• 제목/요약/키워드: Clarke Transformation

검색결과 5건 처리시간 0.02초

Clarke법과 위상면궤적을 이용한 고저항 지락사고의 판별에 관한 연구 (A Study on the Classification of High Impedance Faults using Clarke Transformation and Plane Trajectory Method)

  • 김철환;신영철;안상필
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.243-245
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    • 2001
  • This paper presents a new classification method for high impedance faults in power systems. Results of phase plane trajectory with Clarke modal transformation using postfault current and voltage are utilized to classify types of arcing faults. The performance of the proposed method is tested on a typical 154 kV korean transmission system under various fault conditions using EMTP. As can be seen from results, phase plane trajectory of postfault current should be combined with that of o component from Clarke modal transformation to give reliability of clear fault classification. Thus the proposed method can classify arcing faults including LIFs and HIFs accurately in power systems.

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Clarke 변환을 응용한 3상 유도전동기의 Inter Turn Short Circuit 진단 (Diagnosis of Inter Turn Short Circuit in 3-Phase Induction Motors Using Applied Clarke Transformation)

  • 고영진;김경민
    • 전기전자학회논문지
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    • 제27권4호
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    • pp.518-523
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    • 2023
  • 고정자 권선단락은 미세한 턴이 단락되어 급격히 고장이 심각해짐에 따라 ITSC의 진단이 중요시되고 있다. 그러나, 3상 유도전동기의 노이즈 및 손실등과 유사한 특징을 가짐에 따라 ITSC진단에 많은 어려움이 있다. 이를 효율적으로 진단하기 위해서 인공지능 기법으로 연구되고 있으나, 현장에서는 모델기반 기법이 두루 활용되고 있음에 따라 모델기반 기법에 대한 진단 성능개선 연구가 필요한 실정이다. 이에 본 논문에서는 회전하고 있는 자속에 변화를 무시하며, 전류 성분만을 이용할 수 있도록 Clarke변환 방법을 응용하여 진단방법을 제안하였다. 이에 30분간의 정상 및 ITSC 상태의 측정 결과, 정상상태를 ITSC 상태로 오인식하는 경우 0.2[%], ITSC상태를 정상상태로 오거부하는 경우 0.26[%]로 효율적인 진단 방법임을 실험을 통해 알 수 있었다.

위상면궤적을 이용한 전력계통의 고장판별에 관한 연구 (A Study on the Classification of Arcing Faults in Power Systems using Phase Plane Trajectory Method)

  • 박남옥;신영철;안상필;여상민;김철환
    • 대한전기학회논문지:전력기술부문A
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    • 제51권5호
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    • pp.209-216
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    • 2002
  • Recently, there is greater demand for stable supply of electric power as higher level of our living. It becomes the important problem that the cause of fault in power system is found out in early stage, if once it occurs. In this respect, accurate classification of arcing faults in power systems is vitally important. This paper presents a new classification method for arcing faults in power system. To obtain data of various faults including high impedance fault(HIF) and low impedance fault(LIF), HIF model with the ZnO arrester is adopted and implemented within the overall transmission system model based on the electromagnetic transients program(EMTP). Results of phase plane trajectory if Clarke modal transformation using postfault current and voltage are utilized to classify types of arcing faults. The performance of the proposed method is tested on a typical 154 kV korean transmission system under various fault conditions. As can be seen from results, phase plane trajectory of postfault current should be combined with that of o component from Clarke modal transformation to give reliability of clear fault classification. Thus the proposed method can classify arcing faults including LIFs and HIFs accurately in power systems.

Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

  • Rohan, Ali;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권4호
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    • pp.238-245
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    • 2016
  • Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

쥐방울과 한약의 수치에 따른 aristolochic acid 함량변화 (Quantitative Change of Aristolochic Acid Contents by Processing Methods on the Plants of Aristolochiaceae)

  • 김민석;이정복;박시형;김동욱;민오진;류동영
    • 생약학회지
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    • 제38권2호통권149호
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    • pp.123-127
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    • 2007
  • Aristolochic acid (AA) included in the plants Aristolochiaceae have been well known to be nephrotoxic and carcinogenic inducer and to cause renal disease such as Chinese Herb Nephropathy (CHN). In this study, we used a high performance liquid chromatopaphy-mass spectrometry (HPLC-MS) under the positive ion detection mode for the quantitative change of aristolochic acid-I and-II (AA-I and AA-II) in Aristolochiaceae (Aristolochia contorta Bunge, Aristolochia debilis Sieb. et Zucc., Aristolochia fangchi Wu), some related plants (Cocculus trilobus De candolle, Inula helenium Linne, Saussurea lappa Clarke), and its prescriptions (防己茯笭湯, 定喘散) with or without processing. Here, the processing methods and prescriptions in oriental medicine were generally used to alleviate toxicity or alter property of herbal medicines. However, the concentrations of AA-I and AA-II were highly determined in processed material extracts rather than unprocessed those, not measured in some related plants. Also, the concentrations of AA-I and AA-II even at the prescriptions mixed the plants of Aristolochiaceae were detected to range from 0.73 to 2.53 ppm. Thus, the present results suggest that the content of AA-I and AA-II contained to plants of Aristolochiaceae was not reduced by the processing methods or prescriptions which can induce the physico-chemical change and pharmacological transformation in traditional herbal medicines.