• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.136-144
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• 1999

This paper presents an in-process measurement system for shaft radius measurement during grinding process. This system does not require to stop the grinding process, which can enhance productivity and quality. In order to measure the radius, the system employs an eddy current sensor that can measure without any contact with the shaft. This type of sensor is very appropriate because it is insensitive to interference such as cutting fluid, coolant, contact pressure, and wear. For data analysis, the measurement system is modeled as a linearized discrete form where the states with noise are estimated by an extended Kalman filter. This system has been validated through simulations and experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.468-473
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• 2017

This paper presents an in-process measurement system for shaft radius measurement during grinding process. This system does not require to stop the grinding process, which can enhance productivity and quality. In order to measure the radius, the system employs an eddy current sensor that can measure without any contact with the shaft. This type of sensor is very appropriate because it is insensitive to interference such as cutting fluid, coolant, contact pressure, and wear. For data analysis, the measurement system is modeled as a linearized discrete form where the states with noise are estimated by an extended Kalman filter. This system has been validated through simulations and experiments.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.675-678
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• 1989

This paper proposes two types of the preview algorithms to predict the joint velocities and joint positions, and deals with a control approach using the preview algorithms for the precise trajectory control. Specifically, a predictor an the form of discrete time state equations is proposed based on the robot dynamics model linearized by the computed torque method. And another state predictor is proposed by the beat line fitting in the least square sense, where present joint velocities and positions and several past positions are employed. Then computer simulations are performed for the SCARA robot with two d.o.f. to show the validities of the proposed algothrithms.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2537-2539
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• 2002

This paper presents an in-process measurement system for shaft radius measurement during grinding process. This system does not require to stop the grinding process, which can enhance productivity and quality. For data analysis, the measurement system is modeled as a linearized discrete form where the states with noise are estimated by an extended Kalman filter. This system has been validated through simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.5
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• pp.486-502
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• 1989

This paper proposes two types of the preview algorithms to predict the velocities and joint positions, and deals with a control approach using the preview algorithms for the precise trajectory control. Specifically, a predictor as the form of discrete time state equations is proposed based on the robot dynamics model linearized by the computed toque method. And another state predictor is proposed by the best line fitting in the least square sense, where present joint velocities and positions and several past positions are employed. Then computer simulations are performed for the SCARA robot with two d.o.f to show the validities of the proposed algorithms.

• Coupled systems mechanics
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• v.11 no.2
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• pp.167-198
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• 2022

In this paper we deal with classical instability problems of heterogeneous Euler beam under conservative loading. It is chosen as the model problem to systematically present several possible solution methods from simplest deterministic to more complex stochastic approach, both of which that can handle more complex engineering problems. We first present classical analytic solution along with rigorous definition of the classical Euler buckling problem starting from homogeneous beam with either simplified linearized theory or the most general geometrically exact beam theory. We then present the numerical solution to this problem by using reduced model constructed by discrete approximation based upon the weak form of the instability problem featuring von Karman (virtual) strain combined with the finite element method. We explain how such numerical approach can easily be adapted to solving instability problems much more complex than classical Euler's beam and in particular for heterogeneous beam, where analytic solution is not readily available. We finally present the stochastic approach making use of the Duffing oscillator, as the corresponding reduced model for heterogeneous Euler's beam within the dynamics framework. We show that such an approach allows computing probability density function quantifying all possible solutions to this instability problem. We conclude that increased computational cost of the stochastic framework is more than compensated by its ability to take into account beam material heterogeneities described in terms of fast oscillating stochastic process, which is typical of time evolution of internal variables describing plasticity and damage.

• Journal of the Korean earth science society
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• v.30 no.7
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• pp.834-844
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• 2009

Two-dimensional magnetotelluric (MT) inversion algorithm using minimum support (MS) stabilizer functional was implemented in this study to enhance the contrast of inverted images. For this implementation, this study derived a formula in discrete form for creeping model updates in the least-squares linearized inversion. A spatially varying regularization parameter determination algorithm, which is known as ACB (Active Constraint Balancing), was also adopted to stabilize the inversion process when using MS stabilizer as a model constraint. Inversion experiments for a simple isolated body model show well the feature of MS stabilizer in concentrating the anomalous body compared with the second-order derivative model constraint. This study also compared MS stabilizer and the second-order derivative model constraints for a model having multiple anomalous bodies to show the applicability of the algorithm into field data.