• Title/Summary/Keyword: Abnormal conditions

검색결과 766건 처리시간 0.026초

전력 HILs를 활용한 스마트 인버터의 LVRT 시험 (Low Voltage Ride Through Test for Smart Inverter in Power Hardware in Loop System)

  • Sim, Junbo
    • KEPCO Journal on Electric Power and Energy
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    • 제7권1호
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    • pp.101-105
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    • 2021
  • Encouragement of DER from Korean government with several policies boosts DER installation in power system. When the penetration of DER in the grid is getting high, loss of generation with break-away of DER by abnormal grid conditions should be considered, because loss of high generation causes abnormal low frequency and additional operations of protection system. Therefore, KEPCO where is Korean power utility is preparing improvement in regulations for DERs connected to the grid to support abnormal grid conditions such as low and high frequencies or voltages. This is called 'Ride Through' because the requirement is for DER to maintain grid connection during required periods when abnormal grid conditions occur. However, it is not easy to have a test for ride through capability in reality because emulation of abnormal grid conditions is not possible in real power system in operation. Also, it is not easy to have a study on grid effect when ride through capability fails with the same reason. PHILs (Power Hardware In the Loop System) makes it possible to analyze power system and hardware performance at once. Therefore, this paper introduces PHILs test methods and presents verification of ride through capability especially for low voltage grid conditions.

Experimental Realization of Matrix Converter Based Induction Motor Drive under Various Abnormal Voltage Conditions

  • Kumar, Vinod;Bansal, Ramesh Chand;Joshi, Raghuveer Raj
    • International Journal of Control, Automation, and Systems
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    • 제6권5호
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    • pp.670-676
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    • 2008
  • While the matrix converter has many advantages that include bi-directional power flow, a size reduction, a long lifetime, and sinusoidal input currents, it is vulnerable to the input voltage disturbances, because it directly exchanges the input voltage to the output voltage. So, in this paper, a critical evaluation of the effect of various abnormal voltage conditions like unbalanced power supply, balanced non-sinusoidal power supply, input voltage sags and short time blackout of power supply on matrix converter fed induction motor drives is presented. The operation under various abnormal conditions has been analyzed. For this, a 230V, 250VA three phase to three phase matrix converter (MC) fed induction motor drive prototype is implemented using DSP based controller and tests have been carried out to evaluate and improve the stability of system under typical abnormal conditions. Digital storage oscilloscope & power quality analyzer are used for experimental observations.

An Improved Service Restoration Algorithm under Consideration of Abnormal Conditions in Distribution Automation Systems

  • Cho, Namhun;Kim, Insung;Lee, Sungwoo
    • KEPCO Journal on Electric Power and Energy
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    • 제1권1호
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    • pp.47-54
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    • 2015
  • The most important function in distribution automation system (DAS) is the service restoration. KEPCO's current service restoration provides a very effective restoration service. However, it has been developed without the consideration of unexpected abnormal conditions that may occur while processing the sequence of switching operations. The objective of this paper is to provide practical service restoration schemes under consideration of abnormal conditions. The proposed service restoration schemes have been integrated to a branch office (B/O) in KEPCO. The proposed method strongly supports the conventional service restoration and adds to its value.

이상기후에 따른 농작물의 수확량 및 재해발생 확률의 추정 (Simulating Crop Yield and Probable Damage From Abnormal Weather Conditions)

  • 임상준;박승우;강문성
    • 한국농공학회지
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    • 제39권6호
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    • pp.31-40
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    • 1997
  • Potential impacts for unfavourable weather conditions and the assessment of the magnitudes of their adverse effects on crop yields were studied. EPIC model was investigated for its capability on crop yield predictions for rice and soybean. Weather generationmodel was used to generate long-term climatic data. The model was verified with ohserved climate data of Suwon city. Fifty years weather data including abnormal conditions were generated and used for crop yield simulation by EPIC model. Crop yield probability function was derived from simulated crop yield data, which followed normal distribution. Probable crop yield reductions due to abnormal weather conditions were also analyzed.

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Changes of Enzyme Activities and Compositions of Abnormal Fruiting Bodies Grown under Artificial Environmental Conditions in Pleurotus ostreatus

  • Jang, Kab-Yeul;Cho, Soo-Muk;June, Chang-Sung;Weon, Hang-Yeon;Park, Jeong-Sik;Choi, Sun-Gyu;Cheong, Jong-Chun;Sung, Jae-Mo
    • Mycobiology
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    • 제33권1호
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    • pp.30-34
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    • 2005
  • This study investigated the biochemical changes of abnormal fruiting bodies grown under artificial environmental conditions in P. ostreatus. Abnormal mushroom growth during cultivation damages the production of good quality mushroom. This study showed that different environmental conditions produced morphological changes in the fruiting bodies of P. ostreatus. The fruiting bodies with morphological changes were collected and examined for differences in biochemical properties, enzyme activities, and carbohydrates composition. The enzyme activities assay showed that glucanase and chitinase activities decreased when the temperature was below or above the optimum cultivation temperature for P. ostreatus. The biochemical compositions of the abnormal mushroom were significantly different from the normal fruiting bodies. It was suggested that the changes in the biochemical composition of abnormal mushroom were caused by the unfavorable environmental conditions during mushroom cultivation.

Abnormal behaviour in rock bream (Oplegnathus fasciatus) detected using deep learning-based image analysis

  • Jang, Jun-Chul;Kim, Yeo-Reum;Bak, SuHo;Jang, Seon-Woong;Kim, Jong-Myoung
    • Fisheries and Aquatic Sciences
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    • 제25권3호
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    • pp.151-157
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    • 2022
  • Various approaches have been applied to transform aquaculture from a manual, labour-intensive industry to one dependent on automation technologies in the era of the fourth industrial revolution. Technologies associated with the monitoring of physical condition have successfully been applied in most aquafarm facilities; however, real-time biological monitoring systems that can observe fish condition and behaviour are still required. In this study, we used a video recorder placed on top of a fish tank to observe the swimming patterns of rock bream (Oplegnathus fasciatus), first one fish alone and then a group of five fish. Rock bream in the video samples were successfully identified using the you-only-look-once v3 algorithm, which is based on the Darknet-53 convolutional neural network. In addition to recordings of swimming behaviour under normal conditions, the swimming patterns of fish under abnormal conditions were recorded on adding an anaesthetic or lowering the salinity. The abnormal conditions led to changes in the velocity of movement (3.8 ± 0.6 cm/s) involving an initial rapid increase in speed (up to 16.5 ± 3.0 cm/s, upon 2-phenoxyethanol treatment) before the fish stopped moving, as well as changing from swimming upright to dying lying on their sides. Machine learning was applied to datasets consisting of normal or abnormal behaviour patterns, to evaluate the fish behaviour. The proposed algorithm showed a high accuracy (98.1%) in discriminating normal and abnormal rock bream behaviour. We conclude that artificial intelligence-based detection of abnormal behaviour can be applied to develop an automatic bio-management system for use in the aquaculture industry.

AE에 의한 평면연삭의 가공특성 감시 및 이상진단 (Detection of abnormal conditions and monitoring of surface ginding characteristics by acoustic emission)

  • Lim, Y.H.;Kwon, D.H.;Choi, M.Y.;Lim, S.J.
    • 한국정밀공학회지
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    • 제12권4호
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    • pp.100-110
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    • 1995
  • This paper aims at reviewing the possibility of application over normal or abnormal, detection used by AE, and the characteristics of grinding processes. In this study, when WA-vitri-fied ' resinoid bond grinding wheels:36 kinds of grinding wheel and grinding depth were tuned at the surface grinding, the zone of AE signal generation is theoretically modelled and reviewed by grinding processes. The variation of grinding resistance( F$n^{9}$ $F_{t}$) and AE signal is detected in-process by the use of AE measuring system. The tests are carried out in accordance with grain size and grade of grinding wheels, and work-pieces-STD11 and STD61. According to the experiment's results, the following can be expected;as grinding time passes by, the relation of grinding depth and quantity of AE signal, observing on AE signal and grinding burn suggest the characteristics of grinding processes and evalution on the possibility of control of grinding machine, and monitoring abnormal conditions.e, and monitoring abnormal conditions.

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조명을 위한 인간 자세와 다중 모드 이미지 융합 - 인간의 이상 행동에 대한 강력한 탐지 (Multimodal Image Fusion with Human Pose for Illumination-Robust Detection of Human Abnormal Behaviors)

  • ;공성곤
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2023년도 추계학술발표대회
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    • pp.637-640
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    • 2023
  • This paper presents multimodal image fusion with human pose for detecting abnormal human behaviors in low illumination conditions. Detecting human behaviors in low illumination conditions is challenging due to its limited visibility of the objects of interest in the scene. Multimodal image fusion simultaneously combines visual information in the visible spectrum and thermal radiation information in the long-wave infrared spectrum. We propose an abnormal event detection scheme based on the multimodal fused image and the human poses using the keypoints to characterize the action of the human body. Our method assumes that human behaviors are well correlated to body keypoints such as shoulders, elbows, wrists, hips. In detail, we extracted the human keypoint coordinates from human targets in multimodal fused videos. The coordinate values are used as inputs to train a multilayer perceptron network to classify human behaviors as normal or abnormal. Our experiment demonstrates a significant result on multimodal imaging dataset. The proposed model can capture the complex distribution pattern for both normal and abnormal behaviors.

기존선에서 이상기후 발생시 열차안전운행 확보 방안 (The Measure of Safety Operation of Train under Abnormal Climate in Conventional line)

  • 김치태;이성욱;정도원;주창훈
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2006년도 추계학술대회 논문집
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    • pp.130-137
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    • 2006
  • In these days abnormal climate occurs frequently because of global warming and earthshock. So it is necessary to prepare for the abnormal conditions like gale, rainfall, heavy snow and high temperature. Fortunately, Korea high speed rail(KTX) have a safety climate detection system for the abnormal weather by using CTC. So the safety is guaranteed in most aspect. But in convention line there isn't any alarm system for the abnormal condition and the train runs until the railroad loss occurred. So convention line need additional regulation same as KTX for the abnormal climate and in the near future passenger safety must be protected by new alarm system.

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Oil Whip에 의한 터빈의 이상진동 (Abnormal Vibration of Turbine due to Oil Whip)

  • 구재량;황재현
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 추계학술대회논문집A
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    • pp.539-543
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    • 2001
  • Almost all rotating machinery has bearings. Bearing is one of the most important part of rotating machinery. Vibration of rotating machinery depend on its bearing conditions. Bearing conditions are followings ; oil gap, bearing type, bearing temperature, bearing oil condition. Especially, bearing oil condition influences on rotating machinery vibration directly. In this paper we have discussed the abnormal vibration of turbine due to oil condition. oil whip problem was occured in the certain power plant. and we had sloved this problem through the control of operating values and alignment.

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