• Title/Summary/Keyword: Power Detection System

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저압계통에서 직렬아크신호의 검출 (Detection of Series Arc Signal in Low-voltage Systems)

  • 지홍근;박찬용;길경석;김일권;조영진
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2008년도 춘계학술대회 논문집
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    • pp.316-320
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    • 2008
  • This paper described the design and fabrication of a series arc detection module to monitor electrical insulation in low-voltage system. The module consists of a passive high-pass filter with a low cut-off frequency of 3 kHz to attenuate power frequency voltage by 80 dB and an active band-pass filter with a frequency of 4 kHz to detect series arc signals only. For the application experiment, we simulated series arcing phenomena on various loads such as incandescent lamp controlled by dimmer and inverter fed induction motors by an arc generator specified in UL1699. From the experimental results, we could detect series arc signals without an influence of noises.

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Modular Cellular Neural Network Structure for Wave-Computing-Based Image Processing

  • Karami, Mojtaba;Safabakhsh, Reza;Rahmati, Mohammad
    • ETRI Journal
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    • 제35권2호
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    • pp.207-217
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    • 2013
  • This paper introduces the modular cellular neural network (CNN), which is a new CNN structure constructed from nine one-layer modules with intercellular interactions between different modules. The new network is suitable for implementing many image processing operations. Inputting an image into the modules results in nine outputs. The topographic characteristic of the cell interactions allows the outputs to introduce new properties for image processing tasks. The stability of the system is proven and the performance is evaluated in several image processing applications. Experiment results on texture segmentation show the power of the proposed structure. The performance of the structure in a real edge detection application using the Berkeley dataset BSDS300 is also evaluated.

배관계의 가스누설탐지를 위한 음향모델 연구 (A Study on an Acoustical Model for Gas Leak Detection in a Pipeline)

  • 양윤상;이동훈;고재필
    • 설비공학논문집
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    • 제26권2호
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    • pp.91-96
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    • 2014
  • An acoustical model for detecting the leak location in a buried gas pipeline has been developed. This model is divided into an experimental model for sound diagnosis, and a theoretical model for sound prediction, which is based on the transfer matrix method, representing the sound pressure and the volume velocity as state variables. The power spectrum is measured by attaching only one microphone to the closed end pipe. It has been shown that the response magnitude of acoustic pressure signals calculated by the acoustical model depends upon the thickness and diameter of a pinhole. The validity for the acoustical model has been verified through a comparison between the measured and calculated results.

인공지능에 의한 부하전류파형의 인식으로 화재감지 시스템 (Fire detection system by awareness of load current waveform by Neural Network)

  • 이오걸;송호신;김태우;김민회
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 전력전자학술대회 논문집
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    • pp.301-304
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    • 2001
  • In this paper, a method which can detect tracking caused by the insulation deterioration of conduct wiring, is proposed. The computer which take experiment data is learned by neural network algorithm, which has recently been used for the load recognition. The proposed method in our study can be applied to the development of several measuring equipments such as hot-line insulation tester, car earth tester for the detection of tracking under hot-line state.

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교류 발전기 고정자 사고 검출을 위한 최적 마더 웨이브릿의 선정 (A Selection of an Optimal Mother Wavelet for Stator Fault Detection of AC Generator)

  • 박철원
    • 전기학회논문지P
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    • 제57권4호
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    • pp.377-382
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    • 2008
  • For stator winding protection of AC generator, KCL(Kirchhoff's Current Law) is widely applied. Actually a CRDR(Current Ratio Differential Relay) based on DFT(Discrete Fourier Transform) has been used for protecting generator. It has been pointed out that defects can occur during the process of transforming a time domain signal into a frequency domain one which can lead to loss of time domain information. Wavelets techniques are proposed for the analysis of power system transients. This paper introduces an algorithm to choose a suitable Mother Wave1et for generator stator fault detection. For optimal selection, we analyzed db(Daubechies), sym(Symlets), and coif(Coiflects) of Mother Wavelet. And we compared with performance of the choice algorithm using detail coefficients energy and RMS(root mean square) error. It can be improved the reliability of the conventional DFT based CRDR. The feasibility and effectiveness of the proposed scheme is proved with simulation using collected data obtained from ATP (Alternative Transient Program) package.

Design of Emergency Fire Fighting and Inspection Robot Riding on Highway Guardrail

  • Ma, Xiaotong;Li, Xiaochen;Liu, Yanqiu;Tao, Xueheng
    • 한국멀티미디어학회논문지
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    • 제25권6호
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    • pp.833-843
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    • 2022
  • Based on the problems of untimely Expressway fire rescue and backward traditional fire rescue methods, an emergency fire fighting and inspection robot riding on expressway guardrail is designed. The overall mechanical structure design of emergency fire fighting and inspection robot riding on expressway guardrail is completed by using three-dimensional design software. The target fire detection is realized by using the target detection algorithm of Yolov5; By selecting a variety of sensors and using the control method of multi algorithm fusion, the basic function of robot on duty early warning is realized, and it has the ability of intelligent fire extinguishing. The BMS battery charging and discharging system is used to detect the real-time power of the robot. The design of the expressway emergency fire fighting and inspection robot provides a new technical means for the development of emergency fire fighting equipment, and improves the reliability and efficiency of expressway emergency fire fighting.

TinyML Gamma Radiation Classifier

  • Moez Altayeb;Marco Zennaro;Ermanno Pietrosemoli
    • Nuclear Engineering and Technology
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    • 제55권2호
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    • pp.443-451
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    • 2023
  • Machine Learning has introduced many solutions in data science, but its application in IoT faces significant challenges, due to the limitations in memory size and processing capability of constrained devices. In this paper we design an automatic gamma radiation detection and identification embedded system that exploits the power of TinyML in a SiPM micro radiation sensor leveraging the Edge Impulse platform. The model is trained using real gamma source data enhanced by software augmentation algorithms. Tests show high accuracy in real time processing. This design has promising applications in general-purpose radiation detection and identification, nuclear safety, medical diagnosis and it is also amenable for deployment in small satellites.

온칩 메모리 내 다중 비트 이상에 대처하기 위한 오류 정정 부호 (Error correction codes to manage multiple bit upset in on-chip memories)

  • Jun, Hoyoon
    • 한국정보통신학회논문지
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    • 제26권11호
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    • pp.1747-1750
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    • 2022
  • As shrinking the semiconductor process into the deep sub-micron to achieve high-density, low power and high performance integrated circuits, MBU (multiple bit upset) by soft errors is one of the major challenge of on-chip memory systems. To address the MBU, single error correction, double error detection and double adjacent error correction (SEC-DED-DAEC) codes have been recently proposed. But these codes do not resolve mis-correction. We propose the SEC-DED-DAEC-TAED(triple adjacent error detection) code without mis-corrections. The generated H-matrix by the proposed heuristic algorithm to accomplish the proposed code is implemented as hardware and verified. The results show that there is no mis-correction in the proposed codes and the 2-stage pipelined decoder can be employed on-chip memory system.

LiDAR Measurement Analysis in Range Domain

  • Sooyong Lee
    • 센서학회지
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    • 제33권4호
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    • pp.187-195
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    • 2024
  • Light detection and ranging (LiDAR), a widely used sensor in mobile robots and autonomous vehicles, has its most important function as measuring the range of objects in three-dimensional space and generating point clouds. These point clouds consist of the coordinates of each reflection point and can be used for various tasks, such as obstacle detection and environment recognition. However, several processing steps are required, such as three-dimensional modeling, mesh generation, and rendering. Efficient data processing is crucial because LiDAR provides a large number of real-time measurements with high sampling frequencies. Despite the rapid development of controller computational power, simplifying the computational algorithm is still necessary. This paper presents a method for estimating the presence of curbs, humps, and ground tilt using range measurements from a single horizontal or vertical scan instead of point clouds. These features can be obtained by data segmentation based on linearization. The effectiveness of the proposed algorithm was verified by experiments in various environments.

슬라이딩 모드 관측기 기반 전지형 크레인의 조향입력 고장검출 알고리즘 (Sliding Mode Observer-based Fault Detection Algorithm for Steering Input of an All-Terrain Crane)

  • 오광석;서자호
    • 드라이브 ㆍ 컨트롤
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    • 제14권2호
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    • pp.30-36
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    • 2017
  • This paper presents a sliding mode observer-based fault detection algorithm for steering inputs of an all-terrain crane. All-terrain cranes with multi-axles have several steering modes for various working purposes. Since steering angles at the other axles except the first wheel are controlled by using the information of steering angle at the first wheel, a reliable signal of the first axle's steering angle should be secured for the driving safety of cranes. For the fault detection of steering input signal, a simplified crane model-based sliding mode observer has been used. Using a sliding mode observer with an equivalent output injection signal that represents an actual fault signal, a fault signal in steering input was reconstructed. The road steering mode of the crane's steering system was used to conduct performance evaluations of a proposed algorithm, and an arbitrary fault signal was applied to the steering angle at the first wheel. Since the road steering mode has different steering strategies according to different speed intervals, performance evaluations were conducted based on the curved path scenario with various speed conditions. The design of algorithms and performance evaluations were conducted on Matlab/Simulink environment, and evaluation results reveal that the proposed algorithm is capable of detecting and reconstructing a fault signal reasonably well.