• 전력전자학회논문지
• /
• 제23권6호
• /
• pp.403-407
• /
• 2018

This study proposes a predictive direct power control method in a modular multilevel converter (MMC) high-voltage direct-current (HVDC) system. The conventional proportional integral (PI)-based control method uses a cascaded connection and requires an optimal gain selection procedure and additional decoupling scheme. However, the proposed control method has a simple structure for active/reactive power control due to the direct power control scheme and exhibits a fast dynamic response by predicting the future status of system variables and considering time delay. The effectiveness of the proposed method is verified by simulation results.

• 전기학회논문지
• /
• 제59권7호
• /
• pp.1276-1281
• /
• 2010

To analyze the gas discharge phenomena in parallel-plane electrodes, the fully coupled finite element method (FEM) considering secondary electron emission effects in discharge column was adopted in this paper. Two coupled equations of the hydrodynamic diffusion-drift equations for three carriers and the Poisson's equation for electric scalar potential should be solved as a system equation. The proposed method including two secondary electron processes of the photoemission and background ionization has been successfully applied to evaluating the breakdown voltage in parallel-plane electrodes and is verified by comparing its numerical results with the experimental ones. From the obtained results, it is inferred that the proposed numerical scheme will be useful for predicting and understanding streamer transient phenomena.

• International Journal of Korean Welding Society
• /
• 제1권2호
• /
• pp.36-44
• /
• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 C
• /
• pp.1088-1090
• /
• 1999

The radio noise produced by corona discharge in high voltage transmission tines is one of the most important line design considerations. Therefore it is necessary to pre-evaluate radio noise for transmission line designers using Prediction formulas or field test results. In this Paper, more accurate and useful formulas for Predicting radio noise during fair and foul weathers in AC transmission lines were proposed through comparison with the existing formulas. Also it was verified by comparing with the long-term measured data from operating lines that the Proposed formulas are very accurate. The Proposed prediction formulas are developed by the applications of nonlinear least square optimization method to radio noise database collected from lines throughout the world.

• Journal of Electrochemical Science and Technology
• /
• 제11권4호
• /
• pp.346-351
• /
• 2020

The removal characteristics of copper (Cu) from electrochemical surface by voltage-activated reaction were reviewed to assess the applicability of electrochemical-mechanical polishing (ECMP) process in three types of electrolytes, such as HNO₃, KNO₃ and NaNO₃. Electrochemical surface conditions such as active, passive, transient and trans-passive states were monitored from its current-voltage (I-V) characteristic curves obtained by linear sweep voltammetry (LSV) method. In addition, the oxidation and reduction process of the Cu surface by repetitive input of positive and negative voltages were evaluated from the I-V curve obtained using the cyclic voltammetry (CV) method. Finally, the X-ray diffraction (XRD) patterns and energy dispersive spectroscopy (EDS) analyses were used to observe the structural surface states of a Cu electrode. The electrochemical analyses proposed in this study will help to accurately control the material removal rate (MRR) from the actual ECMP process because they are a good methodology for predicting optimal electrochemical process parameters such as current density, operating voltage, and operating time before performing the ECMP process.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1993년도 추계학술대회 논문집
• /
• pp.482-487
• /
• 1993

A prediction method for determining the welding residual stress by artificial neural network is proposed. A three-dimensional transient thermomechanical analysis has been performed for the CO $_{2}$ Arc Welding using the finite element method. The validity of the above results is demonstrated by experimental elastic stress relief method which is called Holl Drilling Method. The first part of numarical analysis performs a three-dimensional transient heat transfer anslysis, and the second part then uses results of the first part and performs a three-dimensional transient thermo-clasto-plastic analysis to compute transient and residual stresses in the weld. Data from the finite element method were used to train a backpropagation neural network to predict residual stress. Architecturally, the finite element method were used to train a backpropagation voltage and the current, a hidden layer to accommodate failure mechanism mapping, and an output layer for residual stress. The trained network was then applied to the prediction of residual stress in the four specimens. The results of predicted residual stress have been very encouraging.

• 대한조선학회논문집
• /
• 제56권6호
• /
• pp.473-479
• /
• 2019

Welding is one of the most popular joining methods and most welding quality estimation methods are executed using joined material. This paper propose welding quality estimation methods using dynamic current, voltage and resistance which are obtained during welding in real time. There are many kinds of welding method. Among them, we focused on the projection welding and gathered dynamic characteristics from two different types of projection welding. For image learning, graphs are drawn using obtained current, voltage and resistance, and the graphs are converted to images. The images are labeled with two sub-categories - normal and defect. For deep learning of images obtained from welding, Convolutional Neural Network (CNN) is applied, and Tensorflow was used as a framework for deep learning. With two resistance welding test datasets, we conclude that the Convolutional Neural Network helps in predicting the welding quality.

• Journal of Welding and Joining
• /
• 제17권4호
• /
• pp.39-45
• /
• 1999

The procedure of robotic Gas metal Arc (GMA) welding in order to achieve the optimized bead geometry needs the selection of suitable process parameters such as arc current, welding voltage, welding speed. It is required the relationships between process parameters and bead geometry. The objective of this paper is to develop the algorithm that enables the determination of process parameters from the optimized bead geometry for robotic GMA welding. It depends on the inversion of empirical equations derived from multiple regression analysis of the relationships between the process parameters and the bead dimensions using the least square method. The method not only directly determines those parameters which will give the desired set of bead geometry, but also avoids the need to iterate with a succession of guesses employed Finite Element Method(FEM). These results suggest that process parameter from experimental equation for robotic GMA welding may be employed to monitor and control the bead geometry in real time.

• 융복합기술연구소 논문집
• /
• 제11권1호
• /
• pp.33-37
• /
• 2021

The application of multicopters using a battery is limited by the short endurance due to the low energy density. A propeller is one of crucial components that determine the performance of the multicopter. In the present study, a systematic method for predicting the endurance of multicopters is described. Propeller performance database are constructed using the data from UIUC Propeller Data Site. Using the 'trendline' function of MS Excel software, the performance of the commercial propellers are represented as a function of polynomials. The multicopter's endurance is computed iteratively using Peukert's Law and considering the voltage drop effect. We evaluated the endurance of multicopters that use commercial propellers. The endurance of the multicopter was within the range of 28 min. to 36 min. It is expected that the present method can be utilized for optimal propeller selection for the given multicopters.

• Journal of Power Electronics
• /
• 제4권2호
• /
• pp.102-111
• /
• 2004

This paper is concerned with a deadbeat current control implementation of shunt-type three-phase active power filter (APF). Although the one-dimensional deadbeat control method can attain time-optimal response of APF compensating current, one sampling period is actually required fur its settling time. This delay is a serious drawback for this control technique. To cancel such a delay and one more delay caused by DSP execution time, the desired APF compensating current has to be predicted two sampling periods ahead. Therefore an adaptive predictor is adopted for the purpose of both predicting the control error of two sampling periods ahead and bringing the robustness to the deadbeat current control system. By adding the adaptive predictor output as an adjustment term to the reference value of half a source voltage period before, settling time is made short in a transient state. On the other hand, in a steady state, THD (total harmonic distortion) of the utility grid side AC source current can be reduced as much as possible, compared to the case that ideal identification of controlled system could be made.