• 한국생산제조학회지
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• 제22권4호
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• pp.735-739
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• 2013

The error motion of a machine tool spindle directly affects the surface errors of machined parts. Spindle motion errors such as three translational motions and two rotational motions are undesirable. These are usually due to the imperfectness of bearings, stiffness of spindle, assembly errors, and external force or unbalance of rotors. The error motions of the spindle need to be reduced for achieving the desired performance. Therefore, the level of error motion needs to be estimated during the design and assembly process of the spindle. In this study, an estimation method for five degree-of-freedom (5 DOF) error motions for a spindle with an angular contact ball bearing is suggested. To estimate the error motions of the spindle, the waviness of the inner-race of bearings and an external force model were used as input data. The estimation model considers the geometric relationship and force equilibrium of the five DOFs. To calculate the error motions of the spindle, not only the imperfections of the shaft and bearings but also driving elements such as belt pulley and direct driving motor systems are considered.

• 한국정밀공학회지
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• 제32권2호
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• pp.127-133
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• 2015

The error motion of a machine tool spindle directly affects the surface errors of machined parts. Those are usually due to the imperfectness of bearings, stiffness of spindle, assembly errors, external force or unbalance of rotors. The error motions of the spindle have been needed to be decreased to desired goal of spindle's performance. The level of error motion is needed to be estimated during the design and assembly process of the spindle. In this paper, the estimation method for the five degree of freedom (5 D.O.F) error motions for rotary units such as a spindle and rotary table are suggested. To estimate the error motions of the rotary unit, waviness of bearings and external force model were used as input data. The estimation model considers geometric relationship and force equilibrium of the five degree of the freedom motions.

• 한국정밀공학회지
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• 제28권3호
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• pp.285-291
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• 2011

The error motion of a machine tool spindle directly affects the surface errors of machined parts. The error motions of the spindle are not desired errors in the three linear direction motions and two rotating motions. Those are usually due to the imperfect of bearings, stiffness of spindle, assembly errors, external force or unbalance of rotors. The error motions of the spindle have been needed to be decreased to desired goal of spindle's performance. The level of error motion is needed to be estimated during the design and assembly process of the spindle. In this paper, the estimation method for the five degree of freedom (5 D.O.F) error motions of the spindle is suggested. To estimate the error motions of the spindle, waviness of shaft and bearings, external force model was used as input data. And, the estimation models are considering geometric relationship and force equilibrium of the five degree of the freedom. To calculate error motions of the spindle, not only imperfection of the shaft, bearings, such as rolling element bearing, hydrostatic bearing, and aerostatic bearing, but also driving elements such as worm, pulley, and direct driving motor systems, were considered.

• 한국자동차공학회논문집
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• 제7권5호
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• pp.240-248
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• 1999

This paper presents a lane-change collision avoidance control algorithm for autonomous vehicles that will be used in AHS(Automated Highway System). In the proposed control algorithm, nominal control inputs are generated by solving the inverse vehicle dynamic equations of motion for a lane-change maneuver. In addition, a corrective steering input from preview as well as DYC (Direct Yaw Moment Control) may be included to reduce unpredictable errors and to insure yaw directional stability, respectively. The performance of the algorithm is evaluated with an ABS HILS system which consist of 17 DOF vehicle model and real ABS hardware parts. The HILS simulation results show that the proposed algorithm may be used for emergency lane-change maneuvers for autonomous vehicles.