• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1133-1137
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• 2014

The ultrasonic nonlinear parameter ${\beta}$ is generally known as an effective parameter for evaluating material degradation. Thus far, most research has been conducted using a contact method. However, since measurement by this contact method is affected by the contact conditions between the transducer and the specimen, additional devices are required to maintain the contact conditions stable during the measurement. To avoid this inconvenience, this paper proposes a noncontact method. In this study, only the receiver was replaced with a noncontact receiver, and then, the ultrasonic nonlinear parameters measured by the newly developed noncontact receiver were compared with those measured by the contact receiver. Results obtained using both these receivers for heat-treated aluminum alloy specimens showed good agreement. From this result, we can confirm that the ultrasonic nonlinear parameter ${\beta}$ can be measured using the proposed noncontact ultrasonic method.

• Progress in Superconductivity
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• v.9 no.2
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• pp.146-151
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• 2008

Measurements of surface resistance ($R_s$) of high temperature superconductor (HTS) films with accuracy are essential for microwave applications of HTS materials. In using the dielectric resonator method, uncertainties in the unloaded quality factor of the resonator cause significant errors in the measured $R_s$ of HTS films. We compare the Rs values of $YBa_2Cu_3O_{7-{\delta}}$ films calculated from the $Q_0$ as determined from the Lorentzian fit with that from the $Q_0$ as determined from the S-parameter circle-fit at temperatures between 15 K and 77 K. The two sets of values appeared to differ by 5%, 7%, 6%, and 11% at temperatures of 15, 60, 70, and 77 K, respectively, from each other, implying that careful error analysis needs to be performed in obtaining the $R_s$ of HTS films by using the Lorentzian-fit method, with the ones determined from the S-parameter circle-fit used as the reference.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.7-16
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• 2010

Stress history increases the residual horizontal stress of granular soil and, consequently, the penetration resistance. This study analyzes the effect of stress history on the cone resistance ($q_c$), horizontal stress index ($K_D$) and dilatometer modulus ($E_D$) of CPT and DMT from calibration chamber specimen in OC as well as NC state. Test results show that the normalized cone resistance by mean effective stress correlates well with the relative density and the state parameter, whereas the normalized cone resistance by vertical effective stress is a little affected by stress history. The influence of stress history is more reflected on $K_D$ than $E_D$ and $q_c$. The $K_D/K_0$, in which the effect of stress history on $K_D$ is compensated by the at-rest coefficient of earth pressure, $K_0$, is related to relative density, state parameter and the normalized cone resistance by mean effective stress. It is also observed that the normalized dilatometer modulus by mean effective stress ($E_D/{\sigma}_m'$) shows a unique correlation with the state parameter, regardless of stress history.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.1
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• pp.1-11
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• 2017

Seismic risk analysis was performed based on the total stress and effective stress of caisson type quay wall and pier type quay wall. In order to consider the effective stress effect, the pore pressure of the ground was distributed, using Byrne(1991) simple formula to estimate parameter and applied to the finn model. Through the results of seismic risk analysis according to the total stress and effective stress analysis method, the necessity of effective stress analysis in the seismic design of the quay wall installed on the soft ground was confirmed.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.65-72
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• 2001

Generally, it is said that control of the inertia system is to track the reference input quickly while suppressing the vibration due to the system itself. In this case, the difficulty fur designing a controller is caused by modeling uncertainty and parameter variation. The purpose of this paper is to propose a design method to suppress the vibration of three-mass inertia system based on the LMI theory. That is, the generalized plant model by which we can cope with conservativeness of the existing H$_{*}$ theory is proposed and analyzed in terms of LMI. The results of simulation fur the three-mass inertia system show that the proposed design approach is quite effective under the given situations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.195-200
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• 2004

In this paper we propose effective speech recognizer through two recognition experiments. In general, SVM is classification method which classify two class set by finding voluntary nonlinear boundary in vector space and possesses high classification performance under few training data number. In this paper we compare recognition performance of HMM and SVM at training data number and investigate recognition performance of each feature parameter while changing feature space of MFCC using Independent Component Analysis(ICA) and Principal Component Analysis(PCA). As a result of experiment, recognition performance of SVM is better than 1:.um under few training data number, and feature parameter by ICA showed the highest recognition performance because of superior linear classification.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1423-1430
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• 2017

Detonation cell width is an important parameter in hydrogen explosion assessments. The experimental data on gas detonation are statistically analyzed to establish a universal method to numerically predict detonation cell widths. It is commonly understood that detonation cell width, ${\lambda}$, is highly correlated with the characteristic reaction zone width, ${\delta}$. Classical parametric regression methods were widely applied in earlier research to build an explicit semiempirical correlation for the ratio of ${\lambda}/{\delta}$. The obtained correlations formulate the dependency of the ratio ${\lambda}/{\delta}$ on a dimensionless effective chemical activation energy and a dimensionless temperature of the gas mixture. In this paper, support vector regression (SVR), which is based on nonparametric machine learning, is applied to achieve functions with better fitness to experimental data and more accurate predictions. Furthermore, a third parameter, dimensionless pressure, is considered as an additional independent variable. It is found that three-parameter SVR can significantly improve the performance of the fitting function. Meanwhile, SVR also provides better adaptability and the model functions can be easily renewed when experimental database is updated or new regression parameters are considered.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.559-563
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• 1991

Permanent magnet synchronous motor (PMSM) is receiving increased attention for servo drive applications in recent years because of its high torque to inertia ratio, superior power density and high efficiency. Vector-controlled PMSM has the same operating characteristics as separately excited dc motor. The drive system of servo motor is requested to have an accurate response for the speed reference and a quick recovery for the disturbance such as load torque. However the dynamics of PMSM drive change greately by parameter variations. Morever, when the unkown and inaccessible disturbances are imposed on PMSM, the drive system is given a significant effect by them. As a result, the drive system with both a fast drive performance and a reduced sensitivity to parameter variations is requested. In this paper, the robust control system of PMSM with torque feedforward using load torque observer is presented. In the proposed system, load torque is estimated by the reduced order observer, and the robust control system against load torque variation is realized using the torque feedforward. Moreover, the design of speed controller with the torque observer is discussed. Simulation results show that the proposed method is effective for suppression of parameter variations and load disturbance.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.147-153
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• 2011

This paper proposes a methodology using a tool based on the branch-parameter continuation power flow (BCPF) in order to restore the power flow solvability in unsolvable contingencies. A specified contingency from a set of transmission line contingencies is modeled, considering the transient analysis and practice in the Korean power system. This tool traces a solution path that satisfies the power flow equations with respect to the variation of the branch parameter. At a critical point, in which the branch parameter can move on to a maximum value, a sensitivity analysis with a normal vector is performed to identify the most effective compensation. With the sensitivity information, the location of the reactive power compensation is determined and the effectiveness of the sensitivity information is verified to restore the solvability. In the simulation, the proposed framework is then applied to the Korean power system.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.