23 research outputs found

    Modal identification of bridge systems using state-space methods

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    Arrays of large numbers of sensors and accompanying complex system identification (SI) methods have been recently used in engineering applications on structures ranging from complex real space trusses to simple experimental beams. However, practical application to strong motion data recorded on large civil engineering systems is limited. In this study, state-space identification methods are used for modal identification from earthquake records with further investigation into the effectiveness of the methods from the viewpoint of sensor layout configuration. The study presented in this paper adopts a deterministic approach, which is complemented with statistical evaluation in another paper. The used SI methods include eigen realization, system realization with information matrix and subspace methods. The application of the methods on instrumented bridge systems in California is included and the performance of these methods is compared in terms of success and feasibility. Subsequently, viability of the methods on arrays of different numbers of sensors on the bridge systems is investigated. This is motivated by the fact that sensor arrays with wireless communication may be conveniently installed on civil engineering structures in the future. Computational costs and limits of applicability are examined using simulated ground motion analysis with detailed finite element models for a bridge system after validation using recorded data from real ground shaking. Moreover, the effect of the configuration of the sensor arrays is considered, accounting for different noise levels in the data to reflect more realistic situations. Copyright 0 (c) 2005 John Wiley & Sons, Ltd

    System identification of instrumented bridge systems

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    Several recorded motions for seven bridge systems in California during recent earthquakes were analysed using parametric and non-parametric system identification (SI) methods. The bridges were selected considering the availability of an adequate array of accelerometers and accounting for different structural systems, materials, geometry and soil types. The results of the application of SI methods included identification of modal frequencies and damping ratios. Excellent fits of the recorded motion in the time domain were obtained using parametric methods. The multi-input/single-output SI method was a suitable approach considering the instrumentation layout for these bridges. Use of the constructed linear filters for prediction purposes was also demonstrated for three bridge systems. Reasonable prediction results were obtained considering the various limitations of the procedure. Finally, the study was concluded by identifying the change of the modal frequencies and damping of a particular bridge system in time using recursive filters. Copyright (C) 2003 John Wiley Sons, Ltd

    Modal analysis of a densely instrumented building using strong motion data

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    A densely instrumented residential building was tested using seismic simulator (shake table) for a series of strong events. These events included several runs of 200% Izmit Turkey earthquake 1999, which caused over 20,000 casualties. The building was brought to near failure condition through these experiments sequentially. The instrumentation on the system consisted of commonly used piezoresistive and wireless micro-electromechanical systems (MEMS) accelerometers along with conventional strain and displacement measurements. Part, of the ground story was heavily damaged due to these experiments. System identification studies using multiple-input/multiple-output procedure were performed to obtain modal properties of the building. The change of the modal properties of the system was monitored and documented. The obtained natural frequencies and modes were compared with results from shaker tests. The statistical proper-ties of the estimated modal proper-ties were determined using Monte Carlo, simulations. Comparison of conventional piezoresistive accelerometers and new wireless MEMS sensors is also given in the paper for the purpose of future extensions of the presented study

    Statistical significance of modal parameters of bridge systems identified from strong motion data

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    Modal parameters of structural systems have commonly been determined using system identification (SI) methods for damage detection and health monitoring. For determining the deterioration of the integrity of structural systems correctly, modal parameters of a healthy structure have to be obtained with adequate certainty so that these parameters can be used as reliable references for the healthy system to compare with those of the damaged system. In this study, the statistical significance of modal parameters identified using strong motion time histories recorded on two bridge structures is assessed. The confidence intervals of identified modal frequencies and damping ratios are obtained using Monte Carlo simulations and sensitivity analyses in conjunction with eigenrealization algorithm. The dependence of the statistical bounds on model parameters is examined. The effect of using different number of sensors on the statistical significance is evaluated using simulated time history data from a validated finite element model of a bridge. Copyright (c) 2005 John Wiley & Sons, Ltd
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