• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.515-518
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• 2006

A vibration test for a cylindrical rod inserted on the grid support structure was tested using the sine sweep excitation method with closed loop force control. The effect of the mounting location of a test rod on the vibration characteristics of a rod continuously supported by the full size($16{\times}16$) grid support was identified. An electromagnetic vibration shaker, non-contact displacement sensor and HP/VXI data acquisition device were used and TDAS software was also used as a data sampling and processing tools. The natural frequencies and mode shape of the test rod were consistent with the previous works of a rod vibration test with partial grids($3{\times}3,\;5{\times}5\;and\;7{\times}7$). The frequency characteristics of the rod according to the mounting location were shown clear discrepancies, but mode shapes were nearly same. As the test rod closes to the bottom clamping region of the spacer grid, peak vibration amplitudes of the rod become smaller.

• Smart Structures and Systems
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• v.15 no.3
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• pp.787-806
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• 2015

Due to corrosion, a large number of belt conveyors support structure in industrial plants have deteriorated. Severe corrosion may result in collapse of the structures. Therefore, practical and effective structural assessment techniques are needed. In this paper, damage identification methods based on two specific local vibration modes, named periodic and isolated local vibration modes, are proposed. The identification methods utilize the facts that support structures have many identical members repeated along the belt conveyor and there exist some local modes within a small frequency range where vibrations of these identical members are much larger than those of the other members. When one of these identical members is damaged, this member no longer vibrates in those modes. Instead, the member vibrates alone in an isolated mode with a lower frequency. A damage identification method based on frequencies comparison of these vibration modes and another method based on amplitude comparison of the periodic local vibration mode are explained. These methods do not require the baseline measurement records of undamaged structure. The methods is capable of detecting multiple damages simultaneously. The applicability of the methods is experimentally validated with a laboratory model and a real belt-conveyor support structure.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.454-460
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• 1998

The vibration behavior of fuel rods has been analyzed by FEM in consideration of axial force and support spring constants. The axial compression force on the fuel rod in reactor decreases with the fuel rod burnup, and its decrease makes the natural frequencies of fuel rod considerably increase. The change of support spring constant can contribute to the remarkable change of the mode shapes, but not greatly to the natural frequencies. The reaction forces of support springs are obtained from normalizing the lst mode with the max. 0.2 mm displacement. The calculated reaction forces are larger than the previous results obtained by disregarding the deflections of the support springs.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.102-108
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• 2011

Support vector machines are well known for their outstanding performance in pattern recognition fields. One example of their applications is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel scheme that improves the speech/music classification of support vector machines based on the second-order conditional maximum a priori. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. According to experimental results, the proposed algorithm shows its compatibility and potential for improving the performance of support vector machines.

• International Journal of Contents
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• v.16 no.1
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• pp.44-56
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• 2020

The purpose of this study was to examine how the presentation mode (sequential- vs. simultaneous-mode) of information influences its evaluation. Three experiments revealed the interaction effect between the presentation mode and the valence of the product information. When respondents read about the positive aspects of the product, the evaluation was higher in the simultaneous presentation mode than in the sequential presentation mode. For negative product information, respondents' evaluation was higher in the sequential presentation mode than in the simultaneous presentation mode. The simultaneous presentation mode intensified the impact of the information valence on evaluation. This study proposed that the sequential and the simultaneous presentation modes prime high and low construal levels, respectively. The mediation analysis provides support for such a prediction. Finally, the mediating effect of construal levels in evaluation was shown to disappear when respondents focused on the product information for a longer duration, while the mediation effect remained when the response time was short.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.347-355
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• 2013

A damage estimation method for monopile support structure of offshore wind turbine using modal properties and committee of neural networks is presented for effective structural health monitoring. An analytical model for a monopile support structure is established, and the natural frequencies, mode shapes, and mode shape slopes for the support structure are calculated considering soil condition and added mass. The input to the neural networks consists of the modal properties and the output is composed of the stiffness indices of the support structure. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated stiffness indices from different neural networks are averaged. Ten damage cases are estimated using the proposed method, and the identified damage locations and severities agree reasonably well with the exact values. The accuracy of the estimation can be improved by applying the committee of neural networks which is a statistical approach averaging the damage indices in the functional space.

• Nuclear Engineering and Technology
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• v.29 no.5
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• pp.399-405
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• 1997

In this study a new phase separated spectral analysis algorithm is proposed to identify CSB vibration mode directly from ex-core neutron signals. Ex-core neutron signals can be decomposed into the global, core support barrel (CSB) beam mode, and CSB shell mode components by the new phase separation algorithm based on the characteristics of Fourier transform. By using the proposed algorithm and the conventional spectral analysis the vibration mode of the CSB and the fuel assembly of Ulchin-1 NPP were identified from measured ex-core neutron signals.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.23-29
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• 2016

Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.379-390
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• 2018

In this paper, a novel and effective damage diagnosis algorithm is proposed to detect and estimate damage using two stages least squares support vector machine (LS-SVM) and limited number of attached sensors on structures. In the first stage, LS-SVM1 is used to predict the unmeasured mode shapes data based on limited measured modal data and in the second stage, LS-SVM2 is used to predicting the damage location and severity using the complete modal data from the first-stage LS-SVM1. The presented methods are applied to a three story irregular frame and cantilever plate. To investigate the noise effects and modeling errors, two uncertainty levels have been considered. Moreover, the performance of the proposed methods has been verified through using experimental modal data of a mass-stiffness system. The obtained damage identification results show the suitable performance of the proposed damage identification method for structures in spite of different uncertainty levels.