Home About us Contact
|
Home About us Contact | ||
|
|
||
Modal Parameters (modal + parameter)
Selected AbstractsA Wavelet-Based Approach to Identifying Structural Modal Parameters from Seismic Response and Free Vibration DataCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 6 2005C. S. Huang The wavelet transform with orthonormal wavelets is applied to the measured acceleration responses of a structural system, and to reconstruct the discrete equations of motion in various wavelet subspaces. The accuracy of this procedure is numerically confirmed; the effects of mother wavelet functions and noise on the ability to accurately estimate the dynamic characteristics are also investigated. The feasibility of the present procedure to elucidate real structures is demonstrated through processing the measured responses of steel frames in shaking table tests and the free vibration responses of a five-span arch bridge with a total length of 440 m. [source] Long-Term Monitoring and Identification of Bridge Structural ParametersCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 2 2009Serdar Soyoz This three-span 111-m long bridge is instrumented with 13 acceleration sensors at both the superstructure and the columns. The sensor data are transmitted to a server computer wirelessly. Modal parameters of the bridge, that is, the frequencies and the modal shapes were identified by processing 1,707 vibration data sets collected under traffic excitations, based on which the bridge structural parameters, stiffness and mass, and the soil spring values were identified by employing the neural network technique. The identified superstructure stiffness at the beginning of the monitoring was 97% of the stiffness value based on the design drawings. In the identified modal frequencies, a variation from ,10% to +10% was observed over the monitoring period. In the identified stiffness values of the bridge superstructure, a variation from ,3% to +3% was observed over the monitoring period. Based on the statistical analysis of the collected data for each year, 5% decrease in the first modal frequency and 2% decrease in the superstructure stiffness were observed over the 5-year monitoring period. Probability density functions were obtained for stiffness values each year. Stiffness threshold values for the collapse of the bridge under the operational loading can be determined. Then the number of years can be assessed for which the area under the proposed probability density functions is greater than the threshold value. So the information obtained in this study is valuable for studying aging and long-term performance assessment of similar bridges. [source] Identification of Time-Variant Modal Parameters Using Time-Varying Autoregressive with Exogenous Input and Low-Order Polynomial FunctionCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 7 2009C. S. Huang By developing the equivalent relations between the equation of motion of a time-varying structural system and the TVARX model, this work proves that instantaneous modal parameters of a time-varying system can be directly estimated from the TVARX model coefficients established from displacement responses. A moving least-squares technique incorporating polynomial basis functions is adopted to approximate the coefficient functions of the TVARX model. The coefficient functions of the TVARX model are represented by polynomials having time-dependent coefficients, instead of constant coefficients as in traditional basis function expansion approaches, so that only low orders of polynomial basis functions are needed. Numerical studies are carried out to investigate the effects of parameters in the proposed approach on accurately determining instantaneous modal parameters. Numerical analyses also demonstrate that the proposed approach is superior to some published techniques (i.e., recursive technique with a forgetting factor, traditional basis function expansion approach, and weighted basis function expansion approach) in accurately estimating instantaneous modal parameters of a structure. Finally, the proposed approach is applied to process measured data for a frame specimen subjected to a series of base excitations in shaking table tests. The specimen was damaged during testing. The identified instantaneous modal parameters are consistent with observed physical phenomena. [source] Uncertainty and Sensitivity Analysis of Damage Identification Results Obtained Using Finite Element Model UpdatingCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2009Babak Moaveni The shake table tests were designed so as to damage the building progressively through several historical seismic motions reproduced on the shake table. A sensitivity-based finite element (FE) model updating method was used to identify damage in the building. The estimation uncertainty in the damage identification results was observed to be significant, which motivated the authors to perform, through numerical simulation, an uncertainty analysis on a set of damage identification results. This study investigates systematically the performance of FE model updating for damage identification. The damaged structure is simulated numerically through a change in stiffness in selected regions of a FE model of the shear wall test structure. The uncertainty of the identified damage (location and extent) due to variability of five input factors is quantified through analysis-of-variance (ANOVA) and meta-modeling. These five input factors are: (1,3) level of uncertainty in the (identified) modal parameters of each of the first three longitudinal modes, (4) spatial density of measurements (number of sensors), and (5) mesh size in the FE model used in the FE model updating procedure (a type of modeling error). A full factorial design of experiments is considered for these five input factors. In addition to ANOVA and meta-modeling, this study investigates the one-at-a-time sensitivity analysis of the identified damage to the level of uncertainty in the identified modal parameters of the first three longitudinal modes. The results of this investigation demonstrate that the level of confidence in the damage identification results obtained through FE model updating, is a function of not only the level of uncertainty in the identified modal parameters, but also choices made in the design of experiments (e.g., spatial density of measurements) and modeling errors (e.g., mesh size). Therefore, the experiments can be designed so that the more influential input factors (to the total uncertainty/variability of the damage identification results) are set at optimum levels so as to yield more accurate damage identification results. [source] Noncontact Operational Modal Analysis of Structural Members by Laser Doppler VibrometerCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 4 2009Dionysius M. Siringoringo The system employs natural excitation technique (NExT) to generate the cross-correlation functions from laser signals, and the eigensystem realization algorithm (ERA) to identify modal parameters of structural members. To facilitate simultaneous modal identification, time-synchronization technique and construction of cross-correlation functions from ambient response of laser signals are proposed. Performance of the proposed system is verified experimentally by evaluating the consistency and accuracy of identification results in different measurement conditions. The work presented here is an extension of the previous study, where a modal-based damage detection method using LDV was formulated. In the present study, application of LDV for structural parameters identification of a combined dynamical system is proposed. A model that represents the connection properties in terms of additional stiffness and damping is developed, and its importance for structural damage detection is discussed. The study shows that the presence of simulated damage in a steel connection can be detected by tracking the modal phase difference and by quantifying the additional stiffness and damping. [source] Damage Identification of a Composite Beam Using Finite Element Model UpdatingCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2008B. Moaveni As a payload project attached to a quasi-static test of a full-scale composite beam, a high-quality set of low-amplitude vibration response data was acquired from the beam at various damage levels. The Eigensystem Realization Algorithm was applied to identify the modal parameters (natural frequencies, damping ratios, displacement and macro-strain mode shapes) of the composite beam based on its impulse responses recorded in its undamaged and various damaged states using accelerometers and long-gage fiber Bragg grating strain sensors. These identified modal parameters are then used to identify the damage in the beam through a finite element model updating procedure. The identified damage is consistent with the observed damage in the composite beam. [source] Parameter identification of torsionally coupled shear buildings from earthquake response recordsEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 11 2008Ganesh Hegde Abstract This paper presents an efficient procedure to determine the natural frequencies, modal damping ratios and mode shapes for torsionally coupled shear buildings using earthquake response records. It is shown that the responses recorded at the top and first floor levels are sufficient to identify the dominant modal properties of a multistoried torsionally coupled shear building with uniform mass and constant eccentricity even when the input excitation is not known. The procedure applies eigenrealization algorithm to generate the state-space model of the structure using the cross-correlations among the measured responses. The dynamic characteristics of the structure are determined from the state-space realization matrices. Since the mode shapes are obtained only at the instrumented floor (top and first floors) levels, a new mode shape interpolation technique has been proposed to estimate the mode shape coefficients at the remaining floor levels. The application of the procedure has been demonstrated through a numerical experiment on an eight-storied torsionally coupled shear building subjected to earthquake base excitation. The results show that the proposed parameter identification technique is capable of identifying dominant modal parameters and responses even with significant noise contamination of the response records. Copyright © 2008 John Wiley & Sons, Ltd. [source] System identification applied to long-span cable-supported bridges using seismic recordsEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 3 2008Dionysius M. Siringoringo Abstract This paper presents the application of system identification (SI) to long-span cable-supported bridges using seismic records. The SI method is based on the System Realization using Information Matrix (SRIM) that utilizes correlations between base motions and bridge accelerations to identify coefficient matrices of a state-space model. Numerical simulations using a benchmark cable-stayed bridge demonstrate the advantages of this method in dealing with multiple-input multiple-output (MIMO) data from relatively short seismic records. Important issues related to the effects of sensor arrangement, measurement noise, input inclusion, and the types of input with respect to identification results are also investigated. The method is applied to identify modal parameters of the Yokohama Bay Bridge, Rainbow Bridge, and Tsurumi Fairway Bridge using the records from the 2004 Chuetsu-Niigata earthquake. Comparison of modal parameters with the results of ambient vibration tests, forced vibration tests, and analytical models are presented together with discussions regarding the effects of earthquake excitation amplitude on global and local structural modes. Copyright © 2007 John Wiley & Sons, Ltd. [source] Algorithms for time synchronization of wireless structural monitoring sensorsEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 6 2005Ying Lei Abstract Dense networks of wireless structural health monitoring systems can effectively remove the disadvantages associated with current wire-based sparse sensing systems. However, recorded data sets may have relative time-delays due to interference in radio transmission or inherent internal sensor clock errors. For structural system identification and damage detection purposes, sensor data require that they are time synchronized. The need for time synchronization of sensor data is illustrated through a series of tests on asynchronous data sets. Results from the identification of structural modal parameters show that frequencies and damping ratios are not influenced by the asynchronous data; however, the error in identifying structural mode shapes can be significant. The results from these tests are summarized in Appendix A. The objective of this paper is to present algorithms for measurement data synchronization. Two algorithms are proposed for this purpose. The first algorithm is applicable when the input signal to a structure can be measured. The time-delay between an output measurement and the input is identified based on an ARX (auto-regressive model with exogenous input) model for the input,output pair recordings. The second algorithm can be used for a structure subject to ambient excitation, where the excitation cannot be measured. An ARMAV (auto-regressive moving average vector) model is constructed from two output signals and the time-delay between them is evaluated. The proposed algorithms are verified with simulation data and recorded seismic response data from multi-story buildings. The influence of noise on the time-delay estimates is also assessed. Copyright © 2004 John Wiley & Sons, Ltd. [source] A simple LMS-based approach to the structural health monitoring benchmark problemEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 6 2005J. Geoffrey Chase Abstract A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. However, the fundamental modal frequencies can sometimes be less sensitive to (localized) damage in large civil structures, although there are developing algorithms that seek to reduce this difficulty. This research directly identifies changes in structural stiffness due to modeling error or damage using a structural health monitoring method based on adaptive least mean square (LMS) filtering theory. The focus is on computational simplicity to enable real-time implementation. Several adaptive LMS filtering based approaches are used to analyze the data from the IASC,ASCE Structural Health Monitoring Task Group Benchmark problem. Results are compared with those from the task group and other published results. The proposed methods are shown to be very effective, accurately identifying damage to within 1%, with convergence times of 0.4,13.0 s for the twelve different 4 and 12 degree of freedom benchmark problems. The resulting modal parameters match to within 1% those from the benchmark problem definition. Finally, the methods developed require 1.4,14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2004 John Wiley & Sons, Ltd. [source] A neural network approach for structural identification and diagnosis of a building from seismic response dataEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 2 2003C. S. Huang Abstract This work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back-propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a five-storey steel frame, subjected to different strengths of the Kobe earthquake, in shaking table tests. Copyright © 2002 John Wiley & Sons, Ltd. [source] An improved perturbation method for stochastic finite element model updatingINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 13 2008X. G. Hua Abstract In this paper, an improved perturbation method is developed for the statistical identification of structural parameters by using the measured modal parameters with randomness. On the basis of the first-order perturbation method and sensitivity-based finite element (FE) model updating, two recursive systems of equations are derived for estimating the first two moments of random structural parameters from the statistics of the measured modal parameters. Regularization technique is introduced to alleviate the ill-conditioning in solving the equations. The numerical studies of stochastic FE model updating of a truss bridge are presented to verify the improved perturbation method under three different types of uncertainties, namely natural randomness, measurement noise, and the combination of the two. The results obtained using the perturbation method are in good agreement with, although less accurate than, those obtained using the Monte Carlo simulation (MCS) method. It is also revealed that neglecting the correlation of the measured modal parameters may result in an unreliable estimation of the covariance matrix of updating parameters. The statistically updated FE model enables structural design and analysis, damage detection, condition assessment, and evaluation in the framework of probability and statistics. Copyright © 2007 John Wiley & Sons, Ltd. [source] Optimization of structural dynamic behaviour based on effective modal parametersINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 5 2007S. Besset Abstract Optimization of complex structures often leads to high calculation costs. Indeed, the structure has to be frequently reanalysed in order to update the optimization criteria. We propose an optimization method based on effective modal parameters. These parameters are close to the modal matrices used for the modal analysis of a structure. Thus, once the structure has been analysed, it becomes very easy to calculate optimization criteria. First, we will explain the modal analysis that we will use in this paper. A modal model will be used to analyse the hollow parts of the structure. The modal analysis of the whole structure will be performed using substructuring and ,double modal synthesis' proposed by Jezequel. Secondly, we will explain how to obtain effective modal parameters and their use for optimization. Finally, we will show the efficiency of these parameters through the optimization of a complex structure, using two types of optimization methods. Copyright © 2006 John Wiley & Sons, Ltd. [source] A modelling study of aerosol impacts on cloud microphysics and radiative propertiesTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 623 2007Chao-Tzuen Cheng Abstract A warm cloud microphysical parameterization was incorporated into a regional model to study the sensitivity to aerosols of cloud-radiative properties and precipitation. Assuming a trimodal lognormal aerosol size distribution, the aerosol numbers were explicitly calculated from prognostic aerosol masses, considering advection, diffusion, and cloud and raindrop activation/deactivation processes. Clean continental, average continental and urban aerosols, each with different modal parameters, were used to serve as condensation nuclei (CCN) of cloud- and raindrops, whose activations depended on supersaturation and aerosol composition. Consistent with other studies, simulations conducted for a warm cloud system indicate that more aerosols result in more cloud water and more, but smaller, cloud drops, yielding increases in cloud albedo and decreases in surface precipitation. For example, the cloud drop effective radius decreased from ,9 µm for clean continental aerosols to ,5 and ,2 µm, respectively, for average continental and urban aerosols, resulting in an increase in the respective cloud water path by ,10% and ,35% and cloud albedo by ,6% and ,12%. On the other hand, the accumulated precipitation decreased from 2.2 mm for clean continental aerosols to 1.9 and 1.2 mm, respectively, for average continental and urban aerosols. The presence of giant nuclei increased both the cloud drop effective radius and the precipitation, while the use of volumetric cloud drop radius tended to result in larger estimated cloud solar radiative forcing than the use of effective cloud drop radius. Copyright © 2007 Royal Meteorological Society [source] | ||||||||||