• Journal of the Korean Solar Energy Society
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• v.32 no.spc3
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• pp.179-184
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• 2012

This research on building Integrated Photovoltaic System replacing windows and doors with amorphous silicon thin film PV windows and doors installing same exact mount on Mock-up. The windows and doors should be installed in different angle and bearing so that we can analyse the amount of electricity from them. The objective of the research is to evaluate and investigate the relationship between factors(intensity of solar radiation, PV window surface temperature, incidence angle, and sky conditions) that affects performance of PV window and performance. The range and method of this research is to establish monitoring system and analysis the data from the monitoring system to evaluate the performance of PV windows that have thin film of solar battery. We should evaluate the insolation according to the position of PV window, output, and surface temperature according to months and seasons so that we can figure out the relationship between these. And we should investigate the relationship between performance and efficiency according to incidence angle and sky condition so that we can figure out the correlation between factors and performance.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09c
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• pp.37-46
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• 2010

Marine clays are soft soil deposits having complicated mineralogy and formation characteristics. Thus, characterization of its geotechnical behavior has been a main issue for geotechnical engineers. Nowadays, the importance and applications of geophysical exploration on marine clays are increasing significantly according to the accuracy, efficiency, and reliability of geophysical survey technology. For marine clays, seismic survey is effective for density and elasticity characterization, while electro-magnetic wave provides the information about the fluid conductivity phenomena inside soil. For practical applications, elastic wave technology can evaluate the consolidation state of natural marine clay layers and estimate important geotechnical engineering parameters of artificially reclaimed marine deposits. Electrical resistivity can provide geophysical characteristics such as particle cementation, pore geometry shape, and pore material phase condition. Furthermore, nondestructive geophysical monitoring is applicable for risk management and efficiency enhancement during natural methane gas extraction from gas hydrate-bearing sediments.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.343-348
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• 2013

In line with the advances in factory automation, various pieces of equipment are now operated in batch processes controlled by computers. However, many kinds of faults can occur in complicated and large systems, which can result in low productivity and economic loss. The reliability and safety of systems have been studied because of the difficulty of determining the severity and location of faults. Therefore, it is necessary to detect and diagnose such faults in order to guarantee the reliability and safety of the equipment. In this paper, a diagnosis method for the ball bearings of a hydraulic pump is applied using a vibration signal for the maintenance of injection molding equipment. The bearings' defects are selected as a main failure mode through a failure mode and effect analysis (FMEA). Usually, there are nonlinear and impulse components of vibration in a ball bearing with faults. For the effective fault diagnosis of a ball bearing, nonlinear diagnostic methods and time-frequency analysis are applied, in addition to the methods currently used, such as power spectrum, time series analysis, and statistical methods. As a result of this study, a failure diagnosis system is provided that is useful even for non-experts. This is a condition-based method that makes it possible to resolve problems in a timely and economical way, in contrast to the prior method, which required regular but wasteful maintenance based on the experience of expensive external experts.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.215-222
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• 2000

The reinforced roadbed should have the ability to spread out the load intensity lower than the bearing capacity of the subgrade of track structure as well as to prevent the softening of roadbed by providing appropriate stiffness in the roadbed, thus fully supports the track structures. Full scale reinforced roadbeds with several different types of monotoring sensors was also constructed to evaluate the performance of each reinforced roadbed through the continuous monitoring while the train operation. In this study, Field tests such as PLT, SASW were also carried out at each reinforced roadbed. The results of the field and lab tests, installation and calibration of sensors, as well as construction condition of the reinforced roadbed are presented.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1233-1240
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• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1787-1798
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• 1995

Monitoring and diagnosis of the operating machine mean evaluating the condition of a machine such as the detection of the defects and the prediction of the time to failure in the machine elements, while it is running. In this study, a technique of automatic diagnosis using probability concept is studied and the analyses of the pattern comparison are introduced. An expert system, which is able to analyze the automatic identification of the multiple defects in the ball bearings, is also developed. Finally, to confirm the effectiveness of the programmed algorithms, some tests were made with specimens of the ball bearings involving the multiple defects. The proposed system reasonably predicts the defects.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.95-102
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.537-543
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• 2003

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the vibration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.111-121
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• 2018

Many problems in rotating machinery such as aircraft engines, wind turbines and motors are caused by bearing defects. The abnormalities of the bearing can be detected by analyzing signal data such as vibration or noise, proper pre-processing through a few signal processing techniques is required to analyze their frequencies. In this paper, we introduce the condition monitoring method for diagnosing the failure of the rotating machines by analyzing the vibration signal of the bearing. From the collected signal data, the normal states are trained, and then normal or abnormal state data are classified based on the trained normal state. For preprocessing, a Hamming window is applied to eliminate leakage generated in this process, and the cepstrum analysis is performed to obtain the original signal of the signal data, called the formant. From the vibration data of the IMS bearing dataset, we have extracted 6 statistic indicators using the cepstral coefficients and showed that the application of the Mahalanobis distance classifier can monitor the bearing status and detect the failure in advance.

• Geomechanics and Engineering
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• v.23 no.3
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• pp.289-300
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• 2020

With the rapid development of the distributed strain sensing (DSS) technology, the strain becomes an alternative monitoring parameter to analyze slope stability conditions. Previous studies reveal that the horizontal strain measurements can be used to evaluate the deformation pattern and failure mechanism of soil slopes, but they fail to consider various influential factors. Regarding the horizontal strain as a key parameter, this study aims to investigate the stability condition of a locally loaded slope by adopting the variable-controlling method and conducting a strength reduction finite element analysis. The strain distributions and factors of safety in different conditions, such as slope ratio, soil strength parameters and loading locations, are investigated. The results demonstrate that the soil strain distribution is closely related to the slope stability condition. As the slope ratio increases, more tensile strains accumulate in the slope mass under surcharge loading. The cohesion and the friction angle of soil have exponential relationships with the strain parameters. They also display close relationships with the factors of safety. With an increasing distance from the slope edge to the loading position, the transition from slope instability to ultimate bearing capacity failure can be illustrated from the strain perspective.