed conditional information entropy method. In addition, the proposed sensor placement method can be applied to the placement of the multidimensional sensors. The simply supported beam and a bridge benchmark structure are used to explain the sensor placement method, and the redundancy threshold can be set to avoid redundant information provided by closely spaced sensors.

Cable-membrane structures have small rigidity and are highly sensitive to wind. Structural health monitoring is necessary to ensure the serviceability and safety of the structure. In this research, the design method of a structural health monitoring system is using the characteristics of a cable-membrane structure. Taking the Yueyang Sanhe Airport Terminal as an example, a finite element model is established to determine the critical structural components. Next, the engineering requirements and the framework of the monitoring system are studied based on the results of numerical analysis. The specific implementation of the structural health monitoring is then carried out, which includes sensor selection, installation and wiring. The proposed framework is successfully applied to the monitoring system for the Yueyang Airport terminal building, and the synchronous acquisition of fiber Bragg grating and acceleration sensor signals is implemented in an innovative way. The successful implementation and operation of structural health monitoring will help to guarantee the safety of the cable-membrane structure during its service life.

In practical engineering, power spectral density is always used to identify structural dynamic properties by picking peak points. However, the peaks in the spectral curve are not easy to be determined sometimes. A lot of peaks in the curve would cause some peaks close, which induces the closely spaced modes. The damping ratio is another reason to generate closely spaced modes, because the damping can make some peaks merge together. This paper proposes an innovative method to identify the closely spaced modes. First, the formulation is derived to reveal the components of the closely spaced modes in the power spectral density based on frequency domain decomposition. Then singular vector comparison is presented to determine whether there are closely spaced modes or not, where an angle criterion between two vectors is proposed. Finally, a numerical example is used to validate the effectiveness of the proposed method. The results show that the angle criterion can find the independent and dependent modes. For the close peak points in the spectral curve, the angle can determine that the points are single or closely spaced modes. Therefore, the proposed method to identify the closely spaced modes is efficient.

A wireless sensor network (WSN) eliminates physical cables and reduces the difficulty of structural information collection in a structural health monitoring (SHM) system. This paper present...

Flexibility is an important index in the assessment of bridge load-carrying capacity. Impact testing is an efficient and effective method to obtain the flexibility of small- and medium-span...

Structural health monitoring represents an efficient way to diagnose the condition of cable-stayed bridges. Most studies assessing the condition of cable-stayed bridges and detecting damage...

Bridge health monitoring (BHM) technology has been widely accepted as a powerful tool to assess structural performance and has moved from research to practice. Driven by the enormous demand of ensuring bridge safety, the application of BHM technology is particularly active in China and has become an emerging industry in the civil engineering community. It is a common belief among civil engineers that the development and implementation of industry standards will be of paramount importance in guiding the healthy development of BHM and increasing the transfer of professional knowledge and techniques to practical applications. This paper presents a comprehensive overview of the standardization construction and development trend for BHM in China. The achievements, characteristics, and challenges of China’s bridge construction are first introduced. Then, the existing problems of BHM and the necessity of constructing the standardization system for the BHM industry are discussed. Following that, these standards published for guiding BHM system design, construction, management, and maintenance, especially sensor selection, sensor placement, sensor installation, data transmission, data storage, data processing, and early warning, are outlined. Finally, work requiring further efforts in the near future is drawn.

In the dynamic characteristic analysis of high-speed railway bridges, free-vibration responses after a train passes are valuable for modal identification. However, distinguishing between fr...

Independent component analysis (ICA) has the potential to identify anomalies in structural health monitoring (SHM) data due to its non-Gaussian data-processing ability. In order to addition...

This paper proposes a strain-based performance warning method for bridge main girder monitoring using the long-term data obtained for varying load conditions, i.e., the variations in temper...

Modal identification is an important research subject in structural health monitoring. It is a mature subject for modal identification of time-invariant and stationary conditions. Because time-varying properties are valuable for damage detection and time-varying system identification, and because the environmental loads do not always satisfy the assumption of stationarity, it is necessary to develop accurate identification methods for time-varying structures, structures under nonstationary excitations, or the coupling of the two conditions. The variational mode decomposition (VMD) method, which adaptively decomposes the signal into narrow-band intrinsic modes, shows the potential for time-varying and nonstationary conditions. However, parameter selection greatly affects the accuracy of mode decomposition. In this study, a new modal identification method based on an autoregressive spectrum-guided variational mode decomposition method is proposed for the application of time-varying and nonstationary conditions. First, the determination of the initial center frequencies for VMD is proposed using an autoregressive spectrum-guided method to greatly improve the accuracy. Second, a method to select the optimal balancing factor is developed to improve the decomposition accuracy by controlling the proper bandwidth. Subsequently, an instantaneous frequency identification method is presented by detecting the ridge of the time–frequency distribution. Finally, studies of numerical and actual structures demonstrate the capacity of the proposed method for practical applications of time-varying cases and nonstationary conditions.

Wireless sensor networks are becoming attractive data communication patterns in structural health monitoring systems. Designing and applying effective wireless sensor network–based structural health monitoring systems for large-scale civil infrastructure require a great number of wireless sensors and the optimal wireless sensor networks configuration becomes critical for such spatially separated large structures. In this article, optimal wireless sensor network configuration for structural health monitoring is treated as a discrete optimization problem, where parameter identification and network performance are simultaneously addressed. To solve this rather complicated optimization problem, a novel swarm intelligence algorithm called the automatic-learning firefly algorithm is proposed by integrating the original firefly algorithm with the Lévy flight and the automatic-learning mechanism. In the proposed algorithm, the Lévy flight is adopted to maximize the searching capability in unknown solution space and avoid premature convergence and the automatic-learning mechanism is designed to drive fireflies to move toward better locations at high speed. Numerical experiments are performed on a long-span bridge to demonstrate the effectiveness of the proposed automatic-learning firefly algorithm. Results indicate that automatic-learning firefly algorithm can find satisfactory wireless sensor network configurations, which facilitate easy discrimination of identified mode vectors and long wireless sensor network lifetime, and the innovations in automatic-learning firefly algorithm make it superior to the simple discrete firefly algorithm as to solution quality and convergence speed.

Strain gauges and accelerometers are widely used in bridge structural health monitoring systems. Generally, the strain gauges are placed on the key locations to obtain local structural deformation information; the accelerometers are used to obtain the structural modal information. However, the modal information contained in the measured strains is not taken into account. In this article, to fully utilize the modal information contained in strains, a mode shape estimation method is proposed that the strain mode shapes of the strain locations are used to obtain the displacement mode shapes of some positions without accelerometers. At first, to simulate the practical situation, some positions with large structural deformations are selected as the strain gauge locations. Using the proposed mode shape estimation method, the displacement mode shapes of some locations without accelerometers are estimated by the strain mode shapes using the least squares method, and the locations with the smallest estimation error are finally determined as the estimated locations. Then, accelerometers are added to the existing sensor placement. Here, the modal assurance criterion is used to evaluate the distinguishability of the displacement mode shapes obtained from the strain gauges and accelerometers. The accelerometer locations that bring the smallest modal assurance criterion values are selected. In addition, a redundancy can be set to avoid the adjacent sensors containing similar modal information. Through the proposed sensor placement method, the deformation and modal information contained in the strain gauges is fully utilized; the modal information contained in the strain gauges and accelerometers is comprehensively utilized. Numerical experiments are carried out using a bridge benchmark structure to demonstrate the sensor placement method.

Thermal actions greatly influence the mechanical behavior of cable-stayed bridges. The objective of this research is to investigate the characteristics of the thermal field and the variability of the quasi-static responses of the bridge towers. Based on the monitoring temperature and displacement data, the distribution of the thermal field for the bridge was studied and the time variability of the tower displacement was investigated. The correlation was analyzed to study the relationship between the temperature and the tower displacements and the tower-girder distances. The temperature-induced cable force increments were calculated and a linear regression between the cable force increments and the structural temperatures was performed. A strong linear relationship between the temperature and quasi-static responses of the tower was observed. It is concluded that thermal actions have substantial effects on the quasi-static displacement. Moreover, the temperature-induced cable forces should be fully considered in the safety design of the bridge cables.

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.