924 publications from this institution
This paper presents a technique for offline time synchronization of data acquisition systems for linear structures with proportional damping.The technique can be applied when direct synchronization of data acquisition systems is impossible or not sufficiently accurate, for example when multiple measurement nodes with different clock signals are embedded in a health monitoring network.The synchronization is based on the acquired dynamic response of the structure only, and does not require the acquisition of a shared sensor signal or a trigger signal.The time delay is identified from the spurious phase shift of the mode shape components that are obtained from system identification.A demonstration for a laboratory experiment on a cantilever steel beam shows that the proposed methodology can be used for accurate time synchronization, resulting in a significant improvement of the accuracy of the identified mode shapes.
No abstract is provided for this article.
Vibration-based structural health monitoring (SHM) for long-span bridges has become a dominant research topic in recent years. The Nam O Railway Bridge is a large-scale steel truss bridge located on the unique main rail track from the north to the south of Vietnam. An extensive vibration measurement campaign and model updating are extremely necessary to build a reliable model for health condition assessment and operational safety management of the bridge. The experimental measurements are carried out under ambient vibrations using piezoelectric sensors, and a finite element (FE) model is created in MATLAB to represent the physical behavior of the structure. By model updating, the discrepancies between the experimental and the numerical results are minimized. For the success of the model updating, the efficiency of the optimization algorithm is essential. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are employed to update the unknown model parameters. The result shows that PSO not only provides a better accuracy between the numerical model and measurements, but also reduces the computational cost compared to GA. This study focuses on the stiffness conditions of typical joints of truss structures. According to the results, the assumption of semi-rigid joints (using rotational springs) can most accurately represent the dynamic characteristics of the truss bridge considered.
Abstract A major contribution to the status of vibration monitoring has been delivered by the European Brite EuRam research project BE‐3157, System Identification to Monitor Civil Engineering Structures (SIMCES). This paper gives a brief description of the project, the tests performed on bridge Z24 and the results obtained from these tests. The need for further research is indicated. Copyright © 2003 John Wiley & Sons, Ltd.
Tubular structural elements with diameters in the range from 200 mm to 1400 mm are widely used in onshore and off-shore constructions. Typical examples include (drilling) platforms, bridges, and pipelines. In most cases several tubular elements (made of steel) are combined by means of weld joints. The current welding procedures for high strength steel are very time-consuming and thus constitute an important part of the total construction cost. In some applications, the need is inherent for pipes being frequently coupled and uncoupled as in the case of drill pipes and tension-leg platforms. Therefore, the application of threaded connections is considered as a valuable alternative and their design as an important challenge, especially the proof of sufficient fatigue strength. In the case of drill strings, fatigue failure is caused by cyclic load during drilling operations. In other applications, dynamic loads can be caused by environmental and operational conditions, e.g. wind, waves, vortex induced vibrations, internal pressure changes, etc. In this context, fatigue damage identification at an early stage plays an important role on the integrity of the structure. The present work aims at assessing progressive damage in threaded connections subjected to cyclically varying loads by means of vibration measurements. For this purpose, a four-point bending fatigue test with standard connection has been setup [1, 2] and a damage assessment approach has been developed based on dynamic system identification. As damage in a threaded connector is a local phenomenon, which may not significantly influence the lower frequencies or the global response, it is essential to gather accurate information about natural frequencies and mode shapes of many vibration modes [3]. The progressing damage will be compared with the forward predictions of a physical model that is able to predict the stiffness degradation as a function of an arbitrary, but known, load history [4].
The general equilibrium equations describing the dynamic response of a porous saturated medium form a system of coupled hyperbolic partial differential equations. Restricting to two-dimensional plane strain wave propagation, an analytical solution for the dilatational and shear wave contributions to the displacement vectors can be found by a transformation of the generalized coordinates (x, z, t) to (k x, z, ω). A spectrally formulated element uses these frequency and horizontal wave number dependent eigenvectors as shape functions in a displacement formulation. The mass distribution is treated exactly without the need to subdivide an element into smaller elements and therefore, wave propagation is treated exactly. Saturated throw-off and layer elements are developed and enable—together with the dry elements as proposed by Rizzi and Doyle—the study of the harmonic and transient response of horizontally layered saturated and dry porous media. The benefits of the solution method are demonstrated by a numerical example.
In this paper, two stochastic system identification methods are compared. Stochastic means that the method has to cope with output-only data (stochastic, unknown input). The first method is a stochastic subspace algorithm that finds the system matrices of a stochastic state space model. It is a linear method but said to be suboptimal: it is not based on the minimization of a criterion. The second method is a prediction error method that finds the parameters of a multivariable ARMA-model in a nonlinear, iterative way. Both methods are discussed and applied to experimental data from a dynamic test on a concrete beam. The uncertainties of the estimated modal parameters are compared. The determination of these uncertainties is very relevant for structural monitoring based on dynamic measurements. In this way, changes of the dynamic characteristics due to structural modifications (e.g. damage) can be separated from random changes which fall within the uncertainties of the estimated modal parameters.
No abstract is provided for this article.
Modal tests on large structures are often performed in multiple setups for practical reasons. Several sensors are kept fixed as reference sensors over all setups, while the other, so called roving sensors, are moved from one setup to another. This paper develops an optimal sensor placement strategy for multi-setup modal identification, which simultaneously optimizes the locations of the reference sensors and roving sensors. As an optimality criterion, the Information Entropy is adopted, which is a scalar measure of uncertainty in the Bayesian framework. The focus in the application goes to repetitive structures where modes typically occur in clusters, with closely spaced natural frequencies and similar wavelengths. The proposed strategy is illustrated for selecting optimal positions of uni-axial sensors for a repetitive frame structure. The influence of the number of reference sensors and two strategies for positioning roving sensors, i.e. a cluster and a uniform distribution of roving sensors, are investigated. The number of reference sensors is found to be preferably equal to or larger than the number of modes to be identified. In this case, the information content, as quantified by the Information Entropy, is not very sensitive to the roving sensor strategy. If less reference sensors are used, it is highly preferred to distribute the roving sensors uniformly over the structure instead of clustering them. The proposed strategy has been validated by an experimental modal test on a floor of an office building of KU Leuven, which has a nearly repetitive structural layout. The results show how optimally locating sensors allows extracting more information from the data. Though the focus is on applications involving repetitive structures, the proposed strategy can be applied to multi-setup modal identification of any large structure.
No abstract is provided for this article.
No abstract is provided for this article.
<p>Multi-setup operational modal testing has been performed on a multi-span viaduct in Bruges, Belgium. The viaduct consists of two curved integral bridges with a length of about 800 m in parallel with each other. Each bridge has 23 spans and consists of nearly periodic parts. During the measurement, a number of reference sensors is kept fixed, while the other so-called roving sensors are moved in different setups. Modal identification is first carried out for each setup separately. Next, the identified modal data of different setups are merged. It is observed from the stabilization diagrams that the modes are very closely spaced, resulting in a very high modal density, even under 2 Hz. This results in challenges in the modal identification. First, a high model order needs to be considered, leading to a high computational cost. Second, it is difficult to match the partial mode shapes obtained from different setups, due to the closely spaced natural frequencies. This problem is resolved by comparing both the natural frequencies and the mode shapes at the reference locations in the mode matching.</p>
No abstract is provided for this article.
No abstract is provided for this article.
This paper presents the detailed experimental results of 23 full-scale rectangular and I-shaped prestressed and reinforced concrete beams. All beams were designed to fail in shear and were subjected to a four-point bending test with monotonically increasing load until failure. The main investigated parameters were the amount of prestressing, the amount of longitudinal and shear reinforcement ratio and the shear span-to-effective depth ratio respectively. An extensive set of displacement and deformation data were gathered during the experiments using both traditional mechanical measurement devices and advanced optical(-numerical) measurement techniques. The experimentally measured failure loads are compared to analytical predictions obtained from current Eurocode 2 shear design equations. In general, a poor correlation was found between the reported experimental results and analytical predictions (mean experimental to predicted failure load ratio equal to 1.77; coefficient of variation equal to 31.6%). Based on the measured deformation fields, it was observed that, in the case of rectangular beams and prestressed I-shaped beams with shear reinforcement, the applied load is primarily carried by means of a direct compression strut which significantly increased the failure load.
