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Preview: Journal of Structural Control

Structural Control and Health Monitoring

Wiley Online Library : Structural Control and Health Monitoring

Published: 2018-03-01T00:00:00-05:00


Multisensor-based hybrid empirical mode decomposition method towards system identification of structures


Multivariate empirical mode decomposition (MEMD) method is explored in this paper to perform modal identification of structures using the multisensor vibration data. Due to inherent sifting operation of empirical mode decomposition (EMD), the traditional MEMD results in mode-mixing that causes significant inaccuracy in modal identification and condition assessment of structures. Independent component analysis, another powerful blind signal decomposition method, is integrated with the MEMD to alleviate mode-mixing in the resulting modal responses. The proposed technique is verified using a suite of numerical, experimental, and full-scale studies (a building tower in China and a long-span bridge in Canada) considering several practical applications such as low-energy frequencies, closely spaced modes, and measurement noise. The results confirm the improved performance of the proposed method and prove that it can be considered as a robust system identification tool for flexible structures.

The strain amplification sensor: A 3D-printable stand-alone strain gauge for low-cost monitoring


Current in situ strain sensing techniques focus on determining accurate, time-histories of strain utilizing fairly complex sensing, compensation, data processing, and powering arrangements. A simpler and lower-cost strain sensing approach would open up more opportunities to use strain measurements to support engineering decision making. This work explores a fully mechanical, ultra-low cost strain sensor printed using additive manufacturing techniques. The accuracy of current additive manufacturing techniques are discussed, and the performance of the sensor in terms of accuracy, measurement repeatability, and batch-to-batch manufacturing variability are studied. An example of using the proposed sensor to measure transient thermal weld stresses is presented. Overall, the key challenge to such a sensor is shown to be the accuracy of pin and slot print features and the resulting slip and friction introduced into the sensor. A properly calibrated design printed with current state-of-the-art machines is shown to be capable of resolving strain changes on the order of one micro strain with good repeatability.

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge


Vision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets for video processing convenience, leading to high installation effort and focus on only single-point displacement measurement, for example, at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multipoint displacement measurement based on a consumer-grade camera for video acquisition and a custom-developed package for video processing. The system has been validated on a cable-stayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. The analysis results indicate that the system provides valuable information about bridge deformation of the order of a few centimetres induced, in this application, by pedestrian passing. The measured data enable accurate estimation of modal frequencies of either the bridge deck or the bridge cables and could be used to investigate variations of modal frequencies under varying pedestrian loads.

Observer-based repetitive model predictive control in active vibration suppression


In this paper, an observer-based feedback/feedforward model predictive control (MPC) algorithm is developed for addressing the active vibration control (AVC) of lightly damped structures. For this purpose, the feedback control design process is formulated in the framework of disturbance rejection control (DRC) and a repetitive MPC is adapted to guarantee the robust asymptotic stability of the closed-loop system. To this end, a recursive least squares (RLS) algorithm is engaged for online estimation of the disturbance signal, and the estimated disturbance is feed-forwarded through the control channels. The mismatched disturbance is considered as a broadband energy bounded unknown signal independent of the control input, and the internal model principle is adjusted to account for its governing dynamics. For the sake of relieving the computational burden of online optimization in MPC scheme, within the broad prediction horizons, a set of orthonormal Laguerre functions is utilized. The controller design is carried out on a reduced-order model of the experimental system in the nominal frequency range of operation. Accordingly, the system model is constructed following the frequency-domain subspace system identification method. Comprehensive experimental analyses in both time-/frequency-domain are performed to investigate the robustness of the AVC system regarding the unmodeled dynamics, parametric uncertainties, and external noises. Additionally, the spillover effect of the actuation authorities and saturation of the active elements as two common issues of AVC systems are addressed.

Terrestrial laser scanner assessment of deteriorating concrete structures


A terrestrial laser scanner (TLS) assessment of corrosion and deterioration on an accelerated laboratory specimen, together with a 40-year-old seawall, has been undertaken. The assessment studied the potential of a commercial TLS to detect crack initiation and growth and to monitor long-term deterioration. In concrete structures with ongoing deterioration, the TLS data were able to identify indicators of delaminated concrete, via surface movement over time, as well as concrete loss. Thus, TLS provides a possible technique to monitor deterioration of concrete structures over time without the need for close access. In the accelerated laboratory specimen, the data showed an apparent correlation between measurement uncertainty and crack growth, though no clear evidence of the exact time of crack initiation or crack width could be determined.

Real-time substructural identification by boundary force modeling


A major difficulty of structural identification is due to the large number of unknowns and its induced ill condition. Substructural identification approach opens a new angle for the identification of large-scale structures because it offers the flexibility to isolate some critical substructures for identification. The key is to estimate the boundary force using response measurements. However, after 2 decades of development, it has been found that this approach worsens the identifiability of the inverse problem. In this paper, we propose a new real-time substructural identification approach to resolve the ill-posed problem. Its major crux is to model the boundary force as modulated filtered white noise, which can be viewed as a continuity condition. As a result, the boundary force is estimated not only through the response measurement at the same time step but also the boundary force estimation of previous time steps. This drastically enhances the computational condition of the problem. Furthermore, the proposed method does not require stationarity of the response. Examples using a hundred-story shear building under different stationarity scenarios are used to demonstrate the performance of the proposed method.

Investigation of dynamic properties of long-span cable-stayed bridges based on one-year monitoring data under normal operating condition


Environmental factors, such as temperature, traffic, and wind, play an important role on the variations of dynamic properties of long-span cable-stayed bridges. The dynamic characteristics of Sutong Cable-Stayed Bridge (SCB), including acceleration and strain responses as well as modal frequencies, are investigated using one-year continuous monitoring data under operating conditions by the structural health monitoring system. The in situ wind characteristics and structural temperature behavior of SCB are also analyzed. More than 99% of the wind speed values are smaller than 16 m/s; and the largest temperature variation of the main girder exceeds 60 °C. Besides, acceleration and strain, root mean square (RMS) data are both normalized using the Z-score standardization method. Relation analysis between the normalized acceleration and strain RMS values is conducted based on the time-history comparison and linear least square fitting. Results show that both of the processed acceleration and strain RMS values could properly describe the variation trend of the traffic load, although variation amplitudes of the two normalized parameters differ from each other. In addition, one-year continuous modal frequencies of SCB are identified using Hilbert–Huang transform method. Variability analysis of the structural modal frequencies due to environmental temperature and operational traffics is then conducted. Results show that temperature is the most important environmental factor for vertical and torsional modal frequencies. The traffic load is the second critical factor especially for the fundamental vertical frequency of SCB. Research results could provide references for damage detection and safety evaluation for similar long-span cable-stayed bridges.

Damage detection in asymmetric buildings using vibration-based techniques


In recent times, esthetic and functionality requirements have caused many buildings to be asymmetric. An asymmetric building can be defined as one in which there is either geometric, stiffness, or mass eccentricity. Such buildings exhibit complex vibrations as there is coupling between the lateral and torsional components of vibration and are referred to as torsionally coupled buildings. These buildings require 3-dimensional modeling and analysis. Despite recent research and successful applications of damage detection techniques in civil structures, assessing damage in asymmetric buildings remains a challenging task for structural engineers. There has been considerably less investigation on the methodologies for detecting and locating damage specific to torsionally coupled asymmetric buildings. This paper develops a multicriteria approach using vibration-based damage indices for detecting and locating damage in asymmetric building structures. These vibration indices are based on the modified versions of the modal flexibility and the modal strain energy methods. The proposed procedure is first validated through experimental testing of a laboratory scale asymmetric building model. Numerically simulated modal data of a larger scale asymmetric building obtained from finite element analysis of the intact and damaged asymmetric building models are then applied into the modified modal flexibility and modal strain energy algorithms for detecting and locating the damage. Results show that the proposed method is capable of detecting both single and multiple damages in the beams and columns of asymmetric building structures.

Bayesian optimal sensor placement for crack identification in structures using strain measurements


A Bayesian framework is presented for finding the optimal locations of strain sensors in a plate with a crack with the goal of identifying the crack properties, such as crack location, size, and orientation. Sensor grids of different type and size are considered. The Bayesian optimal sensor placement framework is rooted in information theory, and the optimal grid is the one which maximizes the expected information gain (Kullback–Liebler divergence) between the prior and posterior probability density functions of the crack parameters. The uncertainty in the crack parameters is accounted for naturally within the Bayesian framework through the prior probability density functions. The framework is demonstrated for a thin plate with crack, subjected to static loading. A finite element model is used to simulate the strain distributions in the plate given the crack properties. To verify the effectiveness of the proposed optimal sensor placement methodology, the estimated optimal sensor grids are used to perform Bayesian crack identification using simulated data. Parametric analyses are carried out giving emphasis on the effect of the number of sensors, grid type, and experimental data noise levels in the identification results.

Anomaly identification of foundation uplift pressures of gravity dams based on DTW and LOF


Anomaly can provide valuable information for dam safety monitoring. In this paper, a methodology integrating dynamic time warping and local outlier factor to identify anomalies of time series on various time scales is proposed. The main steps of the methodology are introduced in detail. First, measured time series are preprocessed using moving average and normalization, respectively, to eliminate influence of random and amplitude variations. Following this, time series of independent variables (predictors) are selected as templates to calculate dynamic time warping distances using the global constraint to measure similarities with the dependent variable (a predicant) on a large time scale. Then, traditional regression models are built to find out contributions of independent variables to structural behavior, as well as to highlight unwanted behaviors at relatively on a small time scale. Furthermore, local outlier factor values of multivariate are computed, which helps finding anomalies on a small time scale. Finally, causes of anomalies are analyzed comprehensively. A case study is presented focus on the measured foundation uplift beneath the local riverbed blocks of Xixi reservoir dam. Results show that point anomalies occur with sudden changes of independent variables, but contextual anomalies boil down to coupled effect of high reservoir level and low ambient temperature. The natural condition of the rock foundation underlying blocks, which is characterized as intensively open tension joints, is responsible for uplift anomalies.

Anomaly detection with the Switching Kalman Filter for structural health monitoring


The detection of changes in structural behaviour over time, that is, anomalies, is an important aspect in structural safety analysis. This paper proposes an anomaly detection method that combines the existing Bayesian Dynamic Linear Models framework with the Switching Kalman Filter theory. The key aspect of this method is its capacity to detect anomalies based on the prior probability of an anomaly, a generic anomaly model, as well as transition probabilities between a normal and an abnormal state. Moreover, the approach operates in a semisupervised setup where normal and abnormal state labels are not required to train the model. The potential of the new method is illustrated on the displacement data recorded on a dam in Canada. The results show that the approach succeeded in identifying the anomaly caused by refection work, without triggering any false alarm. It also provided the specific information about the dam's health and conditions.

Design of a wireless vibration metre for conductor vibration monitoring


We present a vibration metre for conductor vibration measurement that is highly accurate due to its robustness against interference from the electromagnetic environment. According to the range of load currents in the transmission line, a power supply module based on induction charging is designed for the vibration metre. The module is composed of three parts: the mutual inductor obtains electrical energy from the transmission line based on the electromagnetic induction principle, the power controller manages the charging and discharging of a lithium battery, and the lithium battery supplies power to all modules and sensors. A cantilever beam displacement sensor is used to measure the vibration amplitude of the conductor. Moreover, a calibration method based on two-dimensional regression is proposed to address the linear variation of the sensor output due to frequency variations. The corresponding test platform for power supply and accuracy is established, and the experiments verify the feasibility and accuracy of the vibration metre. Furthermore, the vibration metre is tested on a conductor spanning 105 m at Xi'an Polytechnic University. The test data show the number of amplitudes appearing at different frequencies within 10 days, which indicates the characteristics of vibration during this time.

A layered beam element for modeling de-bonding of steel bars in concrete and its detection using static measurements


In the formulation of finite elements, the variation of elemental internal forces and displacements are interpolated. The force interpolation functions are known to reproduce the variations of forces better than the interpolation functions on the displacements. Layered section beam model is not as complicated as the fiber model, and yet, it is much more accurate than ordinary beam model. The force-based finite element is revisited in this paper with its application in the numerical studies of a damage detection strategy for a reinforced concrete beam under static load. Two kinds of damages are studied including the cracking or other local damage of the concrete and the bonding between the concrete and the steel bar. Both kinds of damages in an element can be detected separately or in combinations with the proposed strategy. The force-based layered finite element is shown to be a practical, accurate, and efficient representation of the bonding damage of steel bars in concrete structures.

On the use of mode shape curvatures for damage localization under varying environmental conditions


A novel damage localization method is introduced in this study, which exploits mode shape curvatures as damage features, while accounting for operational variability. The developed framework operates in an output-only regime,that is, it does not assume availability of records from the influencing environmental/operational quantities but rather from response quantities alone. The introduced tool comprises 3 stages pertaining to training, validation, and diagnostics. During the training stage, a representation of the healthy, or baseline, structural state is acquired over varying operational conditions. A data matrix is formulated, whose individual columns correspond to mode shape curvatures at distinct operational conditions, and principal component analysis (PCA) is applied for extraction of the imprints of separate operational sources on these curvatures. To this end, a residual matrix between the original and the PCA mapped data is formed serving for statistical characterization of each mode. Subsequently, during the validation and diagnostics stages, the mode shape curvature matrices for the currently inspected structural state are assembled and the same PCA mapping is enforced. A typical hypothesis test and a corresponding damage index are then adopted in order to firstly detect damage, and to secondly localize damage, should this exist. The implementation of the proposed method in 2 numerical case studies confirms its effectiveness and the encouraging results suggest further investigation on operating structural systems.

Bayesian optimal estimation for output-only nonlinear system and damage identification of civil structures


This paper presents a new framework for output-only nonlinear system and damage identification of civil structures. This framework is based on nonlinear finite element (FE) model updating in the time-domain, using only the sparsely measured structural response to unmeasured or partially measured earthquake excitation. The proposed framework provides a computationally feasible approach for structural health monitoring and damage identification of civil structures when accurate measurement of the input seismic excitations is challenging (e.g., buildings with significant foundation rocking and bridges with piers in deep water) or the measured seismic excitations are erroneous and/or distorted by significant measurement error (e.g., malfunctioning sensors). Grounded on Bayesian inference, the proposed framework estimates the unknown FE model parameters and the ground acceleration time histories simultaneously, using the sparse measured dynamic response of the structure. Two approaches are presented in this study to solve the joint structural system parameter and input identification problem: (a) a sequential maximum likelihood estimation approach, which reduces to a sequential nonlinear constrained optimization method, and (b) a sequential maximum a posteriori estimation approach, which reduces to a sequential iterative extended Kalman filtering method. Both approaches require the computation of FE response sensitivities with respect to the unknown FE model parameters and the values of base acceleration at each time step. The FE response sensitivities are computed efficiently using the direct differentiation method. The two proposed approaches are validated using the seismic response of a 5-story reinforced concrete building structure, numerically simulated using a state-of-the-art mechanics-based nonlinear structural FE modeling technique. The simulated absolute acceleration response time histories of 3 floors and the relative (to the base) roof displacement response time histories of the building to a bidirectional horizontal seismic excitation are polluted with artificial measurement noise. The noisy responses of the structure are then used to estimate the unknown FE model parameters characterizing the nonlinear material constitutive laws of the concrete and reinforcing steel and the (assumed) unknown time history of the ground acceleration in the longitudinal direction of the building. The same nonlinear FE model of the structure is used to simulate the structural response and to estimate the dynamic input and system parameters. Thus, modeling uncertainty is not considered in this paper. Although the validation study demonstrates the estimation accuracy of both approaches, the sequential maximum a posteriori estimation approach is shown to be significantly more efficient computationally than the sequential maximum likelihood estimation approach.

Long-term monitoring of relative displacements at the keystone of a masonry arch bridge


Nonstop development of the railway transportation and some demands such as axle load increasing caused many researchers work thoroughly about the sustainable development. It consists of the maintenance of historic structures instead of replacing them. Following the same track, the current research is illustrating the structural health monitoring of a masonry arch railway bridge with the main span of 66 m. The leading concern through this research is the changes in relative displacements of the adjacent blocks. Eccentricity tracing, assessment of the maximum service load, and comparing the changes with the code loading are presented in this paper. Estimation of the dynamic impact factor are among the objectives satisfied by taking advantage of the monitoring data, as well. It is also to rate the efficiency of the applied method in tracing the structural performance of the complex structures like masonry arch bridges.

Innovative substructure approach to estimating structural parameters of shear structures


An innovative substructure approach is proposed for estimating the structural parameters of shear structures from the acceleration responses of individual substructures. Two parallel methods are created to form single-degree-of-freedom models of each substructure. The behavioral characteristics of these substructure models chiefly depend on the structural parameters of the edges of the component substructure, which is separate from the shear structure. To obtain structural parameters from the substructure accelerations, discrete substructure models with accelerations are generated using Newmark's method and are found similar to the autoregressive moving average with exogenous (ARMAX) inputs models. Sophisticated techniques for solving ARMAX models are used to process the accelerations and to extract the structural parameters of the substructures. A linear relationship among model coefficients of the discrete substructure models and ARMAX models is discovered that provides an accurate and simple way to identify all the substructure parameters. A numerical simulation of a 10-story shear structure during earthquake is performed to verify this substructure approach, where the factors of the size of the substructure and the noise disturbance are considered. Finally, this substructure approach is used to identify a structural model and reproduce the structural responses of a five-story three-dimensional structure in a shaking-table experiment.

Markov chain Monte Carlo-based Bayesian method for structural model updating and damage detection


This paper proposes a Bayesian method for structural model updating and damage detection using modal data. A recently developed Markov chain Monte Carlo algorithm is adopted to handle the model updating problem. The proposed Bayesian method focuses on calculation of the posterior probability distribution function of uncertain model parameters. In addition to the most probable values of the uncertain parameters, the associated uncertainties can be calculated with consideration of the effects of both the modeling error and the measurement noise. An experimental case study was carried out with a shear building model under laboratory conditions to study the identifiability of the model-updating problem following the proposed Bayesian method. The results demonstrate the change in the posterior probability distribution function of the uncertain parameters with the amount of measured information. It also demonstrates the ability of the proposed method to handle unidentifiable problems. The proposed Bayesian method is then applied for structural damage detection by calculating the probability distribution of the extent of damage to various structural components. To demonstrate the proposed Bayesian damage-detection method, ambient vibration tests were carried out on a 2-story steel frame with bolted connections. Joint damage was simulated by loosening some bolts at the target beam-column connection. The model-updating results show that the uncertainty associated with the rotational stiffness of the steel joints was very high, rendering the problem almost unidentifiable. Although the problem is almost unidentifiable, the calculated probability distribution of the damage extent can still locate the damaged joint and estimate the damage extent (i.e., the percentage reduction in rotational stiffness) together with the associated uncertainty.

Utilising hydraulic transient excitation for fatigue crack monitoring of a cast iron pipeline using optical distributed sensing


Corrosion-induced failures are common in cast iron pipes used in water supply networks. Over times, cracks may initiate from the corroded pits and grow when subjected to fatigue internal loading. When the particular region of the pipe loses its structural capacity, it will eventually lead to leakage or even pipe burst. Thus, it is important to perform permanent and real-time integrity monitoring on these pipelines. Distributed optical fibre sensors (DOFS) have been proposed to monitor the structural health of water pipelines for the last few decades. Most of the previous studies have shown that DOFS is effective in monitoring the condition of a pipeline subjected to static operating pressure. This paper aims to experimentally demonstrate the ability of distributed optical fibre strain sensor to monitor the fatigue crack growth along the cast iron pipeline subjected to pressure transient. The fatigue test was conducted using a large-scale cyclic internal pressure loading facility. The DOFS was instrumented on the pipe to monitor the condition of the pipe when subjected to internal pressure loading approximation of water pressure loading (operating pressure and pressure transient) experienced in the field. The measured response will show the potential application of DOFS for crack detection, as well as monitoring the fatigue crack growth along the pipe. The results confirmed that DOFS is able to enhance the detection of cracks along the pipe subjected to pressure transient.

Proposal of optimum tuning of semiactive TMDs used to reduce harmonic vibrations based on phase control strategy


Tuned mass dampers (TMDs) are a well-established technology for passive structural vibration control involving harmonic vibrations. Some design issues are critical to guarantee the proper functioning of the device, in particular, the adequate tuning and the adequate space to accommodate the TMD stroke. With regard to the first aspect, semiactive TMDs were proposed as an alternative means of correcting the vibrating frequency of the device by adding a semiactive element between the TMD and the structure. In this case, several control strategies have been proposed, among which phase control has proven to lead to excellent results. However, in the framework of this control approach, the minimization of the structure displacements is often used as the main objective of the control, as the relative displacements of the TMDs mass are considered a secondary issue, which nevertheless may be a crucial aspect in some applications. In this context, this paper proposes a strategy to optimally tune the semiactive TMD, taking into account a balance between the level of the reduction of the structural response and the amplitude of the TMD stroke. The optimal tuning is found by minimizing the system stationary mechanical energy. The problem is formulated as an optimization process, and the corresponding results are presented and discussed.

An UKF-based nonlinear system identification method using interpolation models and backward integration


In this paper, a novel identification method for nonlinear systems is proposed. This method utilizes linear interpolation models to describe the nonlinear forces of the physical models, and the unscented Kalman filter (UKF) method is adopted for the task of nonlinear identification. With the help of a linear interpolation algorithm, the proposed method requires little prior knowledge of the form of the nonlinear stiffness. Therefore, this method takes advantage of both the independence of the linear interpolation points and the inherent mathematical properties of the UKF. The UKF method is also modified to better fit the needs of parameter identification. To further emphasize parameter identification, backward integration and observations of the previous states are used. Two numerical simulations of the nonlinear elastic stiffness and Bouc–Wen hysteresis are conducted to show the flexibility and efficiency of this method. In these 2 examples, the observation signals are generated by analytic models, and the identifications are conducted with a linear interpolation model.

Ice monitoring of a full-scale wind turbine blade using ultrasonic guided waves under varying temperature conditions


The icing of wind turbine blades is a common problem in cold climate area. Ice accretion on wind turbines, particularly turbine blades, can cause a variety of problems. The extreme icing may induce full stop of the turbine system. Thus, ice monitoring is one of the important issues for turbine blade icing solutions. The ice coating on the blade surface can change the primary propagation characteristics of the elastic waves. Therefore, Lamb waves are proposed to monitor the ice-forming processes of a full-scale wind turbine blade. Because the varying temperature is a remarkable and inevitably factor during ice monitoring, a principal component analysis (PCA)-based ice monitoring method is proposed to eliminate the temperature effects and is first demonstrated by a segment of the blade in the laboratory. Subsequently, the proposed method is applied on a full-scale blade in the frozen tunnel. The PZT wafers array is arranged to enhance the guided wave signals, and the tuning and attenuation characteristics are investigated on the clear surface of blade without ice. Finally, the PCA-based method is used to identify the ice formation again on both the tip and the middle segments of the full-scale blade under varying temperature conditions. The results indicate that the proposed ultrasonic guided wave combining PCA-based method is efficient and sensitive for ice monitoring of the full-scale wind turbine blade.

Robust design of a multi-floor isolation system


A multi-floor isolation (MFI) technique can provide a building with inherent dynamic vibration suppressors through decoupling different portions of floors masses from the superstructure. This paper evaluates the seismic effectiveness and robustness of the MFI technique using a test-bed 20-story building. First, a parametric study approach is utilized to optimize MFI configurations with different isolated mass ratios (IMRs) and different number of isolated floor subsystems (IFSs). The response quantity to be optimized is the sum of root-mean-square interstory drift responses of the superstructure under a stochastic excitation. The sensitivity of the seismic performance of the optimally designed MFI configurations with respect to uncertainties in the properties of the superstructure, IFSs, and the ground excitation is evaluated. Simulation results illustrate that with the presence of these uncertainties, the effectiveness of the optimally designed MFI configurations with low and high IMRs (e.g., 5% and 90%) is significantly impaired, whereas configurations with intermediate IMRs (e.g., 50%) exhibit a relatively stable performance. Evaluation of the optimal placement of IFSs along the building height, when the number of IFSs is limited, reveals that placing the IFSs at top stories can lead to a near-optimal system in terms of the spatial distribution of IFSs. A genetic algorithm is used to design a robust system for a selected configuration with top 10 IFSs and an IMR of 50%. The robust design is performed via minimizing the maximum deviation with respect to the design root-mean-square interstory drift response when the design parameters vary within a given uncertainty range.

Structural damage identification using image-based pattern recognition on event-based binary data generated from self-powered sensor networks


A continuing challenge in structural health monitoring is power availability for sensors to collect and communicate data. A way to minimize the communication power demand is to transmit the minimum amount of information, namely, one bit. Event-based binary signals are generated at sensor nodes according to local rules based on physical measurements, but interpretation at the global level requires dealing with discrete binary data, which implies system information with reduced resolution. This study presents an investigation on approaches for the interpretation of event-based binary data provided by a self-powered sensor network using a pulse-communication protocol for use in structural assessment and damage identification. Pattern recognition (PR) methods based on image data analysis techniques were adapted for such purpose. The methods used were classifiers based on anomaly detection, a Bayesian method, and a nearest neighbor method. To improve the performance of the approach, 2-dimensional principal component analysis and 2-dimensional linear discriminant analysis were used as feature extraction techniques along with a nearest neighbor classifier. The PR methods and the performance of the interpretation algorithms were evaluated by using virtual data from finite element simulations and real data from experiments on plates. The ability of the PR methods to identify service demands, load variations, and localized material degradation was examined. Results indicate that image-based PR methods can be effectively used for structural damage identification in plate-like structures using event-based binary data sets in novel wireless self-powered sensor networks.

Local effects induced by dynamic load self-heating in NiTi wires of shape memory alloys


The use of shape memory alloys wires in dampers devices for Civil Engineering applications is well documented in the literature. This paper develops a critical discussion on the wire macroscopic behavior and on the associated temperature effects with emphasis on the wire diameter. Vibration damping requires the absorption of mechanical energy and its conversion to heat via the action of hysteresis cycles. The experimental study is carried out on NiTi wires of different diameters. The flat cycles shown by thin wires (i.e., 0.5 mm of diameter or less) and the nonclassical S-shaped cycles (e.g., for diameter 2.46 mm) establish clear differences in the response of the samples. For this reason, a supplementary investigation is here reported to show that the flat cycles are coherent with the classical treatment of shape memory alloys as a first-order phase transition, but the S-shaped cycles of thick wires can be associated to an anomaly in the heat capacity.

Sliding mode trajectory tracking control of a ball-screw-driven shake table based on online state estimations using EKF/UKF


In this paper, we propose a new trajectory tracking control of a ball-screw-driven servomechanism for a shaking table. Displacement and acceleration sensors are assumed available, but currents and velocity sensors are not. The design of this control strategy is based on sliding mode approach with state estimation by extended Kalman filter/unscented Kalman filter. The basic feature of this design is that high velocity and high positioning accuracy can be met despite of the fact that the controlled process suffers from noise, friction, and uncertainty. Torque/flux sliding mode controller with online estimation using extended Kalman filter and unscented Kalman filter is proposed to improve velocity sensorless trajectory tracking control of uniaxial earthquake simulator. Simulation works are carried out to show the ability of the proposed method to simulate the speed and acceleration of 2 important earthquakes. The results also demonstrate the activity of the proposed strategy at wide range of velocity operation with measurement noises.

Evaluation of the dynamic characteristics of a super tall building using data from ambient vibration and shake table tests by a Bayesian approach


The Shanghai Tower is a newly built 127-story and 632 m high super tall building. As of April 2017, it was ranked as the second tallest building in the world. Its main structural system is a mega-frame-tube-outrigger system with six outrigger trusses along the height. Due to its unique structural configuration, a series of field and laboratory model tests have been conducted to better understand its dynamic characteristics. Before its construction, a scaled model of the tower was tested on a shake table, and the results were used to refine the design of the tower. At the completion of the construction, full-scale ambient vibration tests were performed. A Bayesian method was used to perform operational modal analysis from the shake table and full-scale ambient vibration tests. The most probable value of the modal parameters and the associated posterior uncertainties were calculated using this method. The first eight modes were identified, including three translational modes in each principal direction and two torsional modes. Using these results, the dynamic characteristics and associated uncertainties obtained from the two tests were investigated and compared in this paper. Due to the scaling of the model, there are some discrepancies between the natural frequencies obtained from two different tests, but the identified mode shapes matched very well. Although the structure was designed in a very innovative manner, its dynamic characteristics are similar to regular tall buildings. The results from this investigation provide valuable information for an ongoing condition assessment of this super tall building.

Comprehensive investigation of leakage problems for concrete gravity dams with penetrating cracks based on detection and monitoring data: A case study


The leakage amount is an important indicator evaluating the seepage behavior of a dam. Due to the complex behavior, crack development judgment and leakage behavior identification for concrete gravity dams remain a challenging task. The paper is concerned with comprehensive investigation of leakage problems for concrete gravity dams with penetrating cracks. A case study on Shimantan Reservoir Dam was taken to examine the utilization of the comprehensive investigation method. Deficiency investigations were undertaken to identify the nature and sources of defects responsible for the serious leakage. Based on the information acquired from field visual inspections and ground-penetrating radar tests, it is apparent that several transverse cracks penetrate the dam crest and propagate downward into the dam body. The results of the remedial grouting, X-ray diffraction analyses and water injection tests reflect the appearance of penetrating leakage paths in the dam body. Subsequently, 2 behavior models including the special hydrostatic-seasonal-time model and the inverse analysis model were conducted to distinguish the contribution of penetrating cracks to leakage amount. The special hydrostatic-seasonal-time model was modified to address the influence of leakage flow in real microcracks in concrete dams based on the Navier–Stokes equation. The result shows that the proposed models provide an acceptable accuracy in analyzing leakage monitoring data for gravity dams with penetrating cracks. Leakage flow in penetrating cracks plays a dominant role in the dam seepage field. The execution flow in this paper could be readily employed in investigations of similar problems of concrete dams.

Theoretical study and experimental validation on the energy dissipation mechanism of particle dampers


An energy dissipation factor was proposed to quantify the energy dissipation mechanism of particle dampers based on theoretical analysis and was further validated by free vibration tests and wind tunnel tests. The vibration energy of the main structure was consumed by impact and friction between particles and between particles and the container. An elastoplastic collision model and a simplified frictional-elastic collision model were used to analyze the energy dissipation due to impact and friction, respectively. Then, an energy dissipation factor, reflecting the vibration energy consumption of a particle damper, was defined. Finally, free vibration tests and aero-elastic wind tunnel tests of a benchmark model unattached or attached with particle dampers were conducted to validate the relationship between the vibration reduction performances and the energy dissipation factors, and the experimental results were in qualitative agreement with the theoretical results. Consequently, the energy dissipation factor indicated the energy dissipation mechanism of particle dampers and can be used to select the proper material of the particles, helping to maximize the vibration control effects from the material's perspective. It was shown that the material of higher kinetic friction coefficient, higher modulus of elasticity, and lower yield strength usually leads to better energy dissipation effects.

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Bayesian identification of soil-foundation stiffness of building structures


A probabilistic method is presented for identifying the dynamic soil-foundation stiffnesses of building structures. It is based on model updating of a Timoshenko beam resting on sway and rocking springs, which respectively represent the superstructure and the soil-foundation system. Unlike those previously employed for this particular problem, the proposed method is a Bayesian one, which accounts for the prevailing uncertainties due to modeling and measurement errors. As such, it yields the probability distribution of the system parameters as opposed to average/deterministic values. In this approach, the joint probability density function of the parameters that control the flexible-base Timoshenko beam model, together with the fundamental natural frequency and mode shape of the system, forms the prior distribution. Using Bayes' theorem, a posterior distribution is obtained by updating the prior distribution with a sparsely measured mode shape and frequency. The most probable realizations of the system parameters are then determined by maximizing the posterior distribution. For this purpose, first- and second-order derivatives of the objective function are analytically computed via direct differentiation. The proposed method is verified using a synthetic example. Additionally, sensitivity analyses are carried out on both the system parameters and standard deviations of the sources of error. Subsequently, the proposed method is applied to real-life data recorded at the Millikan Library building, which is located at the California Institute of Technology campus in Pasadena, California, and the results are compared with a previous deterministic study.

Structural damage detection based on l1 regularization using natural frequencies and mode shapes


Conventional vibration-based damage detection methods employ the Tikhonov regularization in model updating to deal with the problems of underdeterminacy and measurement noise. However, the Tikhonov regularization technique tends to provide over smooth solutions that the identified damage is distributed to many structural elements. This result does not match the sparsity property of the actual damage scenario, in which structural damage typically occurs at a small number of locations only in comparison with the total elements of the entire structure. In this study, an l1 regularization-based model updating technique is developed by utilizing the sparsity of the structural damage. Both natural frequencies and mode shapes are employed during the model updating. A strategy of selecting the regularization parameter for the l1 regularization problem is also developed. A numerical and an experimental examples are utilized to demonstrate the effectiveness of the proposed damage detection method. The results showed that the proposed l1 regularization-based method is able to locate and quantify the sparse damage correctly over a large number of elements. The effects of the mode number on the damage detection results are also investigated. The advantage of the present l1 regularization over the traditional l2 regularization method in damage detection is also demonstrated.

Effect of hysteretic properties of SMAs on seismic behavior of self-centering concentrically braced frames


Shape memory alloys (SMAs) exhibit nearly ideal superelastic properties when the ambient temperature is above the austenite finish temperature, which enables them to recover deformation and dissipate energy for the seismic-resisting structures. This unique hysteretic properties of SMAs indicate they are very promising in developing self-centering structures. As such, recent studies installed SMAs in concentrically braced frames (CBFs) to form SMA-based self-centering CBFs (SCCBFs) and illustrated that the structures performed excellently with controlled peak drift and eliminated residual drift upon earthquakes. SMAs show variability in the hysteretic parameters due to the difference in metal types, crystallographic structure, component ratios, and heating treatments in producing process. Thus, this necessitates an investigation into the associated effect on the seismic performance of SMA-based SCCBFs. To this end, this study selects 3 SMAs, proposes a bracing form, and installs SMA braces in the CBFs. Prior to the seismic analysis, all 3 frames are designed by an ad hoc design method. The focus of this paper is to understand the effect of hysteretic properties on the seismic behavior of SMA-based SCCBFs. Intensive nonlinear time history analyses are carried out to assess the seismic performance of these structures under frequently occurred earthquakes and design basis earthquakes. The analytical results indicate the properly designed SCCBFs are able to meet prescribed performance targets and display comparable seismic demands, irrespective of the SMA types. This study suggests that using SMAs with greater hysteretic parameters is more favorable, from the perspective of saving material consumption and controlling acceleration demands.

Development of a divergent fluid wall damper for framed structures subjected to dynamic loads


This study developed a new adaptive design for a divergent fluid wall damper (DFWD). This design decreases the dynamic vibration in reinforced concrete (RC) structures subjected to dynamic forces caused by earthquakes, wind, tsunamis, and explosions. The DFWD comprises a tank connected to the lower floor that is filled with a fluid and a plate with fins located inside the tank connected to the upper floor. The DFWD uses a bypass system mechanism that circulates fluid inside the wall damper tank through a divergent pipe and controls the fluid pressure during vibration using a double-acting valve. To evaluate the performance of the DFWD in RC-frame structures, we fabricated and experimentally evaluated a prototype of the device based on a new adjustable design. Two RC frames, a bare frame and a frame with DFWD, were cast with the same geometric specifications. These frames were then examined in terms of the time history of applied displacement with a maximum amplitude of 40 mm under the same conditions. The valves in the design of the DFWD were adjustable, and the fully open valve condition was examined. The results indicated that the failure capacity of the frame was significantly improved compared to that of the bare frame as the DFWD absorbed more dynamic force. The ductility of the RC-frame structure equipped with the DFWD was improved by almost 17.8% compared to that of the bare frame.

Reliability analysis of active tendon-controlled wind turbines by a computationally efficient wavelet-based probability density evolution method


We propose a computationally efficient stochastic framework and an associated mathematical formulation to assess the improvement in the vibration response of wind turbines with active structural controllers. Uncertainties in the turbulent wind speed as well as in the structural parameters are considered in the formulation for analyzing the 2 important (rated and cut-out) wind speed conditions. A multimodal wind turbine model based on a NREL 5-MW wind turbine model is adopted for analysis, and an active tendon controller is used to develop the stochastic framework. Dynamic interaction between the rotor blades and the supporting tower, as well as the coupling induced by the pretwist of the blades, and a collective pitch controller are considered. A time-evolving phase spectrum method together with a phase delay spectrum model is used to simulate the stochastic wind field, which is computationally less expensive. The probability density contours and the extreme value distributions of the blade tip displacements with and without the active controller are obtained by the wavelet-based probability density evolution method, followed by the computation of the corresponding failure probabilities. It is observed that the improvement in reliability and performance of the rotor blades with the controller becomes statistically more effective as the wind speed increases (e.g., significant beneficial effects are noticed from the probability distributions in terms of the spread at the cut-out wind speed).

Effect of horizontal loading direction on performance of prototype square unbonded fibre reinforced elastomeric isolator


Unbonded fibre reinforced elastomeric isolator (U-FREI) is lightweight and facilitates easier installation in comparison to conventional steel reinforced elastomeric isolators. Most of the previous studies were focused to investigate the behaviour of scaled models of square U-FREIs in 0° or 45° horizontal loading directions. However, the angle of incidence of earthquake to a structure may be from any directions. This paper presents influence of different loading directions (0°, 15°, 30°, and 45°) on the horizontal response of a sample prototype square U-FREI on the basis of both experimental investigation and three-dimensional finite element analysis. Mechanical properties and deformed configurations of the prototype U-FREI computed using finite element analyses are observed to be in good agreement with those obtained from experimental study. It is further observed that as the loading direction changes from 0° to 45°, the effective horizontal stiffness of U-FREI increases, whereas the damping value decreases. Thus, the seismic performance of U-FREI will also vary depending on the direction of load acting on them.

Environmental-effects-embedded model updating method considering environmental impacts


In structural health monitoring, one practical challenge is to separate the change of structural characteristics (e.g., natural frequency and mode shape) due to environmental impacts from those induced by actual damage. Generally, data-driven regression models are applied to remove the environmental impacts before model updating takes place. Model selection and training procedures are required in constructing these regression models, which are often subjective, prone to overfitting issue, and human errors. This paper proposes a novel physics-based Environmental-Effects-Embedded model updating method. By embedding physical mechanisms of environmental impacts into the formulation of the finite element model, the proposed method is capable of considering these impacts during the finite element model updating. A comparative numerical study is performed by applying both the Environmental-Effects-Embedded model updating method and traditional method on a pedestrian bridge model subjected to structural damage, temperature variation, and boundary condition change. Comparison between the proposed and traditional methods has demonstrated that the proposed method can offer more accurate results in localizing and quantifying the structural damage under environmental impacts.

Study on self-adjustable tuned mass damper with variable mass


Tuned mass dampers (TMDs) represent a quite mature technology for controlling human-induced vibrations of footbridges, when they are tuned to the primary structure's fundamental frequency. However, the TMD is very sensitive to even a small change in the tuning ratio. This paper proposes a novel TMD named self-adjustable variable mass TMD (SAVM-TMD), which is capable of varying its mass and retuning its frequency on the basis of the acceleration ratio between the primary system and the TMD. The accelerations are obtained from two acceleration sensors, and the frequency adjustment is achieved by using a microcontroller and actuating devices. The acceleration ratio limit value should be set in the microcontroller firstly, and when the adjustment begins, the microcontroller will retune the TMD to a reasonable frequency region, under a specific harmonic excitation. The SAVM-TMD can be regarded as a passive control device capable of adjusting its frequency. The performance of SAVM-TMD is studied via both experimental studies and numerical simulations under different pedestrian excitations. It is found that the SAVM-TMD is effective in reducing the response and improving the equivalent damping ratio of the primary system when the structural frequency changes, with little power consumption. The results obtained from the experimental studies and the numerical simulations agree with each other very well. More pedestrian vibration situations are studied in the numerical simulations, and the results also show that the SAVM-TMD has excellent performance in controlling human-induced vibrations.

Measurement of strains by optical fiber Bragg grating sensors embedded into polymer composite material


This paper presents the experimental results of strain measurements made by the fiber Bragg grating sensors embedded into polymer composite materials (PCMs). A series of performed experiments are described to demonstrate the capability of fiber optic sensors to measure strains in the case of their pronounced gradient distribution within the material, under compression and tension, at cyclic variation of strains with time and at different temperatures. A measuring technique is presented, and the results of strain measurements during the process of preparation of PCM including measurements of residual process-induced strains are discussed.The results of strain measurements made by fiber optic strain sensors (FOSS) are compared with the results of numerical modeling based on the finite element method and independent measurement data obtained with the use of a digital optical system Vic-3D and other experimental devices. The comparison made shows good agreement between the results obtained by the experimental methods and numerical simulation.The results of numerical computations demonstrate that the embedment of optical fibers in a PCM introduces perturbations in the strain distribution pattern in the vicinity of optical fibers but practically does not cause changes in the value of the strain tensor component measured by the FOSS. The conclusions about applicability range of FOSS embedded into PCM were made based upon the numerical simulation. The interrelation model between Bragg wavelength peak shift and the strain of the optical fiber in the fiber Bragg grating area for the sensor that is not affected by the environment is proposed.

Development of a smart-device-based vibration-measurement system: Effectiveness examination and application cases to existing structure


After the 2011 Great East Japan Earthquake, long-term vibration measurement using high-density instruments is one of the most critical issues for structural-health-monitoring owing to increasing deterioration and threat of future large earthquakes. Because of the high initial and running costs of traditional monitoring systems, smart-device-based measurement system is considered as a simple and easy solution. In this paper, the effectiveness of in-built sensor, data transfer via wireless local area network, data acquisition to a synchronize cloud server, and trigger function using shaking table tests were firstly examined. A measurement system including a group of sensors has been established successfully based on the “control center” from which the trigger command can be send to other sensors immediately as any sensor/sensors is/are triggered. Then, the system is applied to seismic-response and environment-vibration measurement at existing structures. Results show that the observable acceleration level of smart devices is more than 5 gal in the frequency range of 0.1 to 10 Hz. The possible sampling rate is 100 Hz. Though it is unstable, correction methods have been proposed. Continuous measurement and data transfer is possible without data loss. Dynamic properties extracted from smart-device-based system is very similar to those extracted from high-quality-sensor-based system.

Mitigation of offshore wind turbine responses under wind and wave loading: Considering soil effects and damage


The present paper studies the mitigation of monopile offshore wind turbines subjected to wind and wave loading. Soil effects (SE) and damage are considered. A semiactive tuned mass damper (STMD) capable of retuning its natural frequency and damping property in real time is utilized to mitigate the nacelle/tower top dynamic response. Based on the Euler–Lagrangian equation, an analytical model of the wind turbine coupled with an STMD is established wherein the interaction between the blades and the tower is modeled. Wind turbulence is generated via mapping a three-dimensional wind field profile onto the rotating blades. Aerodynamic loading is computed using the blade element momentum method where the Prandtl's tip loss factor and the Glauert correction are considered. Wave loading is computed using Morison's equation together with the strip theory. The National Renewable Energy Laboratory monopile 5-MW baseline wind turbine model is employed to examine the performance of the STMD. It is found that the SE and damage presence in the foundation or/and the tower can change the dominant frequency, thereby rendering the conventional TMD detuned and ineffective. In comparison, the STMD retuned in real time by the proposed algorithm can mitigate the nacelle/tower and foundation response more effectively with a smaller stroke. Results indicate that the STMD has significant effectiveness improvement over the TMD when the SE and/or damage are considered.

The MIT Green Building benchmark problem for structural health monitoring of tall buildings


This paper presents a benchmark problem for the structural health monitoring community to study tall buildings. The benchmark building is called the Green Building located at the Massachusetts Institute of Technology campus, with 21 stories above the ground (83.7 m) and a basement (3.8 m) connecting to the Massachusetts Institute of Technology tunnel system. This building was constructed as cast-in-place reinforced concrete and instrumented with 36 accelerometers to measure the building translational, torsional and vertical responses. The benchmark problem includes the detailed description of this building, 7 field measurement data sets (4 ambient data sets, 1 data set under an unidentified event, 1 data set under the excitation of fireworks, and 1 earthquake data set), and finite element models (both full-scale and condensed models). The Green Building has an identifiable soil-structure interaction behavior and the base rocking movement brings significant components into the building response. To decouple the rocking effect, storey measurement condensation and rocking response determination are discussed in this paper. A blind source separation approach is finally applied to identify the modal characteristics and quantify the rocking components. The benchmark data and models are open to the public for algorithmic development and validation.

Characterization of stationary and walking people on vertical dynamic properties of a lively lightweight bridge


This paper investigates the effect of both stationary and walking people on vertical dynamic characteristics of structures based on an experimental program. A lively lightweight bridge was designed and constructed for the experiments. Dynamic properties of the bridge are obtained based on ambient vibration testing method. Stationary tests of straight knees and bent knees postures under different crowd sizes were performed using heel-impact method. Synchronized walking tests were conducted considering walking frequencies ranging from 1.6 to 2.4 Hz and different group sizes of the participants. Random walking activities were also performed. Results of stationary people tests show a decrease in natural frequency and an increase in damping ratio of the occupied structure with respect to the empty structure as number of people increases, for both straight knees and bent knees postures. However, the structural damping tends to be “stable” (or “saturated”) when number of occupants exceeds a critical value. Theoretical modeling of standing people–structure interaction system reflects similar trend. Results of walking tests also show a decrease in natural frequency and an increase in damping ratio of the structure. Comparison of all test data implies that structural properties, structural weight, load frequency, and crowd size all contribute to structural responses, among which load frequency plays a decisive role. Furthermore, both higher harmonics of walking load and higher vibration modes may contribute remarkably to total structural response for lightweight structures.

A novel time reversal sub-group imaging method with noise suppression for damage detection of plate-like structures


In this paper, a new time reversal imaging (TRI) algorithm with noise suppression is developed for the application of imaged based structural damage detection of plate-like structures. The conventional TRI method suffers from performance degradation in high noise condition. The proposed method addresses the aforementioned issues. First, an array of detection transducers is used and is divided into several subgroups. Then, the echo signals of the subgroups are time reversed and reemitted via numerical computation. Finally, the cross-correlation functions of the summation of refocused time reversed signals in each subgroup are obtained to locate damages. The time reversed signals at the reference time are irrelevant to the noise, meanwhile, the multiple refocused signals in each subgroup are first added and then cross-correlated. Therefore, the proposed method can effectively suppress noise. To validate the effectiveness of proposed method, 2 experiments were performed. The 2 experiments involved 2 aluminum plate specimens. Each specimen was equipped with 4 surface-bonded lead zirconate titanate transducers. One specimen involved a simulated damage (an addition of a mass), and the other one involved an actual through-hole damage. The experimental performances of the proposed method are compared to those of the conventional TRI method. The imaging results demonstrated that the damage on both specimens was clearly displayed with high spatial resolution by the proposed method even under the low signal-to-noise ratio condition. On the contrary, the location of the damage computed by the conventional TRI method was submerged in noise and cannot be distinguished.

Visual–inertial displacement sensing using data fusion of vision-based displacement with acceleration


In recognition of the importance of the displacement associated with assessing structural condition, many displacement measurement methods have been proposed to date. With advances in optics and electronics, displacement measurement relying on computer-vision techniques to convert pixel movement into structural displacement has drawn much attention recently, thanks to its simplicity in installation and relatively inexpensive cost. Despite numerous advantages, 2 major obstacles that prohibit the use of vision-based method are (a) resolution, which is a function of distance between the camera and the structure, and (b) limited frame rate, which both lower dynamic displacement-capturing capability. In this paper, to enhance the quality of vision-based displacement measurement, data fusion with acceleration measurement is proposed to improve the dynamic range of displacements while lowering signal noise. To achieve fusion between vision-based displacement and acceleration, complementary filters and a time synchronization method between 2 different sources were proposed. The proposed methods were verified through numerical analysis and an experimental test, the results of which showed the validity of proposed data fusion.

Shaking table test of a four-tower high-rise connected with an isolated sky corridor


A 4-tower high-rise building connected with an isolated sky corridor on the top is designed in the seismic region of China. The 300-meter long sky-corridor bridges the four 230-m-high towers at the top floor. The seismic design of the building is challenging due to the structural complexity. Passive control strategy is employed to reduce earthquake responses and member forces of the towers and the sky corridor. Connections between the towers and the sky corridor are designed as flexible links. Curved surface sliders (CSSs) and viscous dampers (VDs) are installed at the connection joints. The characteristics of the seismic isolation system should remain unchanged during the service life, and the CSSs shall be protected strictly from humidity and dust. To study the seismic performance of the 4-tower connected structure, a 1/25 scale model is tested by shaking table tests subject to minor, moderate, and major earthquake. According to the Chinese code, peak ground accelerations subject to the 3 levels are specified as 0.025, 0.07, and 0.175 g. Eight earthquake records with different frequency spectrum properties were selected to test the model structure. Detailed dynamic similitude design of towers, CSSs, and VDs are described. The maximum acceleration and deformation responses of the towers and the sky corridor are measured, as well as the seismic performance of the CSSs and VDs, the dynamic characteristics, and the cracking pattern of the building. Results show that no serious damage occurs on the 4-tower connected structure. The protective system that consists of the CSSs and VDs reduces the seismic responses of the sky corridor. The sky corridor keep in elastic state under the high-intensity earthquake.

Posterior uncertainty, asymptotic law and Cramér-Rao bound


In a globally identifiable Bayesian system identification problem, the uncertainty of model parameters can be quantified by their “posterior covariance matrix” calculated for a particular data set. When the data is modeled to be distributed as the likelihood function (i.e., no modeling error), a statistical law analogous to the law of large numbers results, where the posterior covariance matrix is asymptotic to a deterministic quantity that depends on the “information content” of data rather than its particular (stochastic) details. This was referred as the “uncertainty law” in a recent study of the achievable precision of modal parameters in operational modal analysis (OMA). Deriving the uncertainty law involves asymptotics techniques and leveraging on the mathematical structure of the likelihood function, which was found to be tedious. As a sequel to the development, this work shows that for long data and up to a Gaussian approximation of the posterior distribution, the uncertainty law is asymptotic to the inverse of the Fisher information matrix, which coincides with the tightest Cramér-Rao bound in classical statistics. A parametric study is presented to illustrate the theoretical results in the context of OMA. As a direct application with practical relevance, the relationship provides a systematic means for deriving the uncertainty laws in OMA. Applied and interpreted properly, the posterior covariance matrix (for given data), uncertainty law, and Cramér-Rao bound can provide a powerful means for quantifying and managing the uncertainties in structural health monitoring.

Real-time hybrid testing of a structure with a piezoelectric friction controllable mass damper by using a shake table


A structure with semi-active control devices is usually a highly nonlinear system. To investigate the aseismic performance of such a system, real-time hybrid testing (RTHT) can be a cost-effective experimental method. However, a substructure with a semi-active friction device is difficult to be tested by the RTHT, because the dynamic behavior of a friction device, which consists of sliding and sticking phases, is determined by the exerted force of the primary structure, rather than its displacement response. To overcome this problem, a methodology of RTHT with a shake table (RTHT-ST) is utilized in this study. In the RTHT-ST, which is an experimental technique combining shaking table test and RTHT, the shake table is employed to mimic the acceleration response of the primary structure that is simulated by a numerical model and imposed to the substructure, which is mounted on the shake table. In order to verify the feasibility of the experimental method, a semi-active piezoelectric friction controllable mass damper substructure is tested by using the RTHT-ST. The test results of the RTHT-ST are compared with those of a full shaking table test, in which the integrated primary structure and piezoelectric friction controllable mass damper system have been physically tested. Moreover, to evaluate the accuracy of the RTHT-ST result, one category of indicators called root-mean-square energy error index is also proposed. Unlike previously existing hybrid-testing indices, the root-mean-square energy error index is able to distinguish modeling error from control system error.

Deflection distribution estimation of tied-arch bridges using long-gauge strain measurements


Deflection, as a critical indicator for structural performance evaluation, is difficult to be measured accurately for long-span bridges, though various deformation sensors and devices have been developed. In this paper, a new scheme using long-gauge fiber optic sensors for estimating the deflection distribution of tied-arch bridges is proposed. First, the complex strain state of the tied-arch bridge is investigated, in which a cubic function describing the axial strain distribution of the tie beam is obtained. Second, the bending strain is separated from the measured long-gauge strain which is a combination of axial and bending components by a sensor layout scheme. Finally, the separated bending strain is utilized to estimate the deflection distribution of the tied-arch bridge through an improved conjugate beam method. Numerical and experimental examples are studied to illustrate the effectiveness of the proposed method for deflection estimation of tied-arch bridges in static and dynamic loading cases.

Detection of structural faults in piers of masonry arch bridges through automated processing of laser scanning data


This paper introduces a new methodology for the automated processing of large point clouds for the diagnosis of structural pathologies in piers of masonry arch bridges. This method starts with the automatic segmentation of the global point cloud of the entire bridge in its different structural elements (piers, arches, spandrel walls, etc.). Later, piers were further segmented in order to be able to detect and quantify structural pathologies. Particularly, faults are based in geometric anomalies (tilts and skews) of the pier walls that might be indicators of stability problems of the entire bridge. The methodology was validated using several samples of representative masonry arch bridges. The obtained results demonstrate that this method can provide useful information about the structural health of the bridge requiring neither training in the technology nor advanced knowledge in the processing of laser scanning data.