• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.365-379
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• 2017

This paper presents a comparison of the black-box and the physics based derived gray-box models for subspace identification for structures subjected to support-excitation. The study compares the damage detection capabilities of both these methods for linear time invariant (LTI) systems as well as linear time-varying (LTV) systems by extending the gray-box model for time-varying systems using short-time windows. The numerically simulated IASC-ASCE Phase-I benchmark building has been used to compare the two methods for different damage scenarios. The efficacy of the two methods for the identification of stiffness parameters has been studied in the presence of different levels of sensor noise to simulate on-field conditions. The proposed extension of the gray-box model for LTV systems has been shown to outperform the black-box model in capturing the variation in stiffness parameters for the benchmark building.

• Fire Protection Technology
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• s.30
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• pp.46-54
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• 2001

According to the use of electric power increases, the fire which ignited by electrical causes increases too. In this thesis electrical fires which occurs in the country for the past ten years are analyzed and developed the technology to identify the electrical fire. The focus of study is method to identify the electrical fires. The causes of electrical fire, it is analyzed a short-circuit and a over current, which take the highest ratio compare with other causes. The rationalization of identification, an electrical operating status is continuous monitored and the status can be accessed, black-box for identification electrical fires. The results of the study are the causes of electrical fire are found out logically, and the developed black-box for identification fires.

• Geomechanics and Engineering
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• v.13 no.6
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• pp.997-1010
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• 2017

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1334-1337
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• 2006

System identification is the field of modeling dynamic systems from experimental data. As a modeling technique, we can mention finite element method (FEM). In addition, we are able to measure modal data as the experimental data. The system can be generally categorized into a gray box and black box. In the gray box, we know mathematical model of a system, but we don't know structural parameters exactly, so we need to estimate structural parameters. In the black box, we don't know a system completely, so we need to identify system from nothing. To date, various system identification methods have been developed. Among them, we introduce system realization theory which uses Hankel matrix and Eigensystem Realization Algorithm (ERA) that enable us to identify modal parameters from noisy measurement data. Although we obtain noise-free data, however, we are likely to face difficulties in identifying a structure with hidden modes. Hidden modes can be occurred when the input or output position comes to a nodal point. If we change a system using a mode decoupling controller, the hidden modes can be revealed. Because we know the perturbation quantities in a closed loop system with the controller, we can realize an original system by subtracting perturbation quantities from the closed loop system. In this paper, we propose a novel method to identify a structure with hidden modes using the mode decoupling controller and the associated example is given for illustration.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.561-563
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• 1997

In this paper, we identified the Black-box system with serious nonlinerity and fast dynamics using Neural Network. This NN have new structure and learned by RLS. It identify system in real-time without priori data. We use this NN to 7-DOF vehicle identification.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1449-1454
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• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.593-596
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• 2020

많은 차량에 부착되어 있는 블랙박스를 활용하여 수집된 이미지 데이터들을 분석, 도로의 파손 상태를 체크하고 웹 서버에 표시하고 관련 기관에 신고합니다. 따라서 해당 도로를 이용하는 운전자들에게 도로의 상황을 알려주고 보수 조치가 빠르게 이루어 질 수 있도록 도와주는 서비스입니다.

• Journal of Conservation Science
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• v.33 no.1
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• pp.17-24
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• 2017

Studies were conducted on manufacturing techniques by applying microscopy and conservation treatments on the annals of Joseon dynasty storage box at the National Museum of Korea. The results revealed that lime tree wood(Tilla spp.) was used to make the annals of Joseon dynasty storage box. Lacquering techniques were used to coat the box with a layer of lacquer and bone ash and then cover it with traditional Korean paper. After being covered with traditional Korean paper, more layers were applied in the following sequence: mud ashes, black lacquer, pure lacquer, and black lacquer. Before conservation treatments, some components and lacquer layers were missing in addition wood joint were loose. Therefore, conservation and restoration should be conducted based on the identified wood and by observing the shape of the remaining components.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.05a
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• pp.279-287
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• 2010

This paper surveys the recent research activities regarding dynamical modeling of high amplitude - high frequency thermo-acoustic instabilities occurring in gas-turbine engines, rockets, and etc, which are fundamental to actively control of such phenomena. For this, we introduces the reduced-order system modeling approaches, conducted after 1990s. Particularly, we deal with the grey-box approach, which determines the structure of the model based on physical rules and uses system's input-output data for estimating parameters of the model, and the black-box approach, which uses model structure without physics-based interpretation. At the end of the paper, we briefly discuss future directions and feasibilities of the research in this field.