• Title/Summary/Keyword: Advance angel

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A Computing Switching Angle for Adaptive Operation of SRM for Drill (드릴용 SRM의 최적운전을 위한 스위칭각 산정)

  • Choe, Gyeong-Ho;Kim, Nam-Hun;Baek, Won-Sik;Kim, Dong-Hui;No, Chae-Gyun;Kim, Min-Hoe;Hwang, Don-Ha
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.50 no.11
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    • pp.575-582
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    • 2001
  • This paper presents a calculating method of switching angle for adaptive switched reluctance motor (SRM) drive of a drill. The operation of the SRM is completely characterized by the flux linked by one phase winding which depends only on the current in that same phase winding and the rotor position. An efficiently adaptive SRM drive is possible on appropriately scheduling the commutation angles with accurate rotor position, supplied current value and speed information. An adaptive SRM drive with reduction torque ripple should be controlled by an optimized phase current control along with rotor position. Therefore, we are suggested a computing method of switching turn-on and off angles for adaptationally SRM operation with varied rotor speed and load. To probe the computing method, we have some simulation and experiment, it is shown a good result that can be computing the optimized switching angles for an electric drill motor.

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Illumination-Robust Lane Detection Algorithm using CIEL *C*h (CIEL * C * h를 이용한 조도변화에 강인한 차선 인식 연구)

  • Pineda, Jose Angel;Cho, Yoon-Ji;Sohn, Kwang-hoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.891-894
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    • 2017
  • Lane detection algorithms became a key factor of advance driver assistance system (ADAS), since the rapidly increasing of high-technology in vehicles. However, one common problem of these algorithms is their performance's instability under various illumination conditions. We recognize a feasible complementation between image processing and color science to address the problem of lane marks detection on the road with different lighting conditions. We proposed a novel lane detection algorithm using the attributes of a uniform color space such as $CIEL^*C^*h$ with the implementation of image processing techniques, that lead to positive results. We applied at the final stage Clustering to make more accurate our lane mark estimation. The experimental results show the effectiveness of our method with detection rate of 91.80%. Moreover, the algorithm performs satisfactory with changes in illumination due to our process with lightness ($L^*$) and the color's property on $CIEL^*C^*h$.