• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.875-878
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• 2006

In the case of a vibration sensitive equipment, it require a vibration free environment to provide its proper function, therefore, it is very important to predict precisely vibration environment of microelectronics production facility due to adjacent blast work. However, it is not easy to evaluate a quantitative vibration response of structure due blast because it can be determined by the characteristics of vibration sources, propagation through rock and soil and dynamic properties of building. In this paper, vibration influence evaluation of micro-electronic Production building induced from adjacent blast activity was performed by real measurement data obtained on ground and structure at same time. And blast vibration allowable limit on ground was supposed by measurement data analysis in order to avoid operation error of precision equipments

• Korean Journal of Applied Biomechanics
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• v.16 no.2
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• pp.55-63
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• 2006

The purpose of this study was to investigate the effects of vibration exercise using surface electromyography. Seven male collegiate wrestlers were participated in this study. Each subject stood on the platform and the vibration was induced for 1min. WEMG8 EMG system was used to record muscle activity from Vastus lateralis, Biceps Femoris, Tibialis Anterior, and Gastrocnemius. The EMG data were sampled for 30 sec. during non-vibration and vibration half squat position, respectively. The raw data were band pass filtered to remove noise and full wave rectified Paired sample t-test were performed to see the differences of maximum and average EMG between non-vibration and vibration trials. The results indicated that vibration produced much more muscle contraction than that of non-vibration trial for all selected muscles even though the significant difference was found only from Biceps Femoris. This phenomenon was due to the individual differences so care must be taken to evaluate vibration intensity and position before personal training.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.9-17
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• 2023

In this paper, we propose a one-class vibration anomaly detection system for bearing defect diagnosis. In order to reduce the economic and time loss caused by bearing failure, an accurate defect diagnosis system is essential, and deep learning-based defect diagnosis systems are widely studied to solve the problem. However, it is difficult to obtain abnormal data in the actual data collection environment for deep learning learning, which causes data bias. Therefore, a one-class classification method using only normal data is used. As a general method, the characteristics of vibration data are extracted by learning the compression and restoration process through AutoEncoder. Anomaly detection is performed by learning a one-class classifier with the extracted features. However, this method cannot efficiently extract the characteristics of the vibration data because it does not consider the frequency characteristics of the vibration data. To solve this problem, we propose an AutoEncoder model that considers the frequency characteristics of vibration data. As for classification performance, accuracy 0.910, precision 1.0, recall 0.820, and f1-score 0.901 were obtained. The network design considering the vibration characteristics confirmed better performance than existing methods.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.64-67
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• 2005

A vibration monitoring system for a small size wind turbine (WIT) is established and operated. The monitoring system consists of monolithic integrated chip accelerometer for vibration monitoring, anemometers for wind data acquisition and auxiliary sensors for atmospheric data. Using the monitoring system, vibration response of a 6kW stand alone WIT generator is investigated. Acceleration data of the WIT tower under various operation condition is acquired in real time using LabVIEW and the data are remotely transferred from the test site to the laboratory in school by internet. Vibration response characteristics of the tower structure are diagnosed in the aspect of stability of W/T. Wind data and electrical power performance are also investigated with the stability problem.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1138-1144
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• 2013

This paper proposes a tactile transfer and display method between a data glove and vibration motors module. The data glove is developed to capture the hand postures and to measure the grip forces. The measured data are simplified with the proposed 5-bit transfer and display algorithm, and the vibration motors module is developed to display the measured hand posture and grip force to the operator. The proposed 5-bit algorithm contains both an 8-step hand posture and 4-step grip force level information for tactile transfer to the vibration motors module. Also, the effectiveness of the proposed method is shown through several experiments.

• Journal of KSNVE
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• v.9 no.4
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• pp.769-777
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• 1999

Research on vibration of a vehicle with a transversely mounted 4-cylinder engine was performed using a vector synthesis method, Data of the engine vibration for the vector synthesis method was obtained experimentally and the data was ODS-fitted to calculate vibration level on any engine location assuming that the engine is rigid body in the frequency range of interest. In order to derive the excitation force on the vehicle body, the displacements were converted from the acceleration of engine. The transfer functions from engine mounts to toe pan on the floor were obtained experimentally. The vibration level on the toe pan was predicted by multiplying the excitation force by the transfer function. The predicted vibration level was compared with experimental data and the result was reasonable. Using the developed method, analysis was made for the effect of body fixture conditions of the vehicle when testing the engine vibration and for the effect of the transfer functions when the engine is installed or when the engine is removed. Finally the degree of contribution for 12 transfer paths was calculated.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.3
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• pp.30-37
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• 2009

The majority of the causes for the failures of power transformers in operation are mechanical defects due to vibration. The vibration phenomenon was measured from the power transformers in operation in the substations. The vibration measurement was performed in a $6{\times}4$ structure on one side of each transformer. The vibrations of the measured points were presented in two and three dimensions and analyzed. The results, according to the elapsed year of the transformer and the load capacity to the transformer, were analyzed. These results could be used as basic data with which to establish vibration standards for power transformers. In addition, the load capacity-vibration phenomenon correlation was examined and regression analysis was performed to derive the estimation function. The vibration phenomenon according to the elapsed yeah was also estimated to derive the function. Then the analysis of the power transformers was used to set vibration standards for them based on the vibration data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.812-816
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• 2014

Recently, there is an increasing interest on railway noise and vibration. Accordingly, the importance of technology that can assess the vibration and structural noise caused due to the railway operation is increasing. Additionally, the need to construct a railway noise and vibration database which is a basic data for a reliable railway noise and vibration assessment as well is increasing. However, the problem is that the currently constructed database fails to include the factors influencing the occurrence of noise and vibration sufficiently. Therefore, In this paper, design a railway noise and vibration database that includes those factors sufficiently and which enables the continuous data management and accumulation.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.67-73
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• 2021

In this paper, in order to prevent the fall of the drone, a study was conducted to collect vibration data from the motor connected to the propeller of the drone, and to predict the abnormal vibration of the drone using recurrent neural network (RNN) and long short term memory (LSTM). In order to collect the vibration data of the drone, a vibration sensor is attached to the motor connected to the propeller of the drone to collect vibration data on normal, bar damage, rotor damage, and shaft deflection, and abnormal vibration data are collected through LSTM and RNN. The root mean square error (RMSE) value of the vibration prediction result were compared and analyzed. As a result of the comparative simulation, it was confirmed that both the predicted result through RNN and LSTM predicted the abnormal vibration pattern very accurately. However, the vibration predicted by the LSTM was found to be 15.4% lower on average than the vibration predicted by the RNN.

• Journal of KSNVE
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• v.8 no.5
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• pp.814-820
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• 1998

Vibration data from two blasting sites were analyzed to determine the sufficient sample number for blasting vibration estimation. Most important result is that much more than 30 sample data and succeeding measurement are necessary to estimate confident blasting vibration level and to determine limit scaled distance.