• 제목/요약/키워드: Power Detection System

검색결과 1,402건 처리시간 0.028초

초기화재 감지를 위한 정밀한 연기 입자 감지 장치 개발 (Development of a precision smoke particle detector to sense a fire in early state)

  • 김희식;김영재;이호재
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1734-1737
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    • 1997
  • The conventional fire detection devices are operated after a processed fire phase, which are sensing only a high density of somke level or high temperature heat. They are not so precision to detect a fire in the early phase to protect the facility form the fire. We need to develope a new high precision smoke detection system to keep expensive industrial facilities most reliably form fire. A new optical precision smoke detection system was developed. It monitors very low level density of smoke particles in the air. It is operated continously through many years without a stop or any malfunction. The developed precision smoke detection system will be installed in important industrial facilities, such as power plants, underground common tunnel, main control rooms, computer rooms etc.

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연기농도 계측용 광학식 미세입자 감지장치 개발

  • 김영재;김희식
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 춘계학술대회 논문집
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    • pp.128-132
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    • 1997
  • The conventional fire detection devices are operated after a processed fire phase, which are sensing only a high density of smoke level or high temperature heat. They are not so precision to detect a fire in the early phase to protect the facility from the fire. We need to develope a new high precision smoke detection system to keep expensive industial facilities most reliably from fire. A new optical precision smoke detection system was developed. It monitors very low level density of smoke psrticles in the air. It is operated continuously through many years without a stop or any malfunction. The developed precision smoke detection system will be installed in important industrial facilities,such as power plants, underground common tunnel,main control rooms,computer rooms etc.

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Joint Detection Method for Non-orthogonal Multiple Access System Based on Linear Precoding and Serial Interference Cancellation

  • Li, Jianpo;Wang, Qiwei
    • Journal of Information Processing Systems
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    • 제17권5호
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    • pp.933-946
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    • 2021
  • In the non-orthogonal multiple access (NOMA) system, multiple user signals on the single carrier are superimposed in a non-orthogonal manner, which results in the interference between non-orthogonal users and noise interference in the channel. To solve this problem, an improved algorithm combining regularized zero-forcing (RZF) precoding with minimum mean square error-serial interference cancellation (MMSE-SIC) detection is proposed. The algorithm uses RZF precoding combined with successive over-relaxation (SOR) method at the base station to preprocess the source signal, which can balance the effects of non-orthogonal inter-user interference and noise interference, and generate a precoded signal suitable for transmission in the channel. At the receiver, the MMSE-SIC detection algorithm is used to further eliminate the interference in the signal for the received superimposed signal, and reduce the calculation complexity through the QR decomposition of the matrix. The simulation results show that the proposed joint detection algorithm has good applicability to eliminate the interference of non-orthogonal users, and it has low complexity and fast convergence speed. Compared with other traditional method, the improved method has lower error rate under different signal-to-interference and noise ratio (SINR).

전력계토의 불량데이타 검출에서의 신경회로망 응용에 관한 연구 (Neural Nerwork Application to Bad Data Detection in Power Systems)

  • 박준호;이화석
    • 대한전기학회논문지
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    • 제43권6호
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    • pp.877-884
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    • 1994
  • In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

변전소 상태추정 및 고장 측정기기의 검정 시뮬레이터에 관한 연구 (A Study on the Substation Simulator for the State Estimation and the Bad Measuring Devices Detection)

  • 이흥재;왕인수;김용한;박성민;강현재
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.116-118
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    • 2000
  • The modern power system including lots of measuring devices and controller is large and complex total information system. A Lot of data and system information are transmitted to operators, and analysing these information and system management is very important. Recently, GUI(Graphic Users Interface) is emphasized as a method that operators carry out their duties, effectively. In this paper. a simulator that can show state estimation and detection of bad measuring devices is introduced for domestic 154kV/22.9kV distribution substations. C language and Visual Basic is used for this simulator. and TCP/IP is adopted to consider connection with a Power system.

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반복 이산 웨이브릿 변환을 이용한 주파수 추정 기법 (Frequency Estimation Technique using Recursive Discrete Wavelet Transform)

  • 박철원
    • 전기학회논문지P
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    • 제60권2호
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    • pp.76-81
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    • 2011
  • Power system frequency is the main index of power quality indicating an abnormal state and disturbances of systems. The nominal frequency is deviated by sudden change in generation and load or faults. Power system is used as frequency relay to detection for off-nominal frequency operation and connecting a generator to an electrical system, and V/F relay to detection for an over-excitation condition. Under these circumstances, power system should maintain the nominal frequency. And frequency and frequency deviation should accurately measure and quickly estimate by frequency measurement device. The well-known classical method, frequency estimation technique based on the DFT, could be produce the gain error in accuracy. To meet the requirements for high accuracy, recently Wavelet transforms and analysis are receiving new attention. The Wavelet analysis is possible to calculate the time-frequency analysis which is easy to obtain frequency information of signals. However, it is difficult to apply in real-time implementation because of heavy computation burdens. Nowadays, the computational methods using the Wavelet function and transformation techniques have been searched on these fields. In this paper, we apply the Recursive Discrete Wavelet Transform (RDWT) for the frequency estimation. In order to evaluate performance of the proposed technique, the user-defined arbitrary waveforms are used.

Detection of Voltage Sag using An Adaptive Extended Kalman Filter Based on Maximum Likelihood

  • Xi, Yanhui;Li, Zewen;Zeng, Xiangjun;Tang, Xin
    • Journal of Electrical Engineering and Technology
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    • 제12권3호
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    • pp.1016-1026
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    • 2017
  • An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

다양한 조명 환경에서의 실시간 사용자 검출을 위한 압축 영역에서의 색상 조절을 사용한 얼굴 검출 방법 (Face detection in compressed domain using color balancing for various illumination conditions)

  • 민현석;이영복;신호철;임을균;노용만
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2009년도 학술대회
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    • pp.140-145
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    • 2009
  • 본 논문에서는 압축 영역에서 동작하는 조명 환경 변화에 강인한 얼굴 검출 방법을 제안한다. 기존 이미지 처리를 이용한 얼굴 검출 방법들은 주로 픽셀 기반 영역에서 이루어져 왔다. 그러나 컴퓨팅 파워와 저장 공간이 제한적인 로봇 환경에는 픽셀 기반 처리가 적합하지 않다. 또한 조명 환경의 변화는 안정된 얼굴 검출을 위해 해결되어야 하는 문제로 인식되어 왔다. 이러한 문제점들을 해결하기 위하여 본 논문에서는 압축 영역에서의 조명 효과 보상과 색 온도 변환을 이용한 색상 정보 조절 과정을 사용한 얼굴 검출 방법을 제안한다. 제안된 방법은 색상 정보 조절을 통하여 다양한 조명 환경에서 기존 방법에 비해 강인한 얼굴 검출을 보여준다.

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DC 정류기 부분방전 신호검출을 위한 SHF 센서의 성능평가 (Performance Evaluation of SHF Sensor for Partial Discharge Signal Detection on DC Rectifier)

  • 정호성;박영;나희승;장순호
    • 전기학회논문지
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    • 제61권7호
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    • pp.1056-1060
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    • 2012
  • Online monitoring system is becoming an essential element of railway traction system for utilized to condition based malignance management and various techniques currently employed in railway traction system. Among the various techniques, it is efficient to detect partial discharge signals by electromagnetic wave detection in order to detect insulation fault of rectifier. Although VHF (Very High Frequency), UHF (Ultra High Frequency) sensors were adopted to detect partial discharge of power facilities, due to characteristics of urban railway, excessive noise occurs from 500 MHz to 1.5 GHz on UHF bandwidth. In this paper a new measurement system able to monitoring the conditions of power facilities on DC substation in metro was studied and set up. The system uses UHF sensors to measure the partial discharge of the rectifier due to electric faulting and dielectric breakdown. Comparison and estimation for performance of SHF sensor which had devised to detect partial discharge signal of urban railway rectifier has conducted. In order to estimate performance of SHF sensor, we have compared the sensor with existing UHF sensor on sensitivity upon frequency bandwidth generated by pulse generator, and also we have verified performance of the SHF sensor by detection results of partial discharge signal from urban railway rectifier.

음향반응에 의한 계란의 크랙검출에 관한 연구 (Crack Detection in Eggshell by Acoustic Responses)

  • 조한근;최완규;백진하
    • Journal of Biosystems Engineering
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    • 제23권1호
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    • pp.67-74
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    • 1998
  • A nondestructive quality inspection technique using acoustic impulse response method was developed for eggshell inspection. An experimental system was built to generate the impact force, to measure the response signal and to analyze the frequency spectrum. This system includes an impulse generating unit, an egg holding seal a microphone with preamplifier, and a DSP board installed on Personal Computer. A simple algorithm .was developed for crack detection. Using the developed system with algorithm, crack detection ability was evaluated and the error rate to estimate the normal egg as cracked was found to be 4% and the error rate to estimate the cracked egg as normal was also found to be 4%. This system could be adopted in industry with some modification.

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