• 제목/요약/키워드: field detection

검색결과 2,384건 처리시간 0.028초

A Non-contact Detection Method for Smelting in Submerged Arc Furnace based on Magnetic Field Radiation

  • Liu, WeiLing;Chang, XiaoMing
    • Journal of Magnetics
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    • 제21권2호
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    • pp.204-208
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    • 2016
  • This paper demonstrates the key parameter detection for smelting of submerged arc furnace (SAF) based on magnetic field radiation. A magnetic field radiation model for the inner structure of SAF is established based on relative theory of electromagnetic field. A simple equipment of 3D magnetic field detection system is developed by theoretical derivation and simulation. The experiments are carried out under the environment of industrial field and AC magnetic field generated by electrode currents and molten currents in the furnace is reflected outside of the furnace. The experimental results show that the key parameters of smelting including the position of electrode tip, the length of electric arc, and the liquid level of molten bath can be achieved. The computed tomography for SAF can be realized by the detection for smelting.

Human Detection in Overhead View and Near-Field View Scene

  • Jung, Sung-Hoon;Jung, Byung-Hee;Kim, Min-Hwan
    • 한국멀티미디어학회논문지
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    • 제11권6호
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    • pp.860-868
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    • 2008
  • Human detection techniques in outdoor scenes have been studied for a long time to watch suspicious movements or to keep someone from danger. However there are few methods of human detection in overhead or near-field view scenes, while lots of human detection methods in far-field view scenes have been developed. In this paper, a set of five features useful for human detection in overhead view scenes and another set of four useful features in near-field view scenes are suggested. Eight feature-candidates are first extracted by analyzing geometrically varying characteristics of moving objects in samples of video sequences. Then highly contributed features for each view scene to classifying human from other moving objects are selected among them by using a neural network learning technique. Through experiments with hundreds of moving objects, we found that each set of features is very useful for human detection and classification accuracy for overhead view and near-field view scenes was over 90%. The suggested sets of features can be used effectively in a PTZ camera based surveillance system where both the overhead and near-field view scenes appear.

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Design of an Optical System for a Space Target Detection Camera

  • Zhang, Liu;Zhang, Jiakun;Lei, Jingwen;Xu, Yutong;Lv, Xueying
    • Current Optics and Photonics
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    • 제6권4호
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    • pp.420-429
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    • 2022
  • In this paper, the details and design process of an optical system for space target detection cameras are introduced. The whole system is divided into three structures. The first structure is a short-focus visible light system for rough detection in a large field of view. The field of view is 2°, the effective focal length is 1,125 mm, and the F-number is 3.83. The second structure is a telephoto visible light system for precise detection in a small field of view. The field of view is 1°, the effective focal length is 2,300 mm, and the F-number is 7.67. The third structure is an infrared light detection system. The field of view is 2°, the effective focal length is 390 mm, and the F-number is 1.3. The visible long-focus narrow field of view and visible short-focus wide field of view are switched through a turning mirror. Design results show that the modulation transfer functions of the three structures of the system are close to the diffraction limit. It can further be seen that the short-focus wide-field-of-view distortion is controlled within 0.1%, the long-focus narrow-field-of-view distortion within 0.5%, and the infrared subsystem distortion within 0.2%. The imaging effect is good and the purpose of the design is achieved.

PMSM Angle Detection Based on the Edge Field Measurements by Hall Sensors

  • Kim, Jae-Uk;Jung, Sung-Yoon;Nam, Kwang-Hee
    • Journal of Power Electronics
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    • 제10권3호
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    • pp.300-305
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    • 2010
  • This paper presents a two Hall sensor method for rotor angle detection in permanent magnet synchronous motors (PMSM). To minimize the implementation complexity, the system is designed to measure the edge field of permanent magnet pieces. However, there are nonlinearities in the measured values of the edge field. In this work, an angle correction algorithm is proposed, and the improvements in accuracy are verified through experiments. Finally, a field orientation controller is constructed with the proposed angle detection algorithm.

IEEE 802.11ac 변조 방식의 딥러닝 기반 분류 (Deep learning-based classification for IEEE 802.11ac modulation scheme detection)

  • 강석원;김민재;최승원
    • 디지털산업정보학회논문지
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    • 제16권2호
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    • pp.45-52
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    • 2020
  • This paper is focused on the modulation scheme detection of the IEEE 802.11 standard. In the IEEE 802.11ac standard, the information of the modulation scheme is indicated by the modulation coding scheme (MCS) included in the VHT-SIG-A of the preamble field. Transmitting end determines the MCS index suitable for the low signal to noise ratio (SNR) situation and transmits the data accordingly. Since data field decoding can take place only when the receiving end acquires the MCS index information of the frame. Therefore, accurate MCS detection must be guaranteed before data field decoding. However, since the MCS index information is the information obtained through preamble field decoding, the detection rate can be affected significantly in a low SNR situation. In this paper, we propose a relatively robust modulation classification method based on deep learning to solve the low detection rate problem with a conventional method caused by a low SNR.

자계안내시스템용 지자계 제거를 위한 Ground 검출법 (Ground Detection Method for Removement of Earth Field for Magnetic Guidance System)

  • 임대영;정영윤;유영재
    • 한국지능시스템학회논문지
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    • 제16권5호
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    • pp.581-586
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    • 2006
  • 본 논문에서는 무인주행 차량의 자율주행에 사용되는 자계안내시스템에서 지자계를 제거하기 위한 새로운 방법으로 Ground 검출법을 제안한다. 자계안내시스템은 도로에 일정한 간격으로 자계표식을 매설하고 차량이 자계표식으로부터 떨어진 거리를 인식하여 주행하는 방법이다. 차량이 주행 중 측면이탈거리를 알기 위해서는 지자계가 제거된 자계표식의 자계만을 이용해야 한다. 그러나 자계센서는 자계를 검출할 때 자계표식의 자계와 지자계를 함께 계측한다. 지자계는 차량의 주행방향과 경사에 따라 다르게 검출되기 때문에 자계표식의 자계와 더해질 경우 측면이탈거리를 인식하는데 오차를 발생한다. 따라서 본 논문에서는 지자계를 제거하는 새로운 방법을 제안하고, 이를 검증하기 위한 실험 장치를 구성하였다. 그리고 실험을 통하여 제안한 방법의 타당성과 유용성을 입증한다.

광학입자센서 내 유동장과 측정영역이 측정효율에 미치는 영향 (Effect of Flow Field and Detection Volume in the Optical Particle Sensor on the Detection Efficiency)

  • 김영길;전기수;김태성
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회B
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    • pp.3162-3167
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    • 2007
  • The OPS (Optical Particle Sensor) using light scattering from the particles (real-time measurement without physical contact to the particles) can be used for cleanroom or atmospheric environment monitoring. For particles smaller than 300 nm, the detection efficiency becomes lower as scattered light decreases with particle size. To obtain higher detection efficiency with small particles, the flow field in particle chamber and the detection volume should be designed optimally to achieve maximum scattered light from the particles. In this study, a commercial computational fluid dynamics software FLUENT was used to simulate the gas flow field and particle trajectories with various optical chamber designs for 300 nm PSL particle. For estimation of laser viewing volume, we used a commercial computational optical design program ZEMAX. The results will be a great help in the development of OPS which can measure small particles with higher detection efficiency.

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딥러닝 기반 객체 인식 기술 동향 (Trends on Object Detection Techniques Based on Deep Learning)

  • 이진수;이상광;김대욱;홍승진;양성일
    • 전자통신동향분석
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    • 제33권4호
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    • pp.23-32
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    • 2018
  • Object detection is a challenging field in the visual understanding research area, detecting objects in visual scenes, and the location of such objects. It has recently been applied in various fields such as autonomous driving, image surveillance, and face recognition. In traditional methods of object detection, handcrafted features have been designed for overcoming various visual environments; however, they have a trade-off issue between accuracy and computational efficiency. Deep learning is a revolutionary paradigm in the machine-learning field. In addition, because deep-learning-based methods, particularly convolutional neural networks (CNNs), have outperformed conventional methods in terms of object detection, they have been studied in recent years. In this article, we provide a brief descriptive summary of several recent deep-learning methods for object detection and deep learning architectures. We also compare the performance of these methods and present a research guide of the object detection field.

라이트 필드 카메라를 사용한 객체 검출 (Object detection using a light field camera)

  • 정민구;김도훈;박상현
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.109-111
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    • 2021
  • 최근 라이트 필드 카메라를 통한 컴퓨터 비전 연구가 활발히 진행되고 있다. 라이트 필드 카메라에서는 공간정보를 가지고 있기 때문에, depth map estimation, super resolution, 3D object detection 과 같은 분야에서 다양한 연구가 진행되고 있다. 본 논문에서는 라이트필드 카메라를 통해 취득되는 7×7 배열의 이미지를 통해 blur 영상에서 객체를 검출하기 위한 방법을 제안한다. 기존의 카메라에서 취약한 blur 영상을 라이트 필드 카메라를 통하여 검출한다. 제안하는 방법은 SSD 알고리즘을 사용하여 실제 라이트 필드 카메라에서 취득한 blur 영상을 사용하여 성능평가를 수행한다

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Magnetic Field 기반 수중무기체계 발화확률에 관한 연구 (A Study on Actuation Probability of Underwater Weapon Based on Magnetic Field)

  • 임병선;홍성표;김영길
    • 한국정보통신학회논문지
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    • 제17권5호
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    • pp.1253-1258
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    • 2013
  • 2010년 천안함 침몰로 인해 수중 폭발체의 위험성이 전시 뿐만 아니라 평시에도 대단히 중요하게 다뤄져야 하며, 그에 따른 방어대책이 필수적으로 필요함을 인지하게 되었다. 다양한 수중무기폭발 체계 중 대표적인 비닉(庇匿) 무기체계인 기뢰를 중심으로 탐지수단, 탐지방법, 위험 제거 방안 등에 대해 연구하며, 특히 탐지를 위한 대표적인 센서인 자력계 등의 데이터를 참조하여 발화확률 모사 시스템을 모델링하고, 아 해군 보유 함형에 따른 수심별 해석을 통해 발화확률 등을 시뮬레이션 하여 효과적인 탐지, 위협제거 및 궁극적인 대기뢰전 전술 등을 연구/제안한다.