• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1108-1110
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• 2007

The resonant converters cause the high voltage stress according to the input voltage, which increases the conduction loss in converter power switches. The topology of LLC half bridge resonant converter provides ZVS characteristic and also the stress of voltage and current is smaller than that of the general resonant converters. So we can expect the higher efficiency. In this paper, the LLC resonant converter is designed for slim adapter. In the adapter design, we should consider the weight, the size and overheat of the adapter. Thus the optimal design of transformer is the most important facts. Some parameters should be considered in order to get the highest efficiency. The LLC resonant converter input is 390VDC Link voltage of PFC and the output has 16VDC/90W ratings. The efficiency measured is about up to 93%.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2017년도 추계학술대회
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• pp.113-114
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• 2017

본 논문은 모듈형 멀티레벨 컨버터를 이용한 특고압 직류 배전용 지능형 변압기의 운용을 위한 제어 기법을 제안한다. 기존의 저주파 변압기는 부피와 무게가 매우 크며 효율이 낮다는 단점을 갖는다. 이에 반해 다수의 IGBT를 사용하는 지능형 변압기는 시스템의 부피를 저감할 수 있으며 고효율 운영이 가능하다. 또한, 직류 배전 계통의 단락 사고가 발생하였을 때 직류 차단기의 역할이 가능하다. 본 논문에서는 지능형 변압기의 토폴로지, 변조 방법을 제시하고, 스위칭 및 출력 특성을 분석한다. 시뮬레이션을 통해 제안하는 지능형 변압기 운용 제어 기법의 타당성을 확인한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.965_966
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• 2009

In this paper, a new soft-switching Two-switch Forward converter topology has been proposed. Compared with conventional two-switch forward converter, the proposed converter employs an auxiliary switch and a clamp capacitor to instead of two reset diodes, not only its duty cycle can exceed 0.5 to achieve wide range input voltage, but also soft switching can be achieved for all switches. Especially, voltage stress across main switches can be clamped at $1/2V_{in}$, voltage stress across auxiliary switch can be clamped at $V_{in}$. In addition, due to clamp capacitor series with the transformer, duty ratio can be extended with equation $V_o=\frac{V_{in}(1-D}D{N}$. Therefore, as a kind of better cost-effective approach, it is very attractive for high input, wide range and high efficiency application.

• 전기학회논문지
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• 제60권11호
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• pp.2028-2034
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• 2011

Substation Automation System (SAS) based on IEC 61850 is becoming more and more reality in applying power systems. As well, the development of various engineering tools and the convergence with diagnostic systems are underway. To reflect recent advancements in SAS technology, the Korea Electric Power Corporation initiated a 154kV SAS pilot project and a smart power grid business in 2010. In this paper, the authors will summarize the overview and the lessons learned in applying the IEC 61850-based 154kV Main transformer bay IED solutions to these two project.

• ETRI Journal
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• 제44권2호
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.186-191
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• 2023

This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.

• Journal of Power Electronics
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• 제16권2호
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• pp.464-472
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• 2016

This study applies the selective harmonic elimination (SHE) technique to design and operate a regulated AC/DC/AC power supply suitable for maritime military applications and underground trains. The input is a single 50/60 Hz AC voltage, and the output is a 400 Hz regulated voltage. The switching angles for a multi-level inverter and transformer turns ratio are determined to operate with special connected transformers with equal power ratings and produce an almost sinusoidal current. As a result of its capability of directly controlling harmonics, the SHE technique is applicable to apparatus with congenital immunity to specific harmonics, such as series-connected transformers, which are specially designed to equally share the total load power. In the present work, a single-phase 50/60 Hz input source is rectified via a semi-controlled bridge rectifier to control DC voltage levels and thereby regulate the output load voltage at a constant level. The DC-rectified voltage then supplies six single-phase quazi-square H-bridge inverters, each of which supplies the primary of a single-phase transformer. The secondaries of the six transformers are connected in series. Through off-line calculation, the switching angles of the six inverters and the turns ratios of the six transformers are designed to ensure equal power distribution for the transformers. The SHE technique is also employed to eliminate the higher-order harmonics of the output voltage. A digital implementation is carried out to determine the switching angles. Theoretical results are demonstrated, and a scaled-down experimental 600 VA prototype is built to verify the validity of the proposed system.

• Smart Structures and Systems
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• 제30권6호
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• 한국전기전자재료학회논문지
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• 제35권6호
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• pp.594-602
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• 2022

Cast-resin transformers are widely installed in various electrical power systems because of their low operating cost and low influence on external environmental factors. However, when they have an internal defect during the manufacturing process or operation, a partial discharge (PD) occurs, and eventually destroys the insulation. In this paper, a Rogowski-type PD sensor was studied to replace commercial PD sensors used for the insulation diagnosis of power apparatus. The proposed PD sensor was manufactured with four different types of PCB-based winding structures, and it was analyzed in terms of the detection characteristics for standard calibration pulses and the changes of the output voltage according to the distance. The output increased linearly in accordance with the applied discharge amount. It was confirmed that the hexagon structure sensor had the highest sensitivity, because the winding cross-sectional area of the sensor was larger than others. In addition, as the distance from the defect increased, the output voltage of the sensors decreased by 7.32% on average. It was also confirmed that the attenuation rate according to the distance decreased as the input discharge amount increased. For the application of this new type sensor, PD electrode system was designed to simulate the void defect. Waveforms and PRPD patterns measured by the proposed PD sensors at DIV and 120% of DIV were the same as the results measured by MPD 600 based on IEC 60270. The proposed PD sensors can be installed on the inner wall of the transformer tank by coating its surfaces with a non-conductive material; therefore, it is possible to detect internal defects more effectively at a closer distance from the defect than the conventional sensors.

• Smart Structures and Systems
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• 제32권1호
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• pp.23-35
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• 2023

Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department.