• Nuclear Engineering and Technology
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• 제43권4호
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• 한국항행학회논문지
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• 제23권6호
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• pp.554-560
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• 2019

원전에서 각종 전자카드는 시간에 경과함에 따라 열화가 되므로 이에 대한 대책이 필요하다. 이 열화 카드들 중에서 노외중성자감시시스템의 카드들은 방사선원의 레벨에서 발생되는 중성자속을 총 원자로출력의 200%까지 연속적으로 감시하게 되는데, 원자로출력이 낮을 때의 경우와 높을 때의 경우의 출력감시신호처리 방법이 달라야 한다. 원자로 출력이 낮을 때는 대수적으로 발생되는 펄스신호를 선형적으로 계수하여 신호처처리를 해야 되지만, 원자로 출력이 커지게 되면 통계이론에 의한 방법으로 처리해야 정확한 값을 얻을 수 있기 때문이다. 이때 전자카드가 열화되는 것이 문제가 된다. 따라서, 본 연구에서는 저출력일 때와 고출력일 때의 신호처리 방법을 달리하여 일정한 기준에 의한 원자로의 출력레벨에서 이를 저출력에서 고출력으로 전환하기 위한 열화 입력선택회로를 개발하였다. 개발된 선택회로의 신뢰성을 확인하기 위하여 원전에서 사용되는 실제의 데이터값을 적용하여 테스트하였으며, 그 결과를 분석하여 선택회로의 정당성을 입증하였다.

• Biotechnology and Bioprocess Engineering:BBE
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• 제8권2호
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• pp.147-150
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• 2003

Water toxicity monitoring based on the continuous cultivation of Photobacterium phorphoreum is presented. Normally, after 10 days of operation, a dark variant, which emits no light, appears and dominates the population, resulting in a rapid decrease in bioluminescence. Therefore, to overcome this problem, a fluidized-bed reactor is used in which alginate-immobilized cells are grown and leaking cells are continuously released into the effluent Experimental results revealed that the dominance of dark variants was suppressed inside the immobilized beads, thereby mitigating the rapid loss of bioluminescence. Plus, a high dilution rate (1.2 h$\^$-1/) prevented the occurrence of other microbial contamination in the reactor The concentration and bioluminescence of the released cells were sufficient to measure the water toxicity for more than 4 weeks.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.900-907
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• 2008

All electric trains in the city should be run without any troubles of the equipments in order to offer good services to the passengers. But some breakdowns occur when they are operated due to the long time uses. There are mechanical troubles and electrical troubles included reactors. Most of them, the reason of the troubles can be found out easily after breakdown. But it is difficult to find out the reasons of the reactor troubles which disappear after operation. The reactors of the train filter the current which supplied from electrical lines and supply the current to the inverter and block the ripple of the current. Partial discharge occur from the reactor by the heat. accordingly, If the signals of discharge were perceived, it could be anticipate the deterioration degree of insulation. In this paper, on-monitoring system for reactor's troubles in trains is established and the output results of monitoring system are investigated.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• Nuclear Engineering and Technology
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• 제36권1호
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• pp.53-63
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• 2004

The research was performed to develop a CANDU-6 Core Monitoring System(CCMS) that enables operators to have efficient core management by monitoring core power distribution, burnup distribution, and the other important core variables and managing the past core history for Wolsong nuclear power plant unit 1. The CCMS uses Reactor Fueling Simulation Program(RFSP, developed by AECL) for continuous core calculation by integrating the algorithm and assumptions validated and uses the information taken from Digital Control Computer(DCC) for the purpose of producing basic input data. The CCMS has two modules; CCMS server program and CCMS client program. The CCMS server program performs automatic and continuous core calculation and manages overall output controlled by DataBase Management System. The CCMS client program enables users to monitor current and past core status in the predefined GUI(Graphic-User Interface) environment. For the purpose of verifying the effectiveness of CCMS, we compared field-test data with the data used for Wolsong unit 1 operation. In the verification the mean percent differences of both cases were the same($0.008\%$), which showed that the CCMS could monitor core behaviors well.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.804-809
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• 1988

PRNM(Power Range Neutron Monitoring) of BWR (Boiling Water Reactor) is a system that processes signals from about two hundred LPRM (Local Power Range Monitor) sensors in the nuclear reactor and this system monitors the neutron flux level during the plant operating region. Development has been made by employing a special technique for multiplexing neutron sensor signals and the recent advanced microelectronics technology. It is applicable to the total plant digital control system for a nuclear power plant.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.112-120
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• 2003

This paper reports the development work carried out in respect of a proposed application of Neural Network approach for the Korean Next generation Reactor (KNGR) now referred as APR-1400. The emphasis is on establishing the methodology and the approach to be adopted towards realizing this application in the next generation reactors. Keeping in view the advantages and limitation of Artificial Neural Network Approach, the role of ANN has been limited to plant status or to be more precise plant transient monitoring. The simulation work carried out so far and the results obtained shows that artificial neural network approach caters to the requirements of plant status monitoring and qualifies to be incorporated as a part of proposed operator support systems of the referenced nuclear power plant.

• 원자력산업
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• 제15권3호통권145호
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• pp.82-92
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• 1995