scholarly journals Wavelet multi-resolution approximation of time-varying frame structure

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879559 ◽  
Author(s):  
Min Xiang ◽  
Feng Xiong ◽  
Yuanfeng Shi ◽  
Kaoshan Dai ◽  
Zhibin Ding
Keyword(s):  
Parameter Estimation ◽  
Degrees Of Freedom ◽  
Structural Parameters ◽  
Identification Problem ◽  
Frame Structure ◽  
Structural Parameter ◽  
Time Varying ◽  
Engineering Structures ◽  
Time Frequency ◽  
Non Parametric

Engineering structures usually exhibit time-varying behavior when subjected to strong excitation or due to material deterioration. This behavior is one of the key properties affecting the structural performance. Hence, reasonable description and timely tracking of time-varying characteristics of engineering structures are necessary for their safety assessment and life-cycle management. Due to its powerful ability of approximating functions in the time–frequency domain, wavelet multi-resolution approximation has been widely applied in the field of parameter estimation. Considering that the damage levels of beams and columns are usually different, identification of time-varying structural parameters of frame structure under seismic excitation using wavelet multi-resolution approximation is studied in this article. A time-varying dynamical model including both the translational and rotational degrees of freedom is established so as to estimate the stiffness coefficients of beams and columns separately. By decomposing each time-varying structural parameter using one wavelet multi-resolution approximation, the time-varying parametric identification problem is transformed into a time-invariant non-parametric one. In solving the high number of regressors in the non-parametric regression program, the modified orthogonal forward regression algorithm is proposed for significant term selection and parameter estimation. This work is demonstrated through numerical examples which consider both gradual variation and abrupt changes in the structural parameters.

STRUCTURAL PARAMETER IDENTIFICATION USING DAMPED TRANSFER MATRIX AND STATE VECTORS

2013 ◽  
Vol 13 (04) ◽  
pp. 1250076 ◽  
Author(s):  
P. NANDAKUMAR ◽  
K. SHANKAR
Keyword(s):  
Transfer Matrix ◽  
Optimization Algorithm ◽  
State Vector ◽  
Degrees Of Freedom ◽  
Structural Parameters ◽  
Frame Structure ◽  
Structural Parameter ◽  
Identification Algorithm ◽  
Lumped Mass ◽  
Mass System

A new method for identification of structural parameters is proposed using Damped Transfer Matrices (DTM) and state vectors. A new transfer matrix is derived for continuous mass systems including the damping parameters. The state vector at a location is the sum of the internal and external contributions of displacements, forces, and moments at that point, when it is multiplied with the transfer matrix, state vector at the adjacent location is obtained. The structural identification algorithm proposed here involves prediction of displacement responses at selected locations of the structure using DTM and compares them with the measured responses at the respective locations. The mean square deviations between the measured and predicted responses at all locations are minimized using a nonclassical optimization algorithm, and the optimization variables are the unknown stiffness and damping parameters in the DTM. A nonclassical heuristic Particle Swarm Optimization algorithm (PSO) is used, since it is especially suited for global search. This DTM algorithm with successive identification strategy is applied on one element or sub-structure of a structure at a time and identifies all the parameters of adjacent elements successively. The algorithm is applied on numerically simulated experiments of two structures such as ten degrees of freedom lumped mass system and a cantilever with seven finite elements and one sub-structure of a nine member frame structure. Also this algorithm is verified experimentally on a sub-structure of a fixed beam. The main advantage of this algorithm is that it can be used for the local identification in a zone in a structure without modeling the entire global structure.

scholarly journals Identification of time-varying systems with partial acceleration measurements by synthesis of wavelet decomposition and Kalman filter

2020 ◽  
Vol 12 (6) ◽  
pp. 168781402093046
Author(s):  
Siyi Chen ◽  
Jubin Lu ◽  
Ying Lei
Keyword(s):  
Kalman Filter ◽  
Degrees Of Freedom ◽  
Structural Parameters ◽  
Parametric Identification ◽  
Identification Problem ◽  
Structural Systems ◽  
Wavelet Expansion ◽  
Time Varying ◽  
Multiresolution Decomposition ◽  
Original Time

Structural systems often exhibit time-varying dynamic characteristics during their service life due to serve hazards and environmental erosion, so the identification of time-varying structural systems is an important research topic. Among the previous methodologies, wavelet multiresolution analysis for time-varying structural systems has gained increasing attention in the past decades. However, most of the existing wavelet-based identification approaches request the full measurements of structural responses including acceleration, velocity, and displacement responses at all dynamic degrees of freedom. In this article, an improved algorithm is proposed for the identification of time-varying structural parameters using only partial measurements of structural acceleration responses. The proposed algorithm is based on the synthesis of wavelet multiresolution decomposition and the Kalman filter approach. The time-varying structural stiffness and damping parameters are expanded at multi-scale profile by wavelet multiresolution decomposition, so the time-varying parametric identification problem is converted into a time-invariant one. Structural full responses are estimated by Kalman filter using partial observations of structural acceleration responses. The scale coefficients by the wavelet expansion are estimated via the solution of a nonlinear optimization problem of minimizing the errors between estimated and observed accelerations. Finally, the original time-varying parameters can be reconstructed. To demonstrate the efficiency of the proposed algorithm, the identification of several numerical examples with various time-varying scenarios is studied.

Identification of Two Degree of Freedom Robot Arm’s Joints’ Time-Varying Stiffness

2012 ◽  
Vol 241-244 ◽  
pp. 1880-1884
Author(s):  
Rui Xu ◽  
Qiang Chen ◽  
Guo Lai Yang
Keyword(s):  
Degrees Of Freedom ◽  
Least Square Method ◽  
Identification Problem ◽  
Degree Of Freedom ◽  
Least Square ◽  
Analytical Mechanics ◽  
Time Varying ◽  
Robot Arm ◽  
Whole Process ◽  
Two Degree Of Freedom

This paper is concerned with the identification problem of two degree of freedom robot arm’s joints’ time-varying stiffness. The dynamic equation of two degrees of freedom robot arm can be obtained by using analytical mechanics method. Then by choosing limited memory least square method, time-varying stiffness can be identified. Finally, the calculative stiffness is compared to the “real” stiffness which is simulated in ADAMS. The whole process shows that the robot arm’s dynamic model and the method of identification are both effective.

scholarly journals Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models

2007 ◽  
Vol 37 (2) ◽  
pp. 323-343 ◽  
Author(s):  
Chi Ho Lo ◽  
Wing Kam Fung ◽  
Zhong Yi Zhu
Keyword(s):  
Parameter Estimation ◽  
Generalized Estimating Equations ◽  
Structural Parameters ◽  
Moving Average ◽  
Estimating Equations ◽  
Structural Parameter ◽  
Simulation Studies ◽  
Remarkable Improvement ◽  
Comprehensive Account ◽  
Generalized Estimating

A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.

Time-Varying Transmissibility Analysis of Vehicle–Bridge Interaction Systems with Application to Bridge-Friendly Vehicles

2021 ◽  
Author(s):  
Ke Lin ◽  
Chin An Tan ◽  
Chengqiang Ge ◽  
Huancai Lu
Keyword(s):  
Natural Frequencies ◽  
Control Strategies ◽  
Structural Parameters ◽  
A Priori ◽  
Coupled System ◽  
Parameter Tuning ◽  
Effective Control ◽  
Time Varying ◽  
Time Frequency ◽  
Tuning Strategy

It is well known that the natural frequencies of a coupled vehicle–bridge interaction system are time-varying. While this knowledge is useful for applications in bridge health monitoring, it does not provide an understanding of the relations between the excitation and coupled system responses, nor leads to developments of effective control strategies to mitigate vibration. In this paper, a novel theoretical framework for the time-varying displacement transmissibility is developed using a time-frozen technique. The time–frequency characteristics of the transmissibility functions are investigated to gain fundamental understanding and insights of the coupling dynamics in relation to the matching of bridge and vehicle natural frequencies. An important aspect of the transmissibility formulation is that it leads to the development of physics-based vibration control strategies in the frequency domain. By applying the principle of fixed points from vibration absorber designs to the transmissibility functions, an optimally tuned vehicle suspension to mitigate bridge vibration is obtained. The tuning strategy depends only on a priori known structural parameters. Thus, the tuning strategy provides useful guidelines in practice and is shown to be effective in reducing the vibrations of both the moving vehicle and the bridge. This work paves a foundation for further research in the design of bridge-friendly vehicles via parameter tuning.

A Bayesian Identification Methodology for Selection Among Pareto Optimal Structural Models Using Modal Residuals

2005 ◽  
Author(s):  
K. Christodoulou ◽  
C. Papadimitriou
Keyword(s):  
Parameter Estimation ◽  
Structural Parameters ◽  
Structural Models ◽  
Structural Parameter ◽  
Pareto Optimal ◽  
Model Errors ◽  
Optimal Weight ◽  
Modal Data ◽  
Modal Properties ◽  
Optimal Values

The structural parameter estimation problem based on measured modal data is formulated as a multi-objective optimization problem in which modal metrics measuring the fit between measured and model predicted groups of modal properties are simultaneously minimized to obtain all Pareto optimal structural models consistent with the measured data. Equivalently, the multiple Pareto optimal models can be obtained by minimizing a single metric formed as a weighted average of the multiple metrics. The Pareto optimal models are obtained by varying the values of the weights. The optimal values of the parameters are sensitive to the values of the weighting factors. A Bayesian statistical framework is used to provide a rational choice of the optimal values of the weight factors based on the available data. It is shown that the optimal weight values for each group of modal properties are asymptotically, for large number of data, inversely proportional to the optimal prediction errors of the corresponding modal group. Two algorithms are proposed for obtaining simultaneously the optimal weight values and the corresponding optimal values of the structural parameters. The proposed framework is illustrated using simulated data from multi-DOF spring-mass chain structure. In particular, compared to conventional parameter estimation techniques that are based on pre-selected values of the weights, it is demonstrated that the optimal structural models proposed by the methodology are significantly less sensitive to large model errors or bad measured modal data, known to affect optimal selection.

A wavelet transform and substructure algorithm for tracking the abrupt stiffness degradation of shear structure

2018 ◽  
Vol 22 (5) ◽  
pp. 1136-1148 ◽  
Author(s):  
Chao Wang ◽  
Demi Ai ◽  
Wei-Xin Ren
Keyword(s):  
Wavelet Transform ◽  
Degrees Of Freedom ◽  
Least Square Method ◽  
Least Square ◽  
Stiffness Degradation ◽  
Discrete Wavelet ◽  
Time Varying ◽  
Engineering Structures ◽  
Shear Structure ◽  
Stiffness And Damping

Time-varying parameter identification is an important research topic for structural health monitoring, performance evaluation, damage diagnosis, and maintenance. Practical civil engineering structures usually contain multiple degrees of freedom; however, damage often locally occurs. In this study, a discrete wavelet transform and substructure algorithm is presented for tracking the abrupt stiffness degradation of shear structures. A substructure model is built by the extraction of the local structure which may contain damaged region. Time-varying stiffness and damping are expanded into multi-scales using discrete wavelet analysis. An optimization method based on Akaike information criterion is introduced to select the decomposition scale. The expanded scale coefficients are evaluated using least square method, then the original time-varying stiffness or damping parameter is identified by reconstructing from the scale coefficients. To validate the proposed method, a numerical example of seven-story shear structure with time-varying stiffness and damping is proposed. Experiment for a three-story shear-type structure with abrupt stiffness degradation is also tested in the laboratory. Both numerical and experimental results indicate that the proposed method can effectively identify the abrupt degradation of stiffness parameter with a satisfactory accuracy.

scholarly journals Free Vibration and Buckling Analysis of Parabolic Frame Structures

2019 ◽  
Vol 7 (12) ◽  
Author(s):  
Oguzhan Das ◽  
Hasan Öztürk ◽  
Can Gönenli
Keyword(s):  
Finite Element ◽  
Free Vibration ◽  
Degrees Of Freedom ◽  
Buckling Analysis ◽  
Frame Structure ◽  
Frame Structures ◽  
Radius Of Curvature ◽  
Engineering Structures ◽  
Frame Element ◽  
Loading Case

Numerous engineering structures take place in many fields such as construction, automotive, naval industry, aerospace, etc. Parabolic frame structures have a significant role in those industries. There are many gaps in terms of the literature studies about these structures. In this paper, free vibration and buckling behavior of parabolic frame structures by using the finite element method are investigated. The structure is modeled by considering a frame element that has three degrees of freedom and neglects the displacement in y-axis. In addition, two-bay parabolic frame structure with different radius of curvature is investigated. The numerical results are compared with the CAD model of the structure by using SolidWorks for various cases. It is concluded that the results are in very good agreement with those results that are obtained from SolidWorks. It is also understood that for the different radius of curvatures the approach that is used for finite element buckling analysis in perpendicular distributed loading case does not change.

Time–frequency analysis and applications in time-varying/nonlinear structural systems: A state-of-the-art review

2018 ◽  
Vol 21 (10) ◽  
pp. 1562-1584 ◽  
Author(s):  
Zuo-Cai Wang ◽  
Wei-Xin Ren ◽  
Genda Chen
Keyword(s):  
Frequency Analysis ◽  
Structural Engineering ◽  
Nonlinear Modeling ◽  
Future Research ◽  
Time Varying ◽  
Engineering Structures ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Extreme Loads ◽  
Vibration Responses

Nonlinear dynamic behaviors of civil engineering structures have been observed not only under extreme loads but also during normal operations. Characterization of the time-varying property or nonlinearity of the structures must account for temporal evolution of the frequency and amplitude contents of nonstationary vibration responses. Neither time analysis nor frequency analysis method alone can fully describe the nonstationary characteristics. In this article, an attempt is made to review the milestone developments of time–frequency analysis in the past few decades and summarize the fundamental principles and structural engineering applications of wavelet analysis and Hilbert transform analysis in system identification, damage detection, and nonlinear modeling. This article is concluded with a brief discussion on challenges and future research directions with the application of time–frequency analysis in structural engineering.

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