• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.395-406
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• 2016

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.353-373
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• 2012

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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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.

• Wind and Structures
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• v.36 no.1
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• pp.61-73
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• 2023

In this article, a novel structural modal parameters identification methodology is developed to determine the natural frequencies and damping ratios of civil structures based on the symplectic geometry mode decomposition (SGMD) approach. The SGMD approach is a new decomposition algorithm that can decompose the complex response signals with better decomposition performance and robustness. The novel method firstly decomposes the measured structural vibration response signals into individual mode components using the SGMD approach. The natural excitation technique (NExT) method is then used to obtain the free vibration response of each individual mode component. Finally, modal natural frequencies and damping ratios are identified using the direct interpolating (DI) method and a curve fitting function. The effectiveness of the proposed method is demonstrated based on numerical simulation and field measurement. The structural modal parameters are identified utilizing the simulated non-stationary responses of a frame structure and the field measured non-stationary responses of a supertall building during a typhoon. The results demonstrate that the developed method can identify the natural frequencies and damping ratios of civil structures efficiently and accurately.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.59-64
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• 2003

The parameter modification of the initial FEM model to match it with the experimental results needs the modal information and the modal sensitivity matrix to the parameter change. There are two cases this methodology is ill-equip to deal with; the deficiency of the necessary modal information and the ill-conditioning of the sensitivity matrix. In this research, a novel concept of the feedback exciter that uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains as the reference signal is proposed. There are 2 advantages using this external feedback excitation. First, we can use the change of the system response such as modal data by the active energy Path from the sensor to the exciter. This change of the system response can be additional clues to the system dynamics that we want to know. Secondly, the external energy Path alternates the offset of the Parameter change to the system response. That means the modal sensitivity of the parameters becomes different from the original sensitivities by the feedback excitation. Through the feedback loop, we can change the similar modal sensitivities of some updating parameters and consequently discriminate the parameters using the closed-loop modal data. To demonstrate the discrimination performance, the parameter estimation of an indeterminate structure by use of the feedback method is introduced.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.328-334
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• 2001

Up to now. vibration analysis and vibration engineering have been developed, encompassing the aspects of both experimental and analytical techniques. Using experimental modal analysis or modal testing, the mode shapes and frequencies of practical structure can be measured accurately. Curve-Fitting Method is realized through experimental modal identification. In the experimental modal parameter estimation, the estimation of modal damping factor is difficult for complicated and large structure. Also numbers of Selected mode are determined before the procedure. This paper describes the vibration shape of the super-structure model of ship through experimental modal analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.641-647
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• 2008

This paper introduces a new technique that can extract natural frequencies and damping ratios from output-only vibration data. Firstly, the free vibration data is obtained from the cross correlations of the output-only response data using a singular value decomposition process. Secondly, the well-known system identification algorithm is applied to extract the natural frequencies and damping ratios from the extracted free vibration data. Comparing to ERADC technique, the accuracy of the proposed modal parameter identification algorithm has been numerically examined. Furthermore, the practicability of the proposed algorithm has been examined through the output-only acceleration data collected from the Seohae cable-stayed bridge. Using the proposed technique, total 24 modes have been identified for the deck plate motions of the bridge.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Journal of Aerospace System Engineering
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• v.7 no.4
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• pp.27-35
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• 2013

Identifying the stability of rotor systems is prerequisite for clear determination of the parameter identification and safety, through which operating conditions may be rationally ascertained. For this purpose, the complex modal analysis of periodically time-varying system has been introduced by transforming the relation between periodic eigen-vectors and the corresponding adjoint vectors into the latent value problem. Stability investigation associated with modal features for rotor systems is performed using numerical simulation based upon the analysis model.