• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.1
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• pp.62-68
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• 2014

Recently, MRI(magnetic resonance imager) scanner is continually used for medical diagnosis and many biomedical researches. When it operates, however, intense noise is generated. The SPL(sound pressure level) of the noise approaches 130 dB especially in 3 T(Tesla) MRI. Meanwhile, more than 3 T MRI scanners have been developed to get higher-resolution images, so louder noise is expected in the future. The intense noise makes patients feel nervous and uncomfortable. Moreover, it could possibly cause hearing loss to patient in extreme cases. For this reason, some active noise control systems have been researched. One of them used feedback Filtered-X LMS(FXLMS) algorithm which is able to control only narrowband noises and possible to diverge in severe case. In this paper, we determine the property of MRI noise. Using the property, we applied a method of open-loop and adaptive control for reducing MRI noise at target point inside bore. We verified performance of the method with computer simulation and preliminary experiment. The results demonstrate that the method can effectively reduce MRI noise at target point.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.119-122
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• 2005

A study on motor current signature analysis has been executed for monitoring the fault of journal bearing due to wear. The air gap eccentricity of motor produces specific frequencies in motor current, the supplied current frequency plus and minus rotational rotor frequency. The air gap eccentricity is simulated by the clearance of Journal bearing. The amplitudes of the specific frequencies increase with the increasing clearances. The amplitudes of the specific frequencies continue to increase over the wear limit that is used in the manufacturer of the test motor. Though clear relations between the amplitudes of the specific frequencies and the clearances are not obtained in this paper, the specific frequencies can be used as an indicator of a journal bearing fault. Further study is necessary to make out the quantitative relations between the specific frequencies and the clearances.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.513-517
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• 2005

The condition monitoring of rotating machinery such as turbines, pumps and compressors, determine what repairs are needed to avoid shutdown and disassembly of the machine in an industrial plant Many diagnosis methods have been developed for use when the machine is running at steady state, the stationary condition. But much information can be gained about a rotor's condition during non-stationary conditions such as run-up and run-down. Order tracking analysis is a powerful tool for analyzing the condition of a rotating machine when its speed changes over time. Powerful OTA using digital signal processing has some advantages(cheap hardware, the powerful methods, the accurate post processing) and also some disadvantages(calculation time, high speed sampling). New OTA tool based on the chirplet transform is similar to the short time Fourier transform. But, it has good resolution at high speed like other OTA methods based STFT and more resolution for constant frequency components than re-sampling OTA.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.77-85
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• 2022

In this study, to diagnose the grinding state of a micro drill bit, a sensor attachment location was selected through random vibration analysis of the grinding unit of the micro drill-bit grinding system. In addition, the vibration data generated during the drill bit grinding were collected from the grinding unit for the grinding wheels under the steady and worn conditions, and data feature extraction and dimension reduction were performed. The wear of the micro-drill-bit grinding wheel was diagnosed by applying KNN, a machine-learning algorithm. The classification model showed excellent performance, with an accuracy of 99.2%. The precision, recall and f1-score were higher than 99% in both the steady and wear conditions.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.4
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• pp.239-246
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• 2005

In this study, a finite element analysis and a vibration test were performed to estimate the natural frequencies of mouse femurs with osteoporosis. Three groups of the femurs include the osteoporotic group, the treated group and the normal group. For the finite element analysis, the micro finite element model of the femur was reconstructed using the Micro-CT images and the Voxel mesh generation algorithm. In the vibration test, the natural frequencies were measured by the mobility test. from the results, the averaged natural frequencies in the osteoporotic group were the highest, followed by those in the treated group. The finite element models were validated within 15% errors by comparing the natural frequencies in the finite element analysis with those in the vibration test. The developed Micro-CT system, the Yokel mesh generation algorithm, the presented finite element analysis, and vibration test could be useful for the investigation of the structural change of the bone tissue, and the diagnosis and the treatment in the osteoporosis.

• Physical Therapy Korea
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• v.26 no.3
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• pp.11-22
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• 2019

Background: Sling exercises are frequently used for the rehabilitation process of patients with shoulder joint injuries, but research on the significant frequency intensity and appropriate treatment duration for sling exercises with local vibration stimulation is lacking. Objects: The aim of this study was to investigate the effects of sling exercise with vibration on shoulder range of motion (ROM), muscle strength, pain, and dysfunction in patients with a medical diagnosis of shoulder joint injury. Methods: Twenty-two patients were randomly assigned to the experiment and control groups. Six sling exercises with and without 50 Hz vibrations were applied in the experiment and control groups, respectively. Each exercise consisted of 3 sets of 5 repetitions performed for 6 weeks. The assessment tools used included shoulder joint range of motion, muscle strength, pain level, and shoulder pain and disability index for functional disability. We conducted re-evaluations before and 3 and 6 weeks after intervention. The changes in the measurement variables were analyzed and compared between the two groups. Results: The ROM of the external rotation of the shoulder joint had a significant interaction between the group and the measurement point (F=3.652, p<.05). In both groups, we found a significant increase in external rotation angle between the measurement points (p<.05). The flexor strength of the shoulder joint significant interaction between the group and the measurement point (F=4.247, p<.05). Both the experiment (p<.01) and control groups (p<.05) showed a significant increase in shoulder flexor strength at the measurement points. After 6 weeks of the interventions, both the groups showed significantly improved VAS (p<.01), SPADI (p<.01), and orthopedic tests (p<.01). However, there was no significant difference between the group and the measurement point in terms of the clinical outcomes observed. Conclusion: The sling exercise with local vibration of 50 Hz affected the external rotation of the shoulder range of motion and improved shoulder flexor strength in the patients with shoulder injuries. Therefore, we propose the use of the sling exercise intervention with vibration in the exercise rehabilitation of patients with shoulder joint injuries.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1529-1535
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• 2011

Improvement of the thermal efficiency in operation and maintenance of low- and medium-speed engines is a kind of never-ending requirement in the maritime power plant business. For the purpose of improving engine management efficiency, a principal factor that represents the fitness of the engine should be identified. Gas pressure, gas temperature, and vibration have all been used as this factor. However, they have limitations in terms of response speed and diagnosis accuracy. The EFR (engine fitness ratio) is suggested as a new diagnostic factor in this paper. The EFR is defined as the ratio of particular frequencies in the frequency domain and represents the fitness of an engine. It is calculated from the fluctuation pattern of the crankshaft angular speed. The EFR was verified using an experimental method for a low-speed engine and an analytic method for a medium-speed engine.

• Structural Engineering and Mechanics
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• v.65 no.3
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• pp.303-314
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• 2018

Shear walls are a typical member under a complex stress state and have complicated mechanical properties and failure modes. The separated-elements model Genetic Evolutionary Structural Optimization (GESO), which is a combination of an elastic-plastic stress method and an optimization method, has been introduced in the literature for designing such members. Although the separated-elements model GESO method is well recognized due to its stability, feasibility, and economy, its adequacy has not been experimentally verified. This paper seeks to validate the adequacy of the separated-elements model GESO method against experimental data and demonstrate its feasibility and advantages over the traditional elastic stress method. Two types of reinforced concrete shear wall specimens, which had the location of an opening in the middle bottom and the center region, respectively, were utilized for this study. For each type, two specimens were designed using the separated-elements model GESO method and elastic stress method, respectively. All specimens were subjected to a constant vertical load and an incremental lateral load until failure. Test results indicated that the ultimate bearing capacity, failure modes, and main crack types of the shear walls designed using the two methods were similar, but the ductility indexes including the stiffness degradation, deformability, reinforcement yielding, and crack development of the specimens designed using the separated-elements model GESO method were superior to those using the elastic stress method. Additionally, the shear walls designed using the separated-elements model GESO method, had a reinforcement layout which could closely resist the actual critical stress, and thus a reduced amount of steel bars were required for such shear walls.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.8
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• pp.801-806
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• 2015

Journal bearings support rotors using fluid film between the rotor and the stator. Generally, journal bearings are used in large rotor systems such as turbines in a power plant, because even in high-speed and load conditions, journal bearing systems run in a stable condition. To enhance the reliability of journal-bearing systems, in this paper, we study health-diagnosis algorithms that are based on the supervised learning method. Specifically, this paper focused on defining the unit of features, while other previous papers have focused on defining various features of vibration signals. We evaluate the features of various lengths or units on the separable ability basis. From our results, we find that one cycle datum in the time-domain and 60 cycle datum in the frequency domain are the optimal datum units for real-time journal-bearing diagnosis systems.