• 한국해양공학회지
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• 제10권1호
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• pp.17-24
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• 1996

In the present paper nonlinear normal modes of a rotor system is studied. The methodology to obtain the nonlinear normal modes is based on center manifold reduction technique. It also provides a way of nonlinear coordinate transform from the physical cordinates to the modal coordinates and an idea of individual nonlinear modal dynamics. In order to apply the present method to a rotor dynamics a single mass rotor system on nonlinear elastic supports is employed and the nonlinear normal modes of the system are obtained.

• Smart Structures and Systems
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• 제17권3호
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.283-290
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• 2007

A bi-modal tram has been developed to offer an advanced transportation service compared with existing vehicles. The All-Wheel-Steering system is applied to the bi-modal tram to satisfy the required steering performance because the bi-modal tram has extended length and articulated mechanism. An ECU for the steering system is essential to steer wheels on 2nd and 3rd axles by the specific AWS algorithm with the prescribed driving condition. The Hardware-In-the-Loop Simulation(HILS) system is planned for the purpose of evaluating the steering system of the bi-modal tram. There are kinematic links with the hydraulic actuator to steer wheels on each 2nd and 3rd axles and also same steering mechanism as the actual vehicle is in the HILS system. Controlling the movement of hydraulic actuator which reflects the lateral steering reaction force on each wheel is the key to realize the HILS system, but the reaction force is continuously changed according to various driving conditions. Therefore, the simulation through the multi-body dynamics model is used to obtain the required forces.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1996년도 춘계학술대회논문집; 부산수산대학교, 10 May 1996
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• pp.86-91
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• 1996

In this study, the modal analysis is adopted for the investigation of vibratory characteristics of a rolling stock. A governing equation for this system is deverived on a condition that the rolling stock is in proportional viscous damping and proportional hysteretic damping. By applying this method a computational modal analysis software is developed. The validity and reliability of this method is verified by comparing the results for the above case and with those of a system having proportional viscous damping and a system having general viscous damping. A system that has non-linearity, an error from the calculation may occur in the analysis. In this case, we applied the piecewise linear method to estimate the modal parameters.

• 소음진동
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• 제10권5호
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• pp.800-805
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• 2000

To determine the modal matrix and modal frequency of engine mount system, we most solve so-called eigen-value problem. However eigen-value problem of engine mount system with hydraulic mount can not be solved by general eigne-analysis algorithm because the properties of hydraulic mount vary with frequency. so in this paper the method for modal analysis of rigid body motions of an engine supported by hydraulic mount is proposed. Natural frequencies and mode shapes of this nonlinear system are obtained by using complex exponential method and Laplace transformation method. In time domain, impulse response functions are calculated by (two-sided) discrete inverse Fourier Transformation of forced frequency response functions achieved by Laplace transformation of the differential equation of motion. Considering the fact that frequency response functions synthesized by modal parameters form proposed method are in good agreement with original FRFs, it is proved that the proposed method is very efficient and useful for the analysis of eigne-value problem of hydraulic engine mount system.

• 한국정밀공학회지
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• 제8권2호
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• pp.57-68
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• 1991

In this study, to analyse the dynamic characteristics of a machine-tool spindle system, the spindle is mathematically represented by a Timoshenko beam including the internal damping of beam material, and each bearing by four bearing coefficients; stiffness and damping coefficients in moment and radial directions. And the dynamic compliance of the system is calculated by introducing the transfer matrix method, and the complex modal analysis method has been applied for the modal parameter identification. The influence of the bearing coefficients, material damping factor and bearing span on the dynamic characteristics of the system is parametrically examined.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1384-1387
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• 2001

Presented is a method to predict strain responses from displacement measurements on a mechanical structure. The method consists of forming a transformation matrix, which is calculated from displacement and strain modal matrices. The modal matrices can be obtained by either finite element analysis or modal testing. One disadvantage of the method is that it requires displacements on all measuring points be measured simultaneously. The strain prediction method is applied to a simple simulated system.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.423-430
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• 2004

A new active neuro-control strategy for seismic response reduction using modal states is proposed. In order to apply the neuro-control strategy to the given structural system it is needed to select state variables used as inputs into the neural network. If the degrees of freedom of the analytical model is large, there are so many possible combinations of the state variables. And selecting state variables is very complicated and troublesome task for the designer. In order to avoid this problem, the proposed control system adopts modal states as inputs. Since the modal states contain the information of the whole structural system's behavior, it is proper to use modal states as inputs of the neuro-controller. The simulation results show that the proposed the proposed active neuro-control strategy is quite effective to reduce seismic responses. In addition, the consuming time for training proposed neuro-controller is quite shorter than that for the conventional neuro- controller. The results of this investigation, therefore, indicate that the proposed active neuro-control strategy using modal states as the inputs could be effectively used for control seismically excited structures.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.184-194
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• 2016

In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.

• International Journal of Fluid Machinery and Systems
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• 제2권4호
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• pp.278-285
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• 2009

Operational modal analysis (OMA) allows modal parameters, such as natural frequencies and damping, to be estimated solely from data collected during operation. However, a main shortcoming of these methods resides in the evaluation of the accuracy of the results. This paper will explore the uncertainty and possible variations in the estimates of modal parameters for different operating conditions. Two algorithms based on the Least Square Complex Exponential (LSCE) method will be used to estimate the modal parameters. The uncertainties will be calculated using a Monte-Carlo approach with the hypothesis of constant modal parameters at a given operating condition. In collaboration with Andritz-Hydro Ltd, data collected on two different stay vanes from an Andritz-Hydro Ltd Francis turbine will be used. This paper will present an overview of the procedure and the results obtained.