• 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.

• Structural Engineering and Mechanics
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• v.38 no.3
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• pp.315-332
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• 2011

The Combined Deterministic Stochastic Subspace based System Identification Technique (CDSSSIT) is a powerful input-output system identification technique which is known to be always convergent and numerically stable. The technique determines a Kalman state sequence from the projection of the output-input data. The state space matrices are determied subsequently from this Kalman state sequence using least squares. The objective of this paper is to examine the efficiency of the CDSSSIT in identifying the modal parameters (frequencies and mode shapes) of a stiff structure. The results show that the CDSSSIT predicts the modal parameters of stiff buildings quite accurately but is very sensitive to the location of sensors.

• 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.

• Smart Structures and Systems
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• v.7 no.2
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• pp.153-167
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• 2011

The Subspace based System Identification Techniques (SSIT) have been very popular within the research circles in the last decade due to their proven superiority over the other existing system identification techniques. For operational (output only) modal analysis, the stochastic SSIT and for operational modal analysis in the presence of exogenous inputs, the combined deterministic stochastic SSIT have been used in the literature. This study compares the application of the two alternative techniques on a typical school building in Istanbul using 100 Monte Carlo simulations. The study clearly shows that the combined deterministic stochastic SSIT performs superior to the stochastic SSIT when the techniques are applied on noisy data from low to mid rise stiff structures.

• 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.

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.347-364
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• 2019

Two seismic response data from the CSMIP strong motion instrumentation of Pacoima dam are selected: San Fernando earthquake (Jan 13, 2001; ML=4.3) and Newhall earthquake (Sept. 1, 2011; ML=4.2), for the identification of the dam system. To consider the spatially nonuniform input ground motion along the dam abutment, the subspace identification technique with multiple-input and multiple-output is used to extract the dynamic behavior of the dam-reservoir interaction system. It is observed that the dam-reservoir interaction is significant from the identification of San Fernando earthquake data. The influence of added mass (from the reservoir) during strong ground motion will create a tuned-mass damper phenomenon on the dam body. The fundamental frequency of the dam will be tuned to two different frequencies but with the same mode shapes. As for the small earthquake event, the dam-reservoir interaction is insignificant.

• 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.

• Smart Structures and Systems
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• v.7 no.2
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• pp.133-152
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• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.331-351
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• 2012

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.