• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1586-1595
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• 2018

For the problem that the complexity of 3-D modeling and multi parameter optimization, as well as the uncertainty of the winding factor of axial flux permanent magnet generator with coreless windings. The complex 3-D model was simplified into 2-D analytic model, and an analytical formula for the winding factor that adapting different coreless stator winding is proposed in this paper. The analytical solution for air-gap magnetic fields, no-load back EMF, electromagnetic torque, and efficiency are calculated by using this method. The multiple objective and multivariable optimization of the maximum fundamental and the minimum harmonic content of back EMF are performed by using response surface methodology. The proposed optimum design method was applied to make a generator. The generator was tested and the calculated results are compared with the proposed method, which show good agreements.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1089-1098
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• 2018

This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1798-1799
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• 2011

In this paper, A new cost-effective and accurate input noise rejection method for High Speed Counter module of PLC (Programmable Logic Controller) is proposed. By using combination of simple additional logic circuit and the Timer Pulse function of general purpose MPU, Cost-effectiveness and improvement of accuracy of filtering function can be achieved. This proposed method is verified by simulation. This proposed method is much useful for simple industrial controller based on simple microprocessor because of simplicity, accuracy and low cost.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.92-95
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• 2002

A study on the system automation for the nitrogen splash slag coating in Basic Oxygen Blowing Furnace (BOF) is described. The engineers are trying to do their best efforts to increase the life of converter lining by developing improved refractory material and optimal operation techniques in the steel plants, A new slag coating method is needed to reduce the erosion rates of the refractory. In the current slag costing method, the BOF was swung back and forth. The new method uses the oxygen lance to blow the residual slag to the walls and cone of the converter. The nitrogen gas is used for blowing. This method is developed based on the automation process at factory in POSCO dated on the May 1998. The test results of nitrogen splash slag coating system for the BOF at POSCO are show to show the effectiveness of the system.

• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.27-31
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• 1995

In this paper, the determination method of available bandwidth for automation of the split-spectrum processing(SSP) has been studied. The SSP is used for the visibility enhancement of the ultrasonic signal with grain noise. Even though the SSP has proved useful in signal-to-noise ratio enhancement, its application and automation have been limited due to ambiguity in the determination of available bandwidth. Until recently, it is the usual practice to optimize the available bandwidth by trial and error. The spectral histogram is the statistical distribution of the spectral windows that is selected by the minimization algorithm with the whole band of the spectrum of the received ultrasonic signal. Since the available bandwidth can be determined adaptively using spectral histogram, this method can be used for automation of the SSP. In order to evaluate the determination technique of the available bandwidth using spectral histogram, this method is applied to experimental ultrasonic data. The experimental results show that the spectral histogram is an efficient method for determination of the available bandwidth and automation of the SSP.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.281-288
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• 2020

In this paper, we propose a control method to solve the surface hardness non-uniformity due to flow non-uniformity occurring in the heat treatment process of marine CAM. In the water cooling method including the decarbonization method, an automation device for deformation control has been developed and applied. LSTM was used to estimate the water cooling conditions, and the proposed method was found to be meaningful by improving the prototype results.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.267-280
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• 2022

Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.10
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• pp.1043-1049
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• 2012

The FEM analysis of machine tools is the general analysis process to evaluate machine performance in the industry for a long time. Despite advances in FEM software, because of difficult simplicity of CAD drawing, little experience of joints stiffness modeling and troublesome manual contact area divide for bindings, the industry designers think the FEM analysis is still an area of FEM analysis expert. In this paper, the automation of modeling process with simplicity of drawing, modeling of joints and contact area divide is aimed at easy FEM analysis to enlarge utilization of a virtual machine tools. In order to verify the effects of modeling automation, a slant bed type model with tilting table is analyzed. The results show FEM modeling automation method only needed 45 minutes to complete the whole modeling process, while manual modeling method requires almost one month with 8200 calculations for coordinate transformations and stiffness data input.

• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.179-192
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• 2015

In an automated industry PLC plays a central role to control the automation system. Therefore, fault free operation of PLC controlled automation system is essential in order to maximize a firm's productivity. A prior test of control system is a practical way to check fault operations, but it is a time consuming job and can not check all possible fault operation. A formal verification of PLC program could be a best way to check all possible fault situation. Tracing the history of the study on formal verification, we found three problems, the first is that a formal representation of PLC control system is incomplete, the second is a state explosion problem and the third is that the verification result is difficult to use for the correction of control program. In this paper, we propose a transformation method to reproduce the control system correctly in formal model and efficient procedure to verify and correct the control program using verification result. To demonstrate the proposed method, we provided a suitable case study of an automation system.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.