• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2143-2145
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• 2003

In the linear system identification using the discrete time constant coefficients, there is a subspace method based on 4SID recently much suggested instead of the parametric method like as the maximum likelihood method. The subspace method is not related with the impulse response and difference equation in its input-output equation, but with the system matrix of the direct state space model from the input-output data. The subspace method is a very useful tool to adopt in the multivariable system identification, but it has a shortage unable to adopt in the closed-loop system identification. In this paper, we are suggested the methods to get rid of the shortage of the subspace method in the closed-loop system identification. The subspace method is used in the estimate of the output prediction values from the estimating of the state space vector. And we have compared the results with the outputs of the recursive least square method in the numerical simulation.

• Journal of Korean Association for Spatial Structures
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• v.3 no.4 s.10
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• pp.53-58
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• 2003

In order to control seismic responses of building structures effectively and stably, it is very important to estimate the dynamic characteristics of target structure exactly based on input-output signal data. In this paper, it is shown that Subspace Identification Method is able to be applied effectively to system identification of building structures. To verify the efficiency of Subspace Identification Method, the vibration experiments were conducted on a specimen structure which is a 5-storied building structure model consisted of H-shaped steel beam, and the simulated seismic responses of the identified structure model were compared with the observed ones under the same excitation. It was observed that the experimental results coincided with the analyzed ones proposed in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.299-303
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• 1995

This paper charcterizes dynamics of cold tandem minns, and constructs it state-space model of which are linear time invariant, using subspace method. Step responses particularly show the influence on mass transfer delay. Input-output data set are obtained form nonlinear differential equations including mass transfer delay and nonlinearity. It is shown that the identified state-apace model well approximates the original systems dynamics.

• Wind and Structures
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• v.9 no.2
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• pp.159-178
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• 2006

For the slender and flexible cable supported bridges, identification of all the flutter derivatives for the vertical, lateral and torsional motions is essential for its stability investigation. In all, eighteen flutter derivatives may have to be considered, the identification of which using a three degree-of-freedom elastic suspension system has been a challenging task. In this paper, a system identification technique, known as covariance-driven stochastic subspace identification (COV-SSI) technique, has been utilized to extract the flutter derivatives for a typical bridge deck. This method identifies the stochastic state-space model from the covariances of the output-only (stochastic) data. All the eighteen flutter derivatives have been simultaneously extracted from the output response data obtained from wind tunnel test on a 3-DOF elastically suspended bridge deck section-model. Simplicity in model suspension and measurements of only output responses are additional motivating factors for adopting COV-SSI technique. The identified discrete values of flutter derivatives have been approximated by rational functions.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.979-980
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• 2008

In this paper we use the Isometric Projection, a linear subspace method, for manifold representation of the pose-varying-faces. Isometric Projection method for pose identification is evaluated on view varying faces and is compared with other global and local linear subspace methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Structural Engineering and Mechanics
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• v.59 no.1
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• pp.187-207
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• 2016

Practical ambient excitations of engineering structures usually do not comply with the stationary-white-noise assumption in traditional operational modal analysis methods due to heavy traffic, wind guests, and other disturbances. In order to eliminate spurious modes induced by non-white noise inputs, the improved stochastic subspace identification based on a delay index is proposed in this paper for a representative kind of stationary non-white noise ambient excitations, which have nonzero autocorrelation values near the vertical axis. It relaxes the stationary-white-noise assumption of inputs by avoiding corresponding unqualified elements in the Hankel matrix. Details of the improved stochastic subspace identification algorithms and determination of the delay index are discussed. Numerical simulations on a four-story frame and laboratory vibration experiments on a simply supported beam have demonstrated the accuracy and reliability of the proposed method in eliminating spurious modes under non-white noise ambient excitations.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.445-466
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• 2004

In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.3
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• pp.288-294
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• 2013

This paper introduces a novel method of on-line identifying the stator resistance and leakage inductance of dual three phase induction motor (DTPIM). According to the machine mathematical model, the stator resistance and leakage inductance can be estimated using the voltage and current values in harmonic subspace. Thus a method of voltage vector injection in harmonic subspace (VVIHS) is proposed, which causes currents in harmonic space. Then the errors between command and actual harmonic currents are utilized to regulate the machine parameters, including stator resistance and leakage inductance. The principle is presented and analyzed in detail. Experimental results prove the feasibility and validity of proposed method.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.429-444
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• 2004

The ambient vibration measurement is a kind of output data-only dynamic testing where the traffics and winds are used as agents responsible for natural or environmental excitation. Therefore an experimental modal analysis procedure for ambient vibration testing will need to base itself on output-only data. The modal analysis involving output-only measurements presents a challenge that requires the use of special modal identification technique, which can deal with very small magnitude of ambient vibration contaminated by noise. Two complementary modal analysis methods are implemented. They are rather simple peak picking (PP) method in frequency domain and more advanced stochastic subspace identification (SSI) method in time domain. This paper presents the application of ambient vibration testing and experimental modal analysis on large civil engineering structures. A 15 storey reinforced concrete shear core building and a concrete filled steel tubular arch bridge have been chosen as two case studies. The results have shown that both techniques can identify the frequencies effectively. The stochastic subspace identification technique can detect frequencies that may possibly be missed by the peak picking method and gives a more reasonable mode shapes in most cases.