• Structural Engineering and Mechanics
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• 제70권5호
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• pp.513-524
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• 2019

This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.443-446
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• 2003

Conventional disturbance rejection methods have to derive the inverse model of a system. However, the inverse model of n nonholonomic system is not unique, because an inverse it changes depending on initial conditions and desired values. A kind of internal model control (IMC) using feedback error learning is discussed for the motion control of nonholonomic mobile robots in this paper, The present method is different from a conventional IMC whose control system consists of an inverse model, a direct model and a filter. The present disturbance rejection method need not use a direct model, where the remaining two elements are composed of the same inverse model based on neural networks.

• 시스템엔지니어링학술지
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• 제14권1호
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• pp.83-88
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• 2018

Engineering is a sector with more than three times the industrial effectiveness of manufacturing. In the domestic engineering life cycle, the Operations & Maintenance (O&M) phase is a relatively high level of technology. Based on accumulated knowledge of O&M phase, it is necessary to advance operating technology and expand overseas O&M market expenditure. This study is the early stage of knowledge-based power plant O&M service framework reference model. In this study, we propose a conceptual model of architecture framework for power plant O&M. We survey the architecture framework and reference model and propose conceptual model of architecture framework for power plant O&M. The conceptual model of architecture framework for power plant O&M consists of stakeholder, O&M scenario, O&M technology. In particular, the O&M technology is defined as the fourth industrial revolution intelligence information technology. We defined a meta model from the conceptual model to define the power plant O&M architecture framework. In the future, we intend to development an architecture framework from the conceptual model and meta model.

• 한국해양공학회지
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• 제27권4호
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• pp.33-44
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• 2013

IIn this study, a wave-surge-tide coupling numerical model was developed to consider nonlinear interaction. Then, this model was applied and calculations were made for a storm surge on the southeast coast. The southeast coast was damaged by typhoon "Maemi" in 2003. In this study, we used a nearshore wind wave model called SWAN (Simulating WAves Nearshore). In addition, the Meyer model was used for the typhoon model, along with an ocean circulation model called POM (Princeton Ocean Model). The wave-surge-tide coupling numerical model could calculate exact parameters when each model was changed to consider the nonlinear interaction.

• 한국자동차공학회논문집
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• 제23권5호
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• pp.486-493
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• 2015

In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

• 공업화학
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• 제23권2호
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• pp.204-209
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• 2012

상업용 루테늄 촉매 상에서 에탄의 수증기 개질 반응에 대한 kinetics 데이터를 얻기 위하여 반응온도, 에탄의 분압, 수증기/에탄의 비 등을 변화시키면서 반응 실험을 수행하였다. Kinetics 데이터를 사용하여 Power rate law kinetic model 과 Langmuir-Hinshelwood model의 parameter를 구하였다. 또한 kinetic model식을 적용하여 PRO/II를 이용한 공정 모사를 통해서 에탄의 수증기 개질 반응기 sizing을 수행하였다. 동일한 전환율을 얻기 위해서는 Power rate law model을 적용하였을 경우가 Langmuir-Hinshelwood model을 적용하였을 경우보다 개질 반응기의 부피가 더 큼을 알 수 있었다. Langmuir-Hinshelwood model에 의해 계산된 반응 속도가 반응 실험 결과에 의해 구해진 반응 속도와 더 잘 일치했기 때문에 Langmuir-Hinshelwood model을 적용하여 계산된 반응기의 크기가 실제 반응기 설계에 더 적절하다고 판단된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1069-1072
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• 1996

In modern control engineering, the model following system is a typical method. The model following system's performance is due to algorithm of control law, accuracy of modeling to the plant, and dynamics of the reference model. But the determination of the reference model depends on knowledge of an expert. Using an expert system, the determination method of the reference model was proposed in this paper. So, the reference model can be selected by user who has no Knowledge of dynamics and parameters.

• Journal of Web Engineering
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• 제21권5호
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• pp.1671-1690
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• 2022

Human activity recognition (HAR) is a key technology in many applications, such as smart signage, smart healthcare, smart home, etc. In HAR, deep learning-based methods have been proposed to recognize activity data effectively from video streams. In this paper, the end-to-end model based on convolutional long short-term memory (LSTM) is proposed to recognize human activities. Convolutional LSTM can learn features of spatial and temporal simultaneously from video stream data. Also, the number of learning weights can be diminished by employing convolutional LSTM with an end-to-end model. The proposed HAR model was optimized with various simulation environments using activities data from the AI hub. From simulation results, it can be confirmed that the proposed model can be outperformed compared with the conventional model.

• 한국해양공학회지
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• 제29권5호
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.