• 한국정밀공학회지
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• 제16권7호
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• pp.178-187
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• 1999

In order to identify a transfer function model with noise, penalty function method has been widely used. In this method, estimation process for possible model parameters from low to higher order proceeds the model identification process. In this study, based on linear estimation method, a new approach unifying the estimation and the identification of ARMAX model is proposed. For the parameter estimation of a transfer function model with noise, linear estimation method by noise separation is suggested instead of nonlinear estimation method. The feasibility of the proposed model identification and estimation method is verified through simulations, namely by applying the method to time series model. In the case of time series model with noise, the proposed method successfully identifies the transfer function model with noise without going through model parameter identification process in advance. A new algorithm effectively achieving model identification and parameter estimation in unified frame has been proposed. This approach is different from the conventional method used for identification of ARMAX model which needs separate parameter estimation and model identification processes. The consistency and the accuracy of the proposed method has been verified through simulations.

• 한국정밀공학회지
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• 제12권5호
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• pp.136-148
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• 1995

In this study, a model integration method is pressented as a new method for development of a parametric simulation model. This method enable us to integrate the special simulation models for each production subsystem into a large simulation model. Not only this large simulation model but also each special simulation model for each production subsytem can be used independently. Using this integration method man can reduce the development time and cost for simulation model development. To show the usefulness of this method, a simulation model for a production system with robots is developed by this model integration method. This simulation model is realized by the integration of two special simulation models, one model for a machining subsystem and the other model for a transport subsystem. The modeled production system consists of the robotic cells for machining and a transport subsystem which enable the material flow among the robotic cells. The flow of workpiece in each robotic cell is not fixed. All machines in a robotic cell are only served by robots.

• Journal of Advanced Marine Engineering and Technology
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• 제27권5호
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• pp.609-616
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• 2003

The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference Adaptive Speed Control system of a diesel engine, in which PID control system for the model of a diesel engine is adopted as the nominal model and Fuzzy controller and derivative operator are adopted as the adaptive controller.

• 한국정보통신학회논문지
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• 제3권4호
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• pp.907-914
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• 1999

This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2002년도 추계학술대회
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• pp.289-312
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• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Structural Engineering and Mechanics
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• 제32권5호
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Structural Engineering and Mechanics
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• 제86권6호
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• pp.705-714
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• 2023

In order to establish a dynamic model test method of bridge pylons subjected to ocean waves, the similarity method of hydroelastic model test for bridge pylons were analyzed systematically, and a model design and production method was proposed. Using this method, a dynamic test model of a bridge pylon was made, and then a free vibration test on the model structure and a dynamic response test of the model structure under wave actions were conducted in a wave flume. The results of the free vibration test show that the primary natural frequencies of the structure by the model test are close to the design frequencies of the prototype structure, indicating that the dynamic characteristics of the bridge pylon are well simulated by the model structure. The results of the dynamic response test show that wave induced base shear forces and motion responses on the model structure are consistent with the numerical results of the prototype structure. The model test results confirm that the proposed model test design method is feasible and applicable. It has application and reference significances for model testing studies of such marine bridge structures.

• The Journal of Advanced Prosthodontics
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• 제10권3호
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• pp.245-251
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• 2018

PURPOSE. To evaluate the accuracy of a model made using the computer-aided design/computer-aided manufacture (CAD/CAM) milling method and 3D printing method and to confirm its applicability as a work model for dental prosthesis production. MATERIALS AND METHODS. First, a natural tooth model (ANA-4, Frasaco, Germany) was scanned using an oral scanner. The obtained scan data were then used as a CAD reference model (CRM), to produce a total of 10 models each, either using the milling method or the 3D printing method. The 20 models were then scanned using a desktop scanner and the CAD test model was formed. The accuracy of the two groups was compared using dedicated software to calculate the root mean square (RMS) value after superimposing CRM and CAD test model (CTM). RESULTS. The RMS value ($152{\pm}52{\mu}m$) of the model manufactured by the milling method was significantly higher than the RMS value ($52{\pm}9{\mu}m$) of the model produced by the 3D printing method. CONCLUSION. The accuracy of the 3D printing method is superior to that of the milling method, but at present, both methods are limited in their application as a work model for prosthesis manufacture.

• 제어로봇시스템학회논문지
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• 제11권2호
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• pp.152-159
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• 2005

This paper describes the application of a model-based system design method critical to complex intelligent systems, PSARE, to a welding robot development to define its top level architecture. The PSARE model consists of requirement model which describes the core processes(function) of the system, enhanced requirement model which adds technology specific processes to requirement model and allocates them to architecture model, and architecture model which describes the structure and interfaces and flows of the modules of the system. This paper focuses on the detailed procedure and method rather than the detailed domain model of the welding robot. In this study, only the top level architecture of a welding robot was defined using the PSARE method. However, the method can be repeatedly applied to the lower level architecture of the robot until the process which the robot should perform can be clearly defined. The enhanced data flow diagram in this model separates technology independent processes and technology specific processes. This approach will provide a useful base not only for improvement of a class of welding robots but also for development of increasingly complex intelligent real-time systems.

• Structural Engineering and Mechanics
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• 제44권5호
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• pp.585-600
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• 2012

This paper presents a Modified Tikhonov Regularization (MTR) method in model updating for damage identification with model errors and measurement noise influences consideration. The identification equation based on sensitivity approach from the dynamic responses is ill-conditioned and is usually solved with regularization method. When the structural system contains model errors and measurement noise, the identified results from Tikhonov Regularization (TR) method often diverge after several iterations. In the MTR method, new side conditions with limits on the identification of physical parameters allow for the presence of model errors and ensure the physical meanings of the identified parameters. Chebyshev polynomial is applied to approximate the acceleration response for moderation of measurement noise. The identified physical parameter can converge to a relative correct direction. A three-dimensional unsymmetrical frame structure with different scenarios is studied to illustrate the proposed method. Results revealed show that the proposed method has superior performance than TR Method when there are both model errors and measurement noise in the structure system.