• Title/Summary/Keyword: Machine Control Data

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A study on the improvement of floating point operation for AC servo motor controller based on fixed point DSP (고정소수연산 DSP 기반 AC 서보모터 제어기의 소수연산 개선에 관한 연구)

  • Hwang In-Sung;Choi Chi-Young;Hong Sun-Ki
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.1196-1198
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    • 2004
  • This paper represents the improvement of floating point operation for AC servo motor controller based on fixed point operation DSP. TMS320F2812 has fixed point operation processing structure. The controller parameters are modified to the digitized data by scaling the original parameters. TMS320F 2812 is a 32-bit processor, and it could have enough accuracy to got the digitized data this procedure is implemented and the experiments controling a AC servo system.

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Intelligent Washing Machine: A Bioinspired and Multi-objective Approach

  • Milasi, Rasoul Mohammadi;Jamali, Mohammad Reza;Lucas, Caro
    • International Journal of Control, Automation, and Systems
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    • v.5 no.4
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    • pp.436-443
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    • 2007
  • In this paper, an intelligent method called BELBIC (Brain Emotional Learning Based Intelligent Controller) is used to control of Locally Linear Neuro-Fuzzy Model (LOLIMOT) of Washing Machine. The Locally Linear Neuro-Fuzzy Model of Washing Machine is obtained based on previously extracted data. One of the important issues in using BELBIC is its parameters setting. On the other hand, the controller design for Washing Machine is a multi objective problem. Indeed, the two objectives, energy consumption and effectiveness of washing process, are main issues in this problem, and these two objectives are in contrast. Due to these challenges, a Multi Objective Genetic Algorithm is used for tuning the BELBIC parameters. The algorithm provides a set of non-dominated set points rather than a single point, so the designer has the advantage of selecting the desired set point. With considering the proper parameters after using additional assumptions, the simulation results show that this controller with optimal parameters has very good performance and considerable saving in energy consumption.

Suggest Schema for Machine Socialization of Technical Development (Machine Socialization 기술개발을 위한 스키마 제안)

  • Park, Sung-hyun;Kim, Yong-Un;Yoo, Sang-keun;Jung, Hoe-kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.865-867
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    • 2014
  • IoT is a kind of business means to maintain the scenario in aware of the situation with the user's through collaboration for M2M have intelligence to each appliance is of machine socializations. The existing IoT Progress from one situation one control of through a simple sensor data, mean from machine socialization is regulate and control on overall the flow of machine manager to solved a scenarios as the situation. In this paper, suggest schema for to apply the M2M of SNS of existing H2H, suggest is schema in information each appliance in solve scenario for machine manager.

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Extraction of the control data for the shoe laster by using tension spline method and verification of the geometric grading system (Tension spline 방법을 이용한 제화용 라스팅기의 제어데이터 추출 및 기하할출제도의 검증)

  • Jang, Kwang-Keol;Kim, Seung-Ho;Huh, Hoon
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.140-145
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    • 2001
  • Lasting machines for shoe manufacturing are continuously developed with the aid of automation and Computer Aided Manufacturing (CAM). Adaptive lasting machine and CAD data of a shoe last are inevitably introduced for the labor-free manufacturing process. Recently, method for the CAD datarization of a shoe last is suggested using finite element mesh system. Initial set up data and control data of machine parts are required for the adaptive lasting machine. For the efficient process, grading of those data is essential to minimize data storage and production costs. In this paper, bonding lines are extracted from the CAD data of a shoe last and graded by the geometric grading system. Tension spline method is adopted for the interpolation of last CAD data. The results are compared with the results from the arithmetic grading system that is widely adopted in the shoemaking companies.

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A Study on Machine Failure Improvement Using F-RPN(Failure-RPN): Focusing on the Semiconductor Etching Process (F-RPN(Failure-RPN)을 이용한 장비 고장률 개선 연구: 반도체 식각 공정을 중심으로)

  • Lee, Hyung-Geun;Hong, Yong-Min;Kang, Sung-Woo
    • Journal of the Korea Safety Management & Science
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    • v.23 no.3
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    • pp.27-33
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    • 2021
  • The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

Design and Implementation of Engine to Control Characters By Using Machine Learning Techniques (기계학습 기법을 사용한 캐릭터 제어 엔진의 설계 및 구현)

  • Lee, Jae-Moon
    • Journal of Korea Game Society
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    • v.6 no.4
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    • pp.79-87
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    • 2006
  • This paper proposes the design and implementation of engine to control characters by using machine teaming techniques. Because the proposed engine uses the context data in the rum time as the knowledge data, there is a merit which the player can not easily recognize the behavior pattern of the intelligent character. To do this, the paper proposes to develop the module which gathers and trains the context data and the module which tests to decide the optimal context control for the given context data. The developed engine is ported to FEAR and run with Quake2 and experimented far the correctness of the development and its efficiency. The experiments show that the developed engine is operated well and efficiently within the limited time.

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A Study on the Program Development of Fatigue Test (피로시험용 프로그램 개발에 관한 연구)

  • 이종선
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.275-280
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    • 1999
  • This study is object to program development of fatigue test for universal testing machine. Fatigue program is consist of test simulation, data analysis and print report by control fatigue testing program which expansively applies tension-compression tests with using oil pressure mechanism by Visual Basic software running under windows 98.

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A Study on the Development of Remote Fault Diagnosis and Maintenance System for Machine Tool (공작기계에서의 원격고장진단 시스템 개발에 관한 연구)

  • 현웅근;신동수;박인준
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.708-713
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    • 1997
  • A remote data communication system for monitoring of NC machine fault diagnosis and status is developed. This system communicates with host PC by using dial-up communication method on PSTN. The developed system consists of (1)remote communication module among NC's and host PC using PSTN, (2) 8 channels analog data sensing module, (3) digital I/O module for control of NC machine, (4) communication module between NC machine and remote data communication system using RS-232c, and (5) Software man-machine interface. This system may be applied for remote sensing of the status in Fms. To show the veridity of the developed system, several examples are illustrated.

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A Study on Robot Hand Gripper Design and Robust Control for Assembly and Disassembly Task of Machine Parts (기계 부품의 조립분해 작업을 위한 로봇핸드 그리퍼 설계 및 견실제어에 관한 연구)

  • Jeong, Gyu-Hyun;Shin, Gi-Su;Noh, Yeon-Guk;Moon, Byeong-Gap;Yoon, Byeong-Seok;Bae, Ho-Young;Kim, Min-Seong;Han, Sung-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.20 no.4
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    • pp.299-305
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    • 2017
  • This study proposes a new technique to design and control of robot hand gripper for assembling and disassembling of a machine parts. The motion equation describing dynamics of the manipulators and object together with geometric constraint is formulated by Lagrange-Euler's equation. And the problems of controlling both the grasping force and the rotation angle of the grasped object under the constraints are analyzed. The effect of geometric constraints and a method of computer simulation for overall system is verified. Finally, it is illustrated that even in case of there exists a sensory feedback from sensing data of the rotational angle of the object to command inputs control of joint and this feedback connection from sensing data to control grasping of machinery parts.

Optimal deep machine learning framework for vibration mitigation of seismically-excited uncertain building structures

  • Afshin Bahrami Rad;Javad Katebi;Saman Yaghmaei-Sabegh
    • Structural Engineering and Mechanics
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    • v.88 no.6
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    • pp.535-549
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    • 2023
  • Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.