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Analysis and Diagnosis Scheme of Parallel Arc Failure in DC Power Lines
Dang Hoang-Long,Kim Jae-Chang,Kwak Sangshin,Choi Seungdeog 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3
The arc phenomena usually relate to the undesired ejection of two electric conductors. The emission power discharge from an arc event might wrath the electrical lines and cause a fire. Numerous studies were proposed to detect arc events and isolate them in time. The DC arc faults are sorted into two common types: series and parallel arcs. Due to corrupting contamination or insulation, a parallel arc occurs between two electrical wiring. The parallel arc currents of the system can be considerably amplified compared with the series type. In this research, the characteristic behaviors of the system in both time and frequency domains are studied during DC parallel arc failures, and arc energy was also discussed and analyzed. The unique behaviors are adopted to identify parallel arcs in different conditions. Sorting electrical arcs that are beneficial and trustworthy for the judicial procedure and deciding the protection schemes. The analyzed process is based on different domains of load current, source current, and arc voltage.
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나경민(Kyung-Min Na),이기원(Kiwon Lee),박철민(Chulmin Park),김형철(Hyungchul Kim),박영(Young Park) 대한전기학회 2021 전기학회논문지 Vol.70 No.10
Hazardous arc generated by electrical faults are detected for safety accidents in power facilities. Arc detection has a different measurement method depending on the faults. the arc flash from short circuit or overload is analyzed by voltage and current for diagnosis. However, there is a disadvantage in detecting the arc because of sensitivity to noise before it occur. In addition, detection method based on the photosensor may cause an malfunction by the light around environment. The photosensor with 220 nm can prevent malfunction because it not work in sun of the light. The arc size according to the detection speed is shown as the arc duration. This method reduces error according to the detection speed. However, it is necessary to implement a program capable of determining detection and accuracy determination for quantitative measurement. In this paper, we propose a detection method and program with improved detection speed to detect the arc duration of 10 μs. the error of program is compared with the arc duration generated in real time. In the future, we propose that customized application will be possible according to the factors of arc generation in the electric power field.
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퍼지알고리즘을 이용한 전기전자기기의 안전진단방법에 대한 연구
이재철 한국디지털정책학회 2018 디지털융복합연구 Vol.16 No.7
최근 전기기기로 인한 화재발생이 급증함에 따라 기기에 대한 안전진단의 필요성이 높아지고 있다. 본 연 구는 지능형의 Fuzzy기술을 이용한 전기기기의 안전진단에 관한 것으로 기기의 사용전류특성, 누적사용시간, 열화특성 및 Arc특성 등의 복합적인 전기안전 요인을 검출하여 진단한다. 이들 안전요인을 실시간으로 추출하기 위하여 각종 Sensor회로, DSP(Digital Signal Processor) 신호처리회로, 무선통신회로 등으로 구성된 Board를 설계하였고, 추출된 4가지 진단정보를 이용하여, 기기의 안전정도를 퍼지수치 값으로 표시하기 위하여 각 정보마다 Gaussian function을 사용한 퍼지 알고리즘을 설계하고 DSP에 실장 하였다. 지능적인 퍼지알고리즘은 4가지의 진단정보를 입력받아 퍼지엔진으로 추론하고 해당기기의 종합적인 안전 상태를 사람의 감성에 익숙한 100단계의 아날로그 퍼지 값으로 출력한다. 본 연구에서 구현된 DSP 하드웨어와 퍼지 알고리즘을 융합한 보드의 실험을 통하여, 전기기기의 운전 중 실시간 안전 상태를 복합적으로 검출하고, 사람에게 친화적인 감성적 퍼지 값으로 진단결과를 출력하는 기능을 소형의 DSP Board에서 구현할 수 있음을 입증하였다. 향후 인공지능 전용 Micom이 출시된다면 지능을 바탕으로 보다 진보된 진단 시스템을 연구할 수 있을 것으로 기대한다. Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.
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張惟進(Yu Jin Jang),金相禹(Sang Woo Kim) 대한전기학회 2006 전기학회논문지 D Vol.55 No.3
In the steel industry, a steel melting electric arc furnace is used to produce both carbon and alloy steels. Steel scrap which is charged into the furnace is heated by means of electric arc between graphite electrodes and the scrap. In this melting process, current is supplied to the furnace through HCC(high current cable) which connect the furnace and transformer. Four HCCs are assigned to each phase in our system to divide the current. Since a sudden cable breaking result in the shutdown of melting process, an aging detection of HCC is very important for both an improvement of productivity and cost reduction. In this paper, the aging of the HCC is estimated by using the current ratio between four HCCs.
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