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      Robust Optimum Design of a Bearingless Rotation Motor Using the Kriging Model

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      https://www.riss.kr/link?id=A104359305

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Recently, bearingless rotation motors have become widely popular in office automation (OA) and factory automation (FA)systems due to their simple structure, high speed of operation, and high precision in positioning. In this study, a bearingless rotation motor was designed to have a large torque and levitation force because these are generally considered as indicators of motor performance. The torque and levitation force of the bearingless rotation motor can be calculated by a commercial finite element method (FEM) program, ANSYS. To robustly design the bearingless rotation motor, first, the effective design parameters were selected; we set a table of orthogonal arrays, including the design variables and parameters. The Kriging model was applied to formulate the cost function of the regression model, which can be used to evaluate the motor performance. By minimizing the cost function, it was possible to quickly realize a robust optimum design of a bearingless rotation motor. As a result, the performance of the motor was improved with regard to the torque and levitation force.
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      Recently, bearingless rotation motors have become widely popular in office automation (OA) and factory automation (FA)systems due to their simple structure, high speed of operation, and high precision in positioning. In this study, a bearingless rotat...

      Recently, bearingless rotation motors have become widely popular in office automation (OA) and factory automation (FA)systems due to their simple structure, high speed of operation, and high precision in positioning. In this study, a bearingless rotation motor was designed to have a large torque and levitation force because these are generally considered as indicators of motor performance. The torque and levitation force of the bearingless rotation motor can be calculated by a commercial finite element method (FEM) program, ANSYS. To robustly design the bearingless rotation motor, first, the effective design parameters were selected; we set a table of orthogonal arrays, including the design variables and parameters. The Kriging model was applied to formulate the cost function of the regression model, which can be used to evaluate the motor performance. By minimizing the cost function, it was possible to quickly realize a robust optimum design of a bearingless rotation motor. As a result, the performance of the motor was improved with regard to the torque and levitation force.

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      참고문헌 (Reference)

      1 Chen,S.X, "The robust design approach for reducing cogging torque in permanent magnet motors" 34 (34): 2135-2137, 1998

      2 Gao,X.K, "Structural robust design for torque optimization of BLDC spindle motor using response surface methodology" 37 (37): 2814-2817, 2001

      3 Huang,D, "Sequential kriging optimization using multiple-fidelity evaluations" 32 (32): 369-363, 2006

      4 Menom,R, "Robust design of a spindle motor:a case study" 75 (75): 313-319, 2002

      5 Gao,X.K, "Robust design for torque optimization using response surface methodology" 38 (38): 1141-1144, 2002

      6 안찬우, "Robust Optimization Desjgn of Overhead Crane with Constrat using the Characteristic Functions" 한국정밀공학회 7 (7): 12-17, 2006

      7 서성일, "Optimum design of the cored linear motor using experiment design" 대한기계학회 23 (23): 2215-2223, 2009

      8 Je-seonRyu, "Kriging Interpolation Methods in Geostatistics and DACE Model" 대한기계학회 16 (16): 5-632, 2002

      9 Chen,S.J, "Fuzzy Multiple Attribute Decision Making: Methods and Application" Springer-Verlag 1992

      10 Sasena,M.J, "Exploration of metamodeling sampling criteria for constrained global optimization" 34 (34): 263-278, 2002

      1 Chen,S.X, "The robust design approach for reducing cogging torque in permanent magnet motors" 34 (34): 2135-2137, 1998

      2 Gao,X.K, "Structural robust design for torque optimization of BLDC spindle motor using response surface methodology" 37 (37): 2814-2817, 2001

      3 Huang,D, "Sequential kriging optimization using multiple-fidelity evaluations" 32 (32): 369-363, 2006

      4 Menom,R, "Robust design of a spindle motor:a case study" 75 (75): 313-319, 2002

      5 Gao,X.K, "Robust design for torque optimization using response surface methodology" 38 (38): 1141-1144, 2002

      6 안찬우, "Robust Optimization Desjgn of Overhead Crane with Constrat using the Characteristic Functions" 한국정밀공학회 7 (7): 12-17, 2006

      7 서성일, "Optimum design of the cored linear motor using experiment design" 대한기계학회 23 (23): 2215-2223, 2009

      8 Je-seonRyu, "Kriging Interpolation Methods in Geostatistics and DACE Model" 대한기계학회 16 (16): 5-632, 2002

      9 Chen,S.J, "Fuzzy Multiple Attribute Decision Making: Methods and Application" Springer-Verlag 1992

      10 Sasena,M.J, "Exploration of metamodeling sampling criteria for constrained global optimization" 34 (34): 263-278, 2002

      11 Dunsmore,W, "Developing methodologies for robust mechanical engineering design" 211 (211): 179-188, 1997

      12 Sacks,J, "Design and analysis of computer experiments" 4 (4): 409-435, 1989

      13 정성필, "Design Optimization of Spring of a Locking Nut using Design of Experiments" 한국정밀공학회 10 (10): 77-83, 2009

      14 Alasuvanto,T, "Comparison of Four Different Permanent Magnet Rotor Constructions" 1034-1039, 1990

      15 Oshima,M, "Characteristics of a permanent magnet type bearingless motor" 196-202, 1994

      16 Wang,H.T, "Application of Taguchi method to robust design of BLDC motor performance" 35 (35): 3700-3702, 1999

      17 Lim,J.M, "Analysis and Design Considerations of Energy Absorbing Steering System Using Orthogonal Arrays" 7 (7): 144-155, 1999

      18 Tae-Gyu Park, "An Efficient Method for Fatigue Reliability Analysis Accounting for Scatter of Fatigue Test Data" 한국정밀공학회 11 (11): 429-437, 2010

      19 Simpson,T.W, "A concept exploration method for product family design" Georgia Institute of Technology 1998

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      2005-05-30 학술지명변경 한글명 : International Journal of the Korean of Precision Engineering -> International Journal of Precision Engineering and Manufacturing
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      2016 1.38 0.71 1.08
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      0.92 0.85 0.583 0.11
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