• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.122-129
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• 1999

A 5-axis CNC machine tool is more useful compared with a 3-axis machine tool, because the position and the orientation of a tool tip can be controlled simultaneously. Unlike the 3-axis machine tool, the 5-axis machine tool has the volumetric position error and volumetric orientation error due to the quasi-static error of each machine tool joint which is a major source of machined part error. So, the generalized error synthesis model of the 5-axis CNC machine tool was developed to predict and to compensate for the volumetric position error and the volumetric orientation error. It was proposed that a compensation algorithm to correct simultaneously the volumetric position error and the volumetric orientation error of the 5-axis CNC machine by error inverse kinematic.

• Structural Engineering and Mechanics
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• v.35 no.6
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• pp.773-789
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• 2010

It is well known that the analytical vibration characteristic of a cracked beam depends largely on the crack model. In the forward analysis, an improved and simplified approach in modeling discrete open cracks in beams is presented. The effective length of the crack zone on both sides of a crack with stiffness reduction is formulated in terms of the crack depth. Both free and forced vibrations of cracked beams are studied in this paper and the results from the proposed modified crack model and other existing models are compared. The modified crack model gives very accurate predictions in the modal frequencies and time responses of the beams particularly with overlaps in the effective lengths with reduced stiffness. In the inverse analysis, the response sensitivity with respect to damage parameters (the location and depth of crack, etc.) is derived. And the dynamic response sensitivity is used to update the damage parameters. The identified results from both numerical simulations and experiment work illustrate the effectiveness of the proposed method.

• Journal of Power System Engineering
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• v.12 no.1
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• pp.72-79
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• 2008

This paper designs a looper-tension controller for mass-flow stabilization in hot strip finishing mills. By Newton's 2nd law and Hooke's law, nonlinear dynamic equations on the looper-tension system are firstly derived, and linearized by a linearization algorithm using a Taylor's series expansion. Moreover, a tension calculation model is obtained from the nonlinear dynamic equations which is called as a soft sensor of strip tension between two neighboring stands. Next, a looper-tension servo controller is designed by an ILQ(Inverse Linear Quadratic optimal control) algorithm, and it is combined with a minimal disturbance observer which to attenuate speed disturbances by AGC and operator interventions, etc.. Finally, it is shown from by a computer simulation that the proposed ILQ controller with a disturbance observer is very effective in stabilizing the strip mass-flow under some disturbances, moreover it has a good command following performance.

• Genomics & Informatics
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• v.19 no.1
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• pp.9.1-9.5
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• 2021

Mammalian olfactory receptors are a family of G protein-coupled receptors (GPCRs) that occupy a large part of the genome. In human genes, olfactory receptors account for more than 40% of all GPCRs. Several types of GPCR structures have been identified, but there is no single olfactory receptor whose structure has been determined experimentally to date. The aim of this study was to model the interactions between an olfactory receptor and its ligands at the molecular level to provide hints on the binding modes between the OR2W1 olfactory receptor and its agonists and inverse agonists. The results demonstrated the modes of ligand binding in a three-dimensional model of OR2W1 and showed a statistically significant difference in binding affinity to the olfactory receptor between agonists and inverse agonists.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1151-1156
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• 2013

In this study, to clearly establish the concept of a geometric modeling I apply for the concept of Pushbroom, limited to two-dimensional radiation Locator to provide a three-dimensional information purposes. Respect to the radiation scanner Pushbroom modeling techniques, geometric modeling method was presented introduced to extract three-dimensional information as long as the rotational component of the Gamma-Ray Linear Pushbroom Stereo System, introduced the two-dimensional and three-dimensional spatial information in the matching relation that can be induced. In addition, the pseudo-inverse matrix by using the conventional least-squares method, GCP(Ground Control Point) to demonstrate compliance by calculating the key parameters. Projection transformation matrix is calculated for obtaining three-dimensional information from two-dimensional information can be used as the primary relationship, and through the application of a radiation image matching technology will make it possible to extract three-dimensional information from two-dimensional X-ray imaging.

• Geomechanics and Engineering
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• v.8 no.2
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• pp.153-171
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• 2015

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the "Bois de Peu" tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.149-157
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• 2021

Given that induced polarization (IP) and direct current (DC) resistivity surveys are similar in terms of data acquisition, most DC resistivity systems are equipped with a time-domain IP data acquisition function. In addition, the time-domain IP data include the DC resistivity values. As such, IP and DC resistivity data are intimately linked, and the inversion of IP data is a two-step process based on DC resistivity inversions. Nevertheless, IP surveys are rarely applied, in contrast to DC resistivity surveys, as proper inversion software is unavailable. In this study, through numerical modeling and inversion experiments, we analyze the problems with the conventional inverse mapping technique used to invert time-domain IP data. Furthermore, we propose a modified inverse mapping technique that can effectively suppress inversion artifacts. The performance of the technique is confirmed through inversions applied to synthetic IP data.

• Atmosphere
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• v.28 no.2
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• pp.113-121
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• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.993-1004
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• 2004

We propose the method for kinematic and dynamic modeling and Path-tracking of four-wheeled mobile robots with 2 d.o.f having the limited drive-torques. Controllability of wheeled-mobile robots is revealed by using the kinematic model. Instantaneously coincident coordinate system, force/torque propagation and Newton's equilibrium law are used to induce the dynamic model. When drive-torques generated by inverse dynamics exceed the limitation, we make wheeled-mobile robots follow the reference path by modifying the planned reference trajectory with time-scaling. The controller is introduced to compensate for error owing to modeling uncertainty and measurement noise. And simulation results prove that the method proposed by this paper is efficient.