• 제목/요약/키워드: 디지탈 시그널 프로세서

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Vision System Design for Automatic Test and Repair of Steam Generator Holes in Nuclear Power Plants (원자력발전소 증기 발생기의 자동검사 및 수리를 위한 비젼시스템 설계)

  • 한성현
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.6
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    • pp.5-14
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    • 1998
  • In this paper we propose a new approach to the development of the automatic vision system to examine and repair the steam generator tubes at remote distance. In nuclear power plants, workers are reluctant of works in steam generator because of the high radiation environment and limited working space. It is strongly recommended that the examination and maintenance works be done by an automatic system for the protection of the operator from the radiation exposure. Digital signal processors are used in implementing real time recognition and examination of steam generator tubes in the proposed vision system. Performance of proposed digital vision system is illustrated by simulation and experiment for similar steam generator model.

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Implementation of the Adaptive-Neuro Controller of Industrial Robot Using DSP(TMS320C50) Chip (DSP(TMS320C50) 칩을 사용한 산업용 로봇의 적응-신경제어기의 실현)

  • 김용태;정동연;한성현
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.10 no.2
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    • pp.38-47
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    • 2001
  • In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

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