Showing papers in "Structural Control & Health Monitoring in 2018"

Optimal tuned mass‐damper‐inerter (TMDI) design for seismically excited MDOF structures with model uncertainties based on reliability criteria

Abstract: The tuned mass-damper-inerter (TMDI) is a recently proposed linear passive dynamic vibration absorber for the seismic protection of buildings. It couples the classical tuned mass damper (TMD) with an inerter, a two-terminal device resisting the relative acceleration of its terminals, in judicial topologies, achieving mass-amplification and higher-modes-damping effects compared to the TMD. This paper considers an optimum TMDI design framework accommodating the above effects while accounting for parametric uncertainty to the host structure properties, modeled as a linear multi degree of freedom system, and to the seismic excitation, modeled as stationary colored noise. The inerter device constant, acting as a TMD mass amplifier, is treated as a design variable, whereas performance variables sensitive to high-frequency structural response dynamics are used to account for the TMDI influence to the higher structural modes. Reliability criteria are adopted for quantifying the structural performance, expressed through the probability of occurrence of different failure modes related to the trespassing of acceptable thresholds for the adopted performance variables: floor accelerations, interstory drifts, and attached mass displacement. The design objective function is taken as a linear combination of these probabilities following current performance-based seismic design trends. Analytical and simulation-based tools are adopted for the efficient estimation of the underlying stochastic integral defining the structural performance under uncertainty. A 10-story building under stationary Kanai-Tajimi stochastic excitation is considered to illustrate the design framework for various TMDI topologies and attached mass values. It is shown that the TMDI achieves enhanced structural performance and robustness to building and excitation uncertainties compared to same mass/weight TMDs.

Particle impact dampers: Past, present, and future

Abstract: Particle damping, an effective passive vibration control technology, is developing dramatically at the present stage, especially in the aerospace and machinery fields. The aim of this paper is to provide an overview of particle damping technology, beginning with its basic concept, developmental history, and research status all over the world. Furthermore, various interpretations of the underlying damping mechanism are introduced and discussed in detail. The theoretical analysis and numerical simulation, together with their pros and cons are systematically expounded, in which a discrete element method of simulating a multi-degree-of-freedom structure with a particle damper system is illustrated. Moreover, on the basis of previous studies, a simplified method to analyze the complicated nonlinear particle damping is proposed, in which all particles are modeled as a single mass, thereby simplifying its use by practicing engineers. In order to broaden the applicability of particle dampers, it is necessary to implement the coupled algorithm of finite element method and discrete element method. In addition, the characteristics of experimental studies on particle damping are also summarized. Finally, the application of particle damping technology in the aerospace field, machinery field, lifeline engineering, and civil engineering is reviewed at length. As a new trend in structural vibration control, the application of particle damping in civil engineering is just at the beginning. The advantages and potential applications are demonstrated, whereas the difficulties and deficiencies in the present studies are also discussed. The paper concludes by suggesting future developments involving semi-active approaches that can enhance the effectiveness of particle dampers when used in conjunction with structures subjected to nonstationary excitation, such as earthquakes and similar nonstationary random excitations.

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

Abstract: 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 e.g. at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multi-point 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 cm induced, in this application, by pedestrian passing. The measured data enables 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.

Demand-based optimal design of oscillator with parallel-layout viscous inerter damper

Abstract: Summary In this study, a demand-based optimal design method is proposed for an oscillator (a single-degree-of-freedom system) with a parallel-layout viscous inerter damper (PVID) The proposed design method overcomes some deficiencies of the existing method, which is based on the fixed-point theory and is mainly suitable for tuned mass dampers Moreover, for the fixed-point method, the inherent damping of the primary structure is neglected, and the global optimal solution cannot be obtained The proposed method can obtain a more rational and practical design for the actual design by minimizing both the response and the cost The design problem of a PVID-equipped oscillator is transformed into a multi-objective optimization problem that can be solved using the e-constraint approach, which is consistent with the concept of demand-based design The dynamic response of the oscillator and the force of the PVID (ie, the cost factor) are evaluated according to theories of random vibration to reduce the number of calculations required A computer program is developed to perform demand-based parametric design of a PVID-equipped oscillator Several design cases were examined under different excitation conditions using the computer program, and dynamic time history analyses were then conducted to verify the designs obtained The results show that the proposed optimal design method identifies satisfactory designs more effectively than the existing method by obtaining PVID design parameter values that better meet the performance demand and simultaneously minimize the cost

Identification framework for cracks on a steel structure surface by a restricted Boltzmann machines algorithm based on consumer-grade camera images

Abstract: Summary This paper proposes an identification framework based on a restricted Boltzmann machine (RBM) for crack identification and extraction from images containing cracks and complicated background inside steel box girders of bridges. The original images that include fatigue crack and other background information are obtained by a consumer-grade camera inside the steel box girder. The original images are cut into a number of elements with small size as the input dataset, and a state representation vector is artificially labeled to every image element used for the crack identification. A deep learning model or network consisting of multiple processing RBM layers to learn the abstract features is constructed to match the input image elements with corresponding state representation vectors. Next, a three-layer RBM with 500; 500; and 2,000 hidden units is trained as the hidden layers in the deep learning network. A contrastive divergence learning algorithm is employed for training the deep network to update and obtain the optimal parameters (i.e., the biases and weights). The new input image elements labeled as crack are sorted out and assembled to form an output image. A deep network is modeled through the consumer-grade camera images containing cracks and complicated background information using the proposed approach. The accuracy and ability to identify cracks from new images with different resolutions using the trained deep network are validated. Furthermore, effects of element size on reconstruction error and identification accuracy are investigated. The results show that there exists optimal element size; that is, too small and too large element sizes both increase the reconstruction error and decrease the identification accuracy.

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

Abstract: Summary 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.

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

Abstract: 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.

A novel model of dam displacement based on panel data

Abstract: Deformation monitoring is the main program in the area of dam safety. Because statistical model is simple and intuitive, it is widely used in dam safety monitoring. However, in dam's displacement statistic model, there is a high degree of linear relationship between influence factors. Due to the influence of multicollinearity, models calculated with traditional methods are not accurate and stable. Besides, because of dam integrity, each part of dam is interrelated and interactive. Currently, single point or multipoints displacement monitoring models cannot accurately reflect the actual dam running state. In this paper, the theory of panel data is introduced to dam deformation analysis. Panel data contain time series data and cross section data, which is able to solve serious multicollinearity problem of traditional regression method. Moreover, all measuring points are classified into several groups according to their similar deformation law. Based on the random-coefficient model of panel data, potential relationship between different measuring points is built. Take 1 hydropower station, for example, to examine that random-coefficient model is able to improve the modeling situation that estimators are not significant and simultaneously provide a stable model, which explores a new approach for the research of dam displacement monitoring.

Sensing dynamic displacements in masonry rail bridges using 2D digital image correlation

Abstract: Dynamic displacement measurements provide useful information for the assessment of masonry rail bridges, which constitute a significant part of the bridge stock in the United Kingdom and Europe. Commercial 2D digital image correlation (DIC) techniques are well suited for this purpose. These systems provide precise noncontact displacement measurements simultaneously at many locations of the bridge with an easily configured camera set-up. However, various sources of errors can affect the resolution, repeatability, and accuracy of DIC field measurements. Typically, these errors are application specific and are not automatically corrected by commercial software. To address this limitation, this paper presents a survey of relevant DIC errors and discusses methods to minimise the influence of these errors during equipment set-up and data processing. A case study application of DIC for multipoint displacement measurement of a masonry viaduct in Leeds is then described, where potential errors due to lighting changes, image texture, and camera movements are minimised with an appropriate set-up. Pixel-metric scaling errors are kept to a minimum with the use of a calibration method, which utilises vanishing points in the image. However, comparisons of DIC relative displacement measurements to complementary strain measurements from the bridge demonstrate that other errors may have significant influence on the DIC measurement accuracy. Therefore, the influence of measurement errors due to lens radial distortion and out-of-plane movements is quantified theoretically with pinhole camera and division distortion models. A method to correct for errors due to potential out-of-plane movements is then proposed.

Initial service life data towards structural health monitoring of a concrete arch dam

Abstract: Summary This paper presents a statistical framework to monitor the performance of an operational concrete arch dam using sensory data acquired during its initial service life One of the major challenges in dealing with a newly constructed dam is to predict its long-term behaviour by forecasting appropriate thresholds using limited data exhibiting nonstationarity In this paper, a hybrid model is implemented to predict dam responses using environmental—hydrostatic, seasonal, and temperature—as well as age-related variables The data from multiple sensors are first analyzed using principal component analysis to incorporate overall dam behaviour into a prediction model The proposed prediction framework is then employed to estimate the residuals and control limits required to calculate thresholds under nonstationary operating conditions during its initial service life The dam performance is then monitored using statistical control charts and anomalies are detected by comparing the test statistics, square prediction error, and Hotelling T-squared, calculated from the residuals with the preset control limits The issue of limited data is addressed by updating the model parameters and thresholds periodically, which is aimed at minimizing the false alarm rate The proposed method is demonstrated using a 130-m-high double-arch concrete dam located in Bulgaria

Monitoring the behavior of segment joints in a shield tunnel using distributed fiber optic sensors

Abstract: Summary Shield tunneling is a popular tunnel construction technique for its efficiency and speed. However, uncertainties associated with site soil conditions, past loading histories and analytical modeling, can result in performance issues. To monitor shield tunnels and ensure performance and safety, fiber optic sensing technique is proposed. Based on Brillouin optical frequency domain analysis, the technique can monitor the opening and closing of segmental joints in shield tunnels with high sensitivity. To determine tunnel lining segment displacement, different fixed-point spacings have been tested in the lab. The test results show that the difference in fixed-point distances had no impact on the test accuracy and the sensing cable with 0.9-mm polyurethane sheath coater has the best performance. For demonstration, the Brillouin optical frequency domain analysis-based monitoring technique is applied to the Suzhou Metro Line 1 tunnel for tunnel lining segment joint monitoring. The technique detected minor deformation of the segment joints in tunnels in operation and located leakages within the tunnel. The technique further identified that the minor deformations of the segment joints and track bed expansion were closely associated with temperature variations.

Experimental and finite element investigation of temperature distributions in concrete-encased steel girders

Abstract: Summary The structural performance of bridge structures is temporal and is mainly controlled by the types of the applied loads To continuously observe the structural performance of bridges, structural health monitoring sensors that include among many temperature sensors are used The impact of nonuniform temperature distributions in bridge girders due to the environment thermal loads has been recognized by former researchers and bridge design codes To evaluate these and other effects on the structural behavior of bridge structures, many field and experimental structural health monitoring studies were carried out However, more researches are required to investigate the temperature distributions in other girder configurations This work is directed to investigate the impact of air temperature and solar radiation on temperature gradient distributions in concrete-encased composite girders For this purpose, an experimental concrete-encased steel girder segment was instrumented with thermocouples and other sensors The experimental data recording continued for 6 months during the hot and cold seasons Furthermore, a thermal finite element (FE) parametric study was conducted to investigate the effect of the girder size The test results showed that the vertical and lateral temperature gradient distributions and the variation of the temperature gradients with time are controlled by the amount and location of the received solar radiations The FE analysis showed that the daily temperature variations are higher in smaller girders, whereas the temperature gradients are smaller than in larger girders Moreover, the FE results showed that the thickness of the girder's concrete members has an important impact on temperature gradients and temperature distributions

Energy regenerative tuned mass dampers in high‐rise buildings

Abstract: Summary This study investigates a novel energy regenerative tuned mass damper (TMD) with dual functions—vibration control and energy harvesting—in a high-rise building. The energy regenerative TMD consists of a pendulum-type TMD, an electromagnetic damper, and an energy-harvesting circuit. A simple optimal design method for energy regenerative TMD is proposed, in which a fixed duty-cycle buck-boost converter is employed as the energy-harvesting circuit to optimize the energy-harvesting efficiency and damping coefficient of the TMD. This study is organized into two main tasks: (a) characterizing and modeling the energy regenerative TMD through laboratory testing of a scaled prototype and (b) evaluating the vibration control and energy-harvesting performance of the energy regenerative TMD when applied in a 76-story wind-excited benchmark building in consideration of the nonlinearities in the energy regenerative TMD. The simulations reveal that the harvested electric power averages from hundreds of watts to kilowatts level when the mean wind speed ranges 8–25 m/s. Meanwhile, the building vibration is mitigated with the control performance comparable to the optimally designed passive TMD in a wide range of wind speed. The results in this study clearly demonstrate the effectiveness of the dual-function energy regenerative TMD when applied to building structures.

Study on self-adjustable tuned mass damper with variable mass

Abstract: Summary 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.