Journal of Aerospace Engineering

This paper proposes a damage-identification and optimal sensor-placement approach for structures under unknown traffic-induced vibrations. Response reconstruction is performed for structures under traffic-induced vibrations to formulate the relationship between different sets of time-domain responses. Measured acceleration responses from a structure under traffic-induced ground motions are used for damage identification with a sensitivity-based iterative model updating method. Numerical simulations on a seven-story planar frame structure are conducted to verify the performance of the proposed approach. Damage identification is conducted based on the initial finite-element model of the structure and the measured responses from the damaged state under traffic-induced vibrations. Structural elemental stiffness factors are iteratively updated until the reconstructed responses match the measured ones as closely as possible. A two-phase optimal sensor-placement scheme is proposed for better response reconstruction and subsequent damage identification. Optimal sensor placement is investigated to identify the best locations for response reconstruction and sensitivity-based damage identification. With the use of optimal sensor locations, the introduced damages can be identified effectively and accurately with nearly exact damage severity estimation and very small false positives and false negatives under a 5% noise effect.

The health monitoring and analysis on the metro tunnels are very important because the metro system is the lifeline of metropolises and the shield tunnels are easily affected by adjacent constructions. In this paper, health monitoring on the deformation of operating metro shield tunnels influenced by a close deep excavation is investigated with a case in Shanghai. Both manual and automatic measuring methods were adopted in the safety monitoring during deep excavation, and the results of both methods are compared to analyze the deviation of measuring methods. Comparison shows that the automatic monitoring results could be affected by poor working conditions and cumulative error. It is suggested that different monitoring methods should be verified against each other to ensure the reliability and accuracy of the monitoring results. Based on the distribution of tunnel settlements, the curvature radius of tunnel deformation is obtained by the cubic B-spline method and then used in performance analysis on the tunnels. The relationship between the settlements and horizontal convergences of the shield tunnels are also studied, which shows a significant correlation. Analysis shows that there is no significant relationship between the curvature radius and settlements of the tunnel, which means monitoring and controlling the settlements plays an important role in protection of the tunnels but cannot guarantee the safety of tunnels. The real-time data of the curvature radius should also be calculated and analyzed in health monitoring and performance analysis on shield tunnels.

Using structural monitoring data collected from a sensor network to assess the health condition of a monitored structure relies on the accurate operation of the sensors and therefore could be affected by various sensor faults. This paper presents a sensor-fault detection and isolation approach with application to structural health monitoring. Principal-component analysis (PCA) is first applied to model the fault-free history monitoring data to generate uncorrelated residuals, which can be seen as the projection of the additional measurement noise into the residual subspace of the PCA transform. Then, under the assumption that the measurement noise is Gaussian distributed, a statistical hypothesis test model is established for the subsequent sensor-fault detection procedure, after that two fault detectors are deduced through the rejection of the null hypothesis. Next, the missing variable approach is used to establish an isolation index to identify the specific faulty sensor. A benchmark structure developed for bridge health monitoring is adopted to validate and demonstrate the performance of the proposed method, and the analysis results indicate that the method is effective in detecting and isolating both bias and drift sensor faults.

Structural-health-monitoring techniques provide valuable in-service measured information for existing civil engineering structures such as bridges, which can be used for predicting future structural performance and determining optimum maintenance strategy. This paper presents an effective approach for analyzing structural reliability during the service life of existing reinforced-concrete structures on the basis of monitored information. The process of lifetime structural-performance deterioration affected by reinforcement corrosion such as bond strength and load-bearing capacity is discussed. Crack growth in cover concrete due to reinforcement corrosion is demonstrated to be the main factor for structural-performance deterioration, thus it is chosen as a representative symptom for evaluating lifetime structural reliability. In order to consider the uncertainty in modeling structural-performance deterioration, the Weibull life evolution model associated with the cover concrete crack growth is employed for analyzing reliability, updating probability of failure profiles after maintenance, and evaluating optimal maintenance strategy. The results for a concrete bridge show that the proposed approach can provide reliable predictions of future structural performance and cost-effective maintenance strategy of aging reinforced-concrete structures.

A safety monitoring system is usually applied in deep excavations in order to control the construction risk and to ensure the serviceability of adjacent facilities. Considering the mass data collected by different sensors, a reasonable assessment method on the monitoring results is necessary to evaluate the safety state of both the deep excavation itself and the surrounding environment. By introducing the conception of data fusion, a comprehensive assessment method is presented to find the anomaly in the safety monitoring results in this paper. Data fusion analyses on both a single monitoring item and the correlation of multiple monitoring items are proposed and studied. The one-class support vector machines (SVMs) are used to improve the data fusion analysis between a single monitoring item and different excavation parameters, and then developed to three-dimensional (3D) fusion analysis on a single item and multiple parameters of an excavation. The mechanical and geometric patterns between different monitoring items are studied to propose a data fusion analysis on multiple monitoring items and then to build the assessment criteria. Based on these two kinds of data fusion analysis, the mass monitoring data can be analyzed completely to assess the safety state of deep excavations. An application in two cases of deep excavation in Shanghai, China, shows that the proposed method is effective in data anomaly assessment.

The structural behavior during the first reservoir-filling phase is significant for evaluating a super high arch dam’s safety. This paper presents an in situ monitoring network of the Xiluodu Dam in Yunnan, China, including a deformation monitoring system using geodetic and nongeodetic monitoring. The system also includes a refined thermal monitoring system based on a slab-level active cooling system. The thermal–structural decoupling numerical analysis method for a dam–water–foundation system is presented in this study with considerations of viscoelasticity material properties and internal/external thermal loads. The structural behavior of the Xiluodu Dam during the first reservoir-filling phase is analyzed using the smart monitoring system with combination of the in situ monitoring technique and the numerical simulation method. The in situ monitoring result can provide intuitional instructions of the structural behavior, showing a positive correlation between the dam deformation and the reservoir water level. The monitoring results are also used as the verification reference of the numerical model. The distribution characteristics of the displacement and stress of the dam subjected to load cases such as nonimpounding, impounding process, and the normal operating water level are discussed and predicted.

Because of the particular and complex engineering environment of subsea tunnels, effective monitoring techniques should be adopted to ensure the operation security of subsea tunnels. Also, monitoring the condition of steel corrosion in reinforced concrete (RC) of subsea tunnels is especially imperative for ensuring structural serviceability and durability of RC structures. In this paper, monitoring the largest excavation section subsea tunnel, Xiamen Xiang’an Subsea Tunnel, is studied. It includes the layout of monitoring sections and monitoring contents, selection of monitoring locations, and the monitoring instruments. The design of corrosion monitoring system is especially focused on because of its complexity. Both commercial corrosion sensors and developed corrosion sensors based on electrochemical and fiber Bragg grating techniques, respectively, are adopted. The arrangement of corrosion monitoring section and locations as well as the installations of sensors and the establishment of corrosion database are discussed. Finally, the evaluation of corrosion in the subsea tunnel is established based on the monitoring data of reinforced concrete collected in the field. Based on the monitoring data of the subsea tunnel collected in the field, the status of stress and corrosion in the Xiamen Xiang’an Subsea Tunnel can be evaluated.

Highway flyover bridges in New Jersey experienced extensive early-age cracking on the high performance concrete deck recently. There were transverse cracks observed predominantly in the positive moment regions and spider cracks concentrated in the negative moment region over the box beam. A typical two-span curved continuous bridge with high performance concrete (HPC) deck, steel girders and integral box-beam was selected to identify factors that affect early-age HPC deck cracking so as to mitigate the cracking issues on existing concrete continuous bridges. Extensive field tests were performed and various structural responses were collected for model calibration and structural analysis. Cracking issues due to effects of vertical temperature differentials, staging, shrinkage, settlement, tilt of piers, dead load, live load, etc., were quantitatively investigated and summarized through parametric study. Of prime interest has been the identification of the contributions of various effects on deck cracks. The present study provides better understanding of the behavior of curved composite bridges, which can be efficiently used to reduce the risk of cracking at early ages.

Tianjin 117 is a high-rise building comprised of a reinforced-concrete core and perimeter steel framing that includes megacolumns and megabraces, with a height of 597 m. As the construction process goes on, the influences of the external environment and loads are more crucial to structural safety. In order to verify the structural properties and behaviors in the construction stages, a structural health monitoring (SHM) system is developed in this paper by the authors’ research group. Various sensors are used in this SHM system to monitor different structural parameters that significantly affect the structural safety. The collected data can be analyzed using specifically developed software, thereby used for assessment of structural performance during construction. Interlinked with finite-element software, structural monitor/analysis/evaluation software is developed based on the idea of modular design, which can realize data exchange and result comparison between on-site monitoring and numerical models. It can be expected that the developed SHM system will provide useful information for construction of the Tianjin 117 building as well as other high-rise buildings.

In this study, the effect of temperature variation on prestress force monitoring by fiber Bragg grating (FBG) sensors embedded in prestressing tendons of prestressed concrete (PSC) girders is estimated. First, a fiber optic sensor (FOS)-based prestress force monitoring method is proposed for PSC girders with unbonded tendons. A temperature-effect estimation method is modeled to theoretically estimate the change of prestress force due to the temperature variation. Second, lab-scale experiments are performed on a PSC girder with a FBG sensor-embedded smart tendon. A series of temperature-variation and prestress-loss events are simulated for the PSC girder. Third, the feasibility of the FOS-based monitoring method is experimentally evaluated for the prestress-loss cases under constant temperature. Finally, the effect of temperature variation on the FBG sensor-embedded tendon is evaluated by the temperature-effect estimation method.

The implementation and operation of health monitoring systems in structures is an effective method of evaluating structural serviceability, reliability, safety, and integrity and providing economical maintenance and repair planning. This paper reports on an innovative structural health monitoring (SHM) system designed and permanently deployed on a complicated long-span arch bridge during its construction for the purpose of continuous performance monitoring throughout the bridge’s lifespan. The SHM system integrates several novel and practice-based concepts—i.e., life-cycle concerns for system design and implementation; newly designed high-performance sensors; flexible, modularized hardware and software; multilevel data management; multiscale condition evaluation; and reliable warning strategies. More than 300 sensors of 10 types are installed on the bridge with the aim of monitoring the environmental effects and structural responses. The innovative design and implementation of the monitoring system are presented together with a functional description of each subsystem. Selected preliminary monitoring results are outlined, including structural temperatures, main girder deformations, relationship between structural temperature and main girder deformation, and dynamic responses. The architecture of this SHM system is expected to provide a valuable reference for other structures.

Lifecycle structural health monitoring (SHM) systems provide an abundance of information that is greatly beneficial for securing structural safety over the whole service life. In application to large-scale structures, the management of accumulated massive data from a sophisticated long-term SHM system poses a challenge. A robust data management system (DMS), which not only facilitates spatiotemporal data management but also enables display in an attractive way, is highly desirable. This article presents the development of an effective visualized DMS specific for managing immense and heterogeneous SHM data by integrating nested relational database, three-dimensional (3D) model, and virtual reality (VR) technology and demonstrates its application to an instrumented supertall structure. A custom nested data model is designed to store redundant inherent temporal data and hierarchical inherent spatial data. Strategies for speeding up querying massive data are set up in the database. Making use of OpenSceneGraph (OSG) 3D engine, a 3D model is reconstructed from the 3D spatial data, which serves as a platform for data visualization. A four-dimensional (4D) animation protocol is presented by tying temporal data and construction schedule to the 3D model. The efficiency of the proposed DMS is exemplified through its application to a supertall structure instrumented with a sophisticated long-term SHM system.

Bridge scour has attracted enormous attention because of its catastrophic influence on bridge safety. In order to measure and monitor scour depth variations including deposition process, a scour monitoring system was developed in the authors’ previous study. An instrument with fiber Bragg grating (FBG) sensors was designed together with a reliable sensor-protection measure, of which the performance has been tested in the laboratory. In the present paper, the proposed system was applied on a field bridge with a critical scour history. Two test piles were manufactured and each was assembled with six standard 0.9 m-long (3 ft-long) segments. The two test piles were then installed beside two foundation piles of the field bridge, respectively, for long-term monitoring. Up until now, the measured sensor responses have verified the functionality of the proposed system. The estimated scour depths based on the sensor data to date match qualitatively well with the actual scour depths observed on the bridge site, and the concept of the scour monitoring design has been confirmed.

A complete structural health monitoring system has been implemented on Aizhai Suspension Bridge for monitoring its health status and assessing its safety for long-term services. This system consists of nearly 112 sensors of various types, including four subsystems: automatic data collection subsystem, artificial maintenance management subsystem, early safety warning and comprehensive assessment subsystem, and centralized database management subsystem. The deployments and functions of this structural health monitoring system are first introduced in this paper. Then, a finite-element model updating method, which combines the substructure method with the response surface model updating method, is proposed to reconstruct the actual working state of this suspension bridge in the early safety warning and comprehensive assessment subsystem. In the remaining part, the temperature fields, strain responses, tension forces of the hangers, longitudinal displacements of the stiffening girder, and the meteorological temperature are analyzed. Through the statistical analysis, the relationship between the temperature fields was found; the temperature fields induced strains of the stiffening girder satisfies the linear relationship. The cumulative probability distribution function of the cycle-index of the same daily stress amplitude follows a Weibull distribution. The monitored relative longitudinal displacements of the stiffening girder are linearly related with the meteorological temperatures. The monitored tension forces of the hangers verify the effects of the suspender-free zones of main cables on the normal hangers for this pylon-girder detached suspension bridge.

In this paper, a stable and robust filter is proposed for structural identification. This filter resolves the instability problems of the traditional extended Kalman filter (EKF). Instead of ad hoc assignment of the noise covariance matrices in the EKF, the proposed stable robust extended Kalman filter (SREKF) provides real-time updating of the noise parameters. This resolves the well-known instability problem of the EKF due to improper assignment of the noise covariance matrices. Furthermore, the proposed SREKF is capable of removing abnormal data points in a real-time manner. As a result, the parametric identification results will be more reliable and have fewer fluctuations. The proposed approach will be applied to structural damage detection of degrading linear and nonlinear structures in comparison with the plain EKF, utilizing highly contaminated response measurements. It turns out that the estimation error of the state vector and the structural parameters is lower than the EKF by one and two orders of magnitude, respectively.

A reference-free damage detection method based on distributed monitoring of strains in large structural systems is introduced. The method employs the dynamic distributed strain data to formulate its own virtual reference state for detection of defect locations. It uses a single line of optical fiber by way of a dynamic pulse-prepump (amplitude transfer) Brillouin scattering technique in order to acquire dynamic distributed strain data. An experimental program was designed to evaluate the performance of the proposed methodology. The experiments involved dynamic tests of a long beam with simulated defects with small opening displacements ranging between 50 and 550 μm. The implications of this approach are significant since it enables the structure to be monitored at any stage during its service life without the need for prior reference data.

In structural health monitoring, the presence of damage is detected and localized by outlining the differences between the initial state and current behavior of a given structure. The problem is often formulated as an optimization problem. In this paper, a highly nonlinear objective function that minimizes the discrepancies between the analytical and experimental features of a structure is introduced. Within a finite-element discretization, some stiffness parameters are chosen as reference variables. Two metaheuristic tools, the artificial bee colony (ABC) algorithm and the firefly algorithm (FA), are applied to proceed the iterations toward the global minima of the objective function. By comparing the identified and analytical stiffness matrices, the damage detection and localization are performed. These methods are applied to a steel structure. The efficiency of the two tools is compared.

The Shenzhen Vanke Center is constructed of a composite frame and cable system, which is a novel structural system and leads to a tedious, complex, and lengthy construction process. The structural construction process simultaneously affects the shape of the Shenzhen Vanke Center and the final structural force state. To control the construction process and make sure the construction is safe, a structural health monitoring system for the Shenzhen Vanke Center construction has been implemented, which includes monitoring of the cable tensioning phase and superstructure construction phase. In this paper, the Shenzhen Vanke Center and its construction process are first introduced. The monitoring data for a standard unit of the whole structure was selected for study. For the cable tensioning phase, these data include the cable forces, strains of the bottom floor’s steel beams, and concrete-filled steel column and structural displacements; for the superstructure construction phase, the data include the cable forces and structural displacements. According to this monitoring data, a comprehensive understanding for the performance of the structure and key members in the construction phase are shown and discussed. The analysis results indicate that the construction monitoring system of the Shenzhen Vanke Center is stable and reliable. It also has many functions, such as to guide the cable tensioning, to grasp the changes in strain of key members, to control the structural construction deformation, to conduct the construction process, and to ensure safe structural construction.

Ambient vibration tests and analyses of a long-span rigid-frame bridge were conducted using distributed long-gauge fiber-optic sensors. The concept of a long-gauge fiber-optic sensor and its merit to reveal local and global structural features are presented. Monitoring of a long-span bridge was performed using long-gauge sensors, and a method to calculate structural deformation distribution from the measured long-gauge strains is proposed, in which shear-deformation effect is considered because the main girder of the studied bridge is deep with a length–depth ratio of 17.9 at the end of the middle span. Modal identification of the studied bridge using the measured long-gauge dynamic strains was also performed, from which strain and displacement mode shapes were identified. Those results demonstrate the superiority of long-gauge fiber-optic sensors and their successful application to the studied bridge.

A distinct element model was proposed to simulate cracking in a reinforced concrete beam, and the influence of cracking on natural frequency was analyzed. Hexagonal block and tensile-shear failure criteria were implanted into the framework of the expanded distinct element method to determine two-dimensional cracking and to analyze the crack growth of the reinforced-concrete beam. Experimental tests were also carried out to verify the numerical simulation results. Numerical and experimental results show that at the cracking initiation stage, cracks appear below the loading points because of concentrated tensile stresses and grow upward. When these cracks penetrate three-quarters of the beam, cracks open in the bottom and gradually curve toward the loading points. Cracks caused by shear failure occur in the top of the beam. The beam fails because of a yielding of the longitudinal tensile reinforcement bar. Cracking and yielding of longitudinal tensile reinforcement can be identified based on a continuously descending natural frequency.