• Nuclear Engineering and Technology
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• 제55권2호
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• 전기학회논문지
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• 제57권3호
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• pp.398-402
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• 2008

Recently, the development of superconducting fault current limiters (SFCLs) has been required as power demands increase in the power system. A distribution-level prototype resistive SFCL using coated conductor (CC) has been developed by Hyundai Heavy Industries Co., Ltd. and Yonsei University for the first time in the world. The ratings of the SFCL are 13.2kV/630A at normal operating condition. A novel non-inductive winding method is used in fabricating coils so there is almost zero impedance during normal operation. The distribution SFCL is cooled by sub-cooled liquid nitrogen $(LN_2)$ of 65K and 3 bar to enhance cryo-dielectric performance, critical current density, and thermal conductivity. In order to make reliable operation of an SFCL in real power systems, we monitored and controled its operation conditions by using supervisory control and data acquisition (SCADA) method. Thus, a monitoring system for the SFCL employing information technology (IT) is proposed and developed to be on the lookout for the operation conditions such as inside temperature, inside pressure, $LN_2$ level, voltage and current. Since operation temperature should be kept constant, bang-bang control for temperature feedback with a heater attached to the cold head of cryo-cooler is applied to the system. Short-circuit tests with prospective fault current of 10kA and AC dielectric withstand voltage tests up to 143kV for 1 minute were successfully performed at Korea Electrotechnology Research Institute. This paper deals with the development of a distribution level SFCL and its monitoring system for reliable operation.

• 전기학회논문지P
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• 제60권3호
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• pp.114-119
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• 2011

Large Power transformer is a complex and critical component of power plant and consists of cellulosic paper, insulation oil, core, coil etc. Insulation materials of transformer and related equipment break down to liberate dissolved gas due to corona, partial discharge, pyrolysis or thermal decomposition. The dissolved gas kinds can be related to the type of electrical faults, and the rate of gas generation can indicate the severity of the fault. The identities of gases being generated are using very useful to decide the condition of transformation status. Therefore dissolved gas analysis is one of the best condition monitoring methods for power transformer. Also, on-line multi-gas analyzer has been developed and installed to monitor the condition of critical transformers. Rogers method, IEC method, key gas method and Duval Triangle method are used to failure diagnosis typically, and those methods are using the ratio or kinds of dissolved gas to evaluate the condition of transformer. This paper analyzes the reliability of transformer diagnostic methods considering actual dissolved gas concentration. Fault diagnosis is performed based on the dissolved gas of five transformers which experienced various fault respectively in the field, and the diagnosis result is compared with the actual off-line fault analysis. In this comparison result, Diagnostic methods using dissolved gas ratio like Rogers method, IEC method are sometimes fall outside the ratio code and no diagnosis but Duval triangle method and Key gas method is correct comparatively.

• 한국태양에너지학회 논문집
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• 제38권3호
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• pp.21-28
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• 2018

The objects of PV (Photovoltaic) monitoring system is to reduce the loss of system and operation and maintenance costs. In case of PV plants with configured of centralized inverter type, only 1 PV module might be caused a large loss in the PV plant. For this reason, the monitoring technology of PV module-level that find out the location of the fault module and reduce the system losses is interested. In this paper, a fault diagnosis algorithm are proposed using thermal and electrical characteristics of PV modules under failure. In addition, the monitoring system applied with proposed algorithm was constructed. The wireless sensor using LoRa chip was designed to be able to connect with IoT device in the future. The characteristics of PV module by shading is not failure but it is treated as a temporary failure. In the monitoring system, it is possible to diagnose whether or not failure of bypass diode inside the junction box. The fault diagnosis algorithm are developed on considering a situation such as communication error of wireless sensor and empirical performance evaluation are currently conducting.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.462-465
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• 1988

In this paper, it is described that digital back-up control system is developed and applied to the thermal power boiler control system which consists of many kinds of analog electronic cards. Also, by the installation of this system in ulsan power pllant, it was proven to have excellent capabilities of fault detection and digital back-up control.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2001년도 추계학술대회 논문집
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• pp.459-466
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• 2001

As the Public use part of the railway and the road, the railway crossing is important to work properly by two transportation means. Also, It is important to provide the good face of friction on the railway crossing in aspect of protecting the railway crossing accident. Lately, the material of railway crossing panel is the wood, the asphalt, and the steel. As they have a various fault, it was studied to analyze the structural action of the new material, rubber panel. This paper analyzed eigenvalue, stress and displacement by truck passing weight, thermal stress and train moving weight, using the FEM model.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(D)
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• pp.369-371
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• 2012

Wireless sensor networks have taken immense interest in healthcare systems in recent years. One example of it is in an in vivo sensor that is deployed in critical and sensitive healthcare applications like artificial retina, cardiac pacemaker, drug delivery, blood pressure, internal heat calculation, glucosemonitoring etc. In vivo sensor nodes exhibit temperature that may be very dangerous for human tissues. However, existing in vivo thermal aware routing approaches suffer from hotspot creation, delay, and computational complexity. These limitations motivate us toward an in vivo virtual backbone, a small subset of nodes, connected to all other nodes and involved in routing of all nodes, -based solution. A virtual backbone is lightweight and its fault-tolerant version allows in vivo sensor nodes to disconnect hotspot paths and to use alternative paths. We have formulated the problem as m-connected k-dominating set problem with minimum temperature cost in in vivo sensor network. This is a combinatorial optimization problem and we have been motivated to use evolutionary approach to solve the problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.301-304
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• 2001

This paper considers the research of the hybrid interrupter which adopts both rotating arc and thermal expansion technology. The operating principle of this device defends on rapid arc rotation due to the magnetic field created by the fault current through a coil which is mounted on contacts and also relies on the principle of thermal expansion created by arc energy in extinguishing chamber and finally causes pressure rise in expansion volume. In this research, the principle of the interrupting techniques are given and experimental results of hybrid interrupter which is developed by new technology is introduced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.624-626
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• 1999

실제 공정상에서는 웨이퍼에 열을 가하는 공정뿐만 아니라 다른 형태의 여러 공정도중에도 다양한 종류의 예측 불가능한 고장 또는 기기의 오동작이 발생할 수 있으며 이는 고속열처리장비(RTP)의 throughput과 수율에 심각한 영향을 미치고 있다. 따라서 RTP 공정의 일부분뿐만 아니라 전체 공정에서의 장비의 상태변화를 기반으로 성능인자를 향상시킬 수 있는 modeling기법의 구축이 절실하다. 각각의 에러 수준과 발생 빈도에 의해서 시스템의 동작과 성능이 결정되며 높은 신뢰도(reliability)가 요구되는 시스템일수록 필수적으로 모든 부분의 기능 및 동작상태를 고려한 모델링이 선행되어야 한다. 그러나 시스템의 많은 부분은 분석 및 실험을 바탕으로 한 정확한 상태 방정식을 구할 수 없으므로 추상적이고 개념적인 상태변화 또한 전체 모델링에 포함시킬 수 있는 효율적인 기법이 필요하다. 이에 본 논문은 DES 모델링 기법을 사용하여 RTP의 동작 운용상태를 모델링하고 이를 통해 적절한 성능평가를 하고, 이를 컴퓨터 모의실험을 통해 검증하는 것을 주된 연구내용으로 한다.

• 설비공학논문집
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• 제22권5호
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• pp.275-281
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• 2010

Car HVAC is one of main factors influencing a potential customer's first impression. It should be fault-free, which requires the most stable control performance. So, the control algorithm consists of a proportional feedback only, not with an integral action needed for elimination of steady-state errors. To reduce the errors and make the response faster, feedforward algorithm based on predicted thermal load is added. To evaluate the performance, car HVAC is dynamically modelled and its control logic is simulated. The results shows that the proportional feedback leads to about $4^{\circ}C$ of steady-state error. When the feedback is combined with the feedforward algorithm and with a set value update based on disturbances, it predicts less than $1^{\circ}C$ of control error and improved thermal comfort.