• 제목/요약/키워드: Transformer Model

검색결과 584건 처리시간 0.025초

The study of Method for the Diagnosis of Transformers Trouble

  • Song, Jae-Tae;Jeong, Seung-Cheol;Choi, Hyun-Seob;Park, Poo-Gyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.118.1-118
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    • 2001
  • In this paper, we suggest a new distribution model for a single phase transformer which is different from the existing model which was modeled for only primary parts, but new distribution model is modeled for primary and secondary parts. Using this model, we simulate various faults of the transformer to know how the transfer function vary from the normal one, i.e., the trend of the variation of transfer function. As an another approach, we measure the voltage and current of a three phase transformer while various faults are made at the transformer. From the simulation of the model and experiment, we fine some trends of the variation of transfer function.

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변압기 부분방전 상시 감시기법에 관한 연구 (A Study on the on Line Monitoring Techniques of the Partial Discharge for Transformer)

  • 권동진;박재준
    • 한국전기전자재료학회논문지
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    • 제14권12호
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    • pp.1032-1040
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    • 2001
  • In order to apply the partial discharge measuring technique utilizing electrical pulse to the transformer at sites, this paper describes the measuring technique obtaining only the signals due to internal partial discharge in the transformer, but the noises due to external corona which has been a major problem so far. At first, partial discharge and corona noise were simultaneously generated in the model transformer by using needle-plane electrodes and rod-sphere electrodes out of it in a high voltage laboratory, respectively. It was verified that only the partial discharge signals in the transformer could be measured by removing the noise signals from the superposed signals of partial discharges and noises on the grounding wire of the model transformer. By application to a 345kV transformer in service, it was also confirmed that the partial discharge could be on-line monitored by removing the noise signals measured by the inductance sensor on the grounding wire of a 154kV lightning arrester from the superposed signals of internal partial discharge and external corona noise measured by bushing tap coupler of the transformer.

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PSCAD를 이용한 전력용 변압기 모델링과 과도 해석 (Power Transformer Modeling and Transient Analysis using PSCAD)

  • 박철원
    • 전기학회논문지P
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    • 제65권2호
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    • pp.122-129
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    • 2016
  • Current differential protection relaying with second harmonic restraint is the main protection for large capacity power transformer. PSCAD simulation program is widely used for modeling of dynamic varying transients phenomena. This paper deals with a power transformer model and transients analysis using PSCAD software to develop IED for power transformer. Simulation was carried out using a three phase 40MVA, 154/22.9kV, 60Hz, two-winding transformer with Y-Y connection used in actual fields. The paper analyzed transformer magnetizing inrush, external fault, and internal fault conditions with this model in the time domain. In addition, we performed an analysis in the frequency domain using FFT during several conditions.

Improving Transformer with Dynamic Convolution and Shortcut for Video-Text Retrieval

  • Liu, Zhi;Cai, Jincen;Zhang, Mengmeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권7호
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    • pp.2407-2424
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    • 2022
  • Recently, Transformer has made great progress in video retrieval tasks due to its high representation capability. For the structure of a Transformer, the cascaded self-attention modules are capable of capturing long-distance feature dependencies. However, the local feature details are likely to have deteriorated. In addition, increasing the depth of the structure is likely to produce learning bias in the learned features. In this paper, an improved Transformer structure named TransDCS (Transformer with Dynamic Convolution and Shortcut) is proposed. A Multi-head Conv-Self-Attention module is introduced to model the local dependencies and improve the efficiency of local features extraction. Meanwhile, the augmented shortcuts module based on a dual identity matrix is applied to enhance the conduction of input features, and mitigate the learning bias. The proposed model is tested on MSRVTT, LSMDC and Activity-Net benchmarks, and it surpasses all previous solutions for the video-text retrieval task. For example, on the LSMDC benchmark, a gain of about 2.3% MdR and 6.1% MnR is obtained over recently proposed multimodal-based methods.

Swin Transformer를 이용한 항공사진에서 다중클래스 차량 검출 (The Detection of Multi-class Vehicles using Swin Transformer)

  • 이기춘;정유석;이창우
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.112-114
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    • 2021
  • 도시 상태를 탐지하기 위해서는 운송 수단 수, 교통 흐름등이 필수적으로 파악되어야 할 요소이다. 본 논문에서는 기존의 Mask R-CNN을 이용하여 다양한 차량의 형태를 학습하고, 드론으로 촬영한 도시항공 영상에서 특정 유형의 차량 들을 검출하는 시스템을 오늘날 NLP 분야에서 널리 쓰이게 된 Transformer 모델을 컴퓨터 비전 문제에 도입하여 기존의 컨볼루션 신경망보다 높은 성능을 보여준 Swin Transformer 모델을 이용하여 기존의 연구에서 보여주었던 검출 시스템 능력을 향상시켰다.

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Vision Transformer를 활용한 비디오 분류 성능 향상을 위한 Fine-tuning 신경망 (Fine-tuning Neural Network for Improving Video Classification Performance Using Vision Transformer)

  • 이광엽;이지원;박태룡
    • 전기전자학회논문지
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    • 제27권3호
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    • pp.313-318
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    • 2023
  • 본 논문은 Vision Transformer를 기반으로 하는 Video Classification의 성능을 개선하는 방법으로 fine-tuning를 적용한 신경망을 제안한다. 최근 딥러닝 기반 실시간 비디오 영상 분석의 필요성이 대두되고 있다. Image Classification에 사용되는 기존 CNN 모델의 특징상 연속된 Frame에 대한 연관성을 분석하기 어렵다는 단점이 있다. 이와 같은 문제를 Attention 메커니즘이 적용된 Vistion Transformer와 Non-local 신경망 모델을 비교 분석하여 최적의 모델을 찾아 해결하고자 한다. 또한, 전이 학습 방법으로 fine-tuning의 다양한 방법을 적용하여 최적의 fine-tuning 신경망 모델을 제안한다. 실험은 UCF101 데이터셋으로 모델을 학습시킨 후, UTA-RLDD 데이터셋에 전이 학습 방법을 적용하여 모델의 성능을 검증하였다.

Transformer Core Model and Parameter Estimation for ATP

  • Cho Sung-Don
    • KIEE International Transactions on Power Engineering
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    • 제5A권4호
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    • pp.385-389
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    • 2005
  • Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Transformer modeling is not a mature field and newer improved models must be made available in ATP packages. Further, there is a lack of published guidance on recommended modeling approaches. And there is typically not enough detailed design or test information available to determine the parameters for a given model. The purpose of this paper is to develop improved transformer core models for ATP and parameter estimation methods that can efficiently utilize the limited available information such as factory test reports.

제어알고리즘 개발을 위한 변압기 냉각시스템의 수학적모델 (Mathematical Models of a Transformer Cooling System for the Control Algorithm Development)

  • 한도영;노희전
    • 설비공학논문집
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    • 제22권2호
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    • pp.70-77
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    • 2010
  • In order to improve the efficiency of a main transformer in a train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include static and dynamic models of a main transformer, an oil pump, an oil cooler, and a blower. Static models were used to find optimal oil temperatures of the inlet and the outlet of a transformer. Dynamic models were used to predict transient performances of control algorithms of a blower and an oil pump. Simulation results showed good predictions of the static and the dynamic behavior of a main transformer cooling system. Therefore, mathematical models developed in this study may be effectively used for the development of control algorithms of a main transformer cooling system.

Sequence dicriminative training 기법을 사용한 트랜스포머 기반 음향 모델 성능 향상 (Improving transformer-based acoustic model performance using sequence discriminative training)

  • 이채원;장준혁
    • 한국음향학회지
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    • 제41권3호
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    • pp.335-341
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    • 2022
  • 본 논문에서는 기존 자연어 처리 분야에서 뛰어난 성능을 보이는 트랜스포머를 하이브리드 음성인식에서의 음향모델로 사용하였다. 트랜스포머 음향모델은 attention 구조를 사용하여 시계열 데이터를 처리하며 연산량이 낮으면서 높은 성능을 보인다. 본 논문은 이러한 트랜스포머 AM에 기존 DNN-HMM 모델에서 사용하는 가중 유한 상태 전이기(weighted Finite-State Transducer, wFST) 기반 학습인 시퀀스 분류 학습의 네 가지 알고리즘을 각각 적용하여 성능을 높이는 방법을 제안한다. 또한 기존 Cross Entropy(CE)를 사용한 학습방식과 비교하여 5 %의 상대적 word error rate(WER) 감소율을 보였다.

3차 권선을 고려한 단상 33MVA 고온초전도 변압기의 개념설계 (Conceptual Design of a Single Phase 33 MVA HTS Transformer with a Tertiary Winding)

  • 이승욱;김우석;한송엽;황영인;최경달
    • Progress in Superconductivity
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    • 제7권2호
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    • pp.162-166
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    • 2006
  • We have proposed a 3 phase, 100 MVA, 154 kV class HTS transformer substituting for a 60 MVA conventional transformer. The power transformer of 154 kV class has a tertiary winding besides primary and secondary windings. So the HTS transformer should have the 3rd superconducting winding. In this paper, we designed conceptually the structure of the superconducting windings of a single phase 33 MVA transformer. The electrical characteristics of the HTS transformer such as % impedance and AC loss vary with the arrangement of the windings and gaps between windings. We analyzed the effects of the winding parameters, evaluated the cost of each design, and proposed a suitable HTS transformer model for future power distribution system.

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