• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.116-123
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• 2008

Food and Agriculture Organization (FAO) and many countries make an effort to conserve and utilization of animal genetic resources to prepare for our unpredictable future. In order to protect the customer and the producer from the animal diseases and unjust distribution, many country seek to appropriate solution. Among the solutions, RFID technology can be used as a basic technology, since this technology can be applied in the conservancy and utilization of animal genetic resources, object management for improved animal and traceability of animal's distribution flow. There are two main issues in making the efficient RFID environment. The first issue is the standardization of code system for object identification. International Organization for Standard (ISO) published the standard which regulates RFID of animal (ISO 11784 and ISO 11785). Based on these standards, many countries have tried to establish their national standard. In Korea, National Institute of Animal Science (NIAS) playa main role in establishing the standard of object identification code based on ISO 11784. Even though the standard format of object's identification is well established, the RFID system may not be operated well without the standardization of RFID network and related equipment. In Korea, National Internet Development Agency of Korea (NIDA) has proposed the RFID Network at 2006, which can be applied in the different kind of system at each phase. But, the implementation case of this RFID Network does not reported yet, since many company or agency who introduce RFID technology, implemented as an isolated individual system. In our study, we show that RFID network can be utilized for any kind of system at each phase, and propose the improvement point in order to be widely used.

• Smart Structures and Systems
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• v.15 no.3
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• pp.683-698
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• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.394-402
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• 1999

In this paper, we present an effective RLS algorithm with forgetting factor of Erlang function for the system identification. In the proposed algorithm, the forgetting factor decreases monotonically in the first stage, and then it increases monotonically in the second stage in contrary to the conventional forgetting factor RLS algorithms. In addition, annealing effect and an asymptotically stability of the proposed algorithm is discussed based on the analysis of convergency property on. Simulation results for the system identification problem indicate the superiority of the proposed algorithm in comparison to the RLS algorithm such as NLMS and Kalman filter based algorithm.

• Computational Structural Engineering
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• v.6 no.2
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• pp.71-78
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• 1993

A method to estimate damage of bridge structures is developed using system identification approach. Dynamic behavior of damaged structures is represented by a non-linear hysteretic moment model. Structural properties can be evaluated through system identification. To incorporate variability of the structural properties and uncertainties of structural response, damage is represented as random quantities. Numerical example is shown for the bridge structure under different ground excitation.

• Journal of Power System Engineering
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• v.4 no.3
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.676-681
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• 2002

System Identification is carried out for a full scale five-story builing to design a vibration controller. Dynamic characteristics such as natural frequencies, damping ratios, and modes are obtained from the input/output information by both sine-sweep method and white noise method. The active mass driver installed on the five floor is applied as external loading to move the building and each floor acceleration is measured and processed for the system identification. The identified building will be experimentally investigated again with viscoelastic dampers installed at inter-stories to obtain the response behavior. Corresponding result will be presented soon.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.10
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• pp.912-917
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• 2007

In this paper system identification of a small UAV via neural networks is tried and the estimated parameters are then compared to those obtained by Fourier Transform Regression and Maximum Likelihood Estimation Techniques. With the estimated parameters a linear system is constructed and simulated to compare to the flight data. The results show that parameter identification using neural networks is comparable to the existing techniques

• 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.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.93-100
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• 2003

We present a recursive total least squares (RTLS) algorithm for adaptive system identification. So far, recursive least squares (RLS) has been successfully applied in solving adaptive system identification problem. But, when input data contain additive noise, the results from RLS could be biased. Such biased results can be avoided by using the recursive total least squares (RTLS) algorithm. The RTLS algorithm described in this paper gives better performance than RLS algorithm over a wide range of SNRs and involves approximately the same computational complexity of O(N²).

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.815-817
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• 1999

In this paper, we developed a fuzzy identification system to evaluate sensation of equilibrium objectively and quantitatively. By using caloric test. we estimated ECG(electro-cardiogram) and EOG(electro-oculogram), which were biomedical signals related to sensation of equilibrium, and used them as inputs of fuzzy identification system input. Fuzzy identification system analyzed the relationality between biomedical signals and sensation of equilibrium automatically, and evaluated it taking the co-relation between these signals into consideration.