• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.273-278
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• 2002

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the booming sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for booming sound of a passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.141-146
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• 2007

A gear whine sound due to the axle system is one of the most important sound qualities in a sport utility vehicle (SUV). In the previous research about the gear whine sound, it was known that it is difficult to evaluate the gear whine sound objectively by using the only A-weighted sound pressure level because of the masking effect. In this paper, for the objective evaluation of the axle-gear whine sound, the characteristics of the axle-gear whine sound is at the first investigated based on the synthetic sound technology and the new objective evaluation method for the axle-gear whine sound is developed by using the sound metrics, which is the psychoacoustics parameters, and the artificial neural network (ANN) used for the modeling of the correlation between objective evaluation and subjective evaluation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.1003-1008
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• 2004

In our life, we have used many digital appliances. They helped us to improve the quality of lift but sometimes gave us unsatisfactory result because they produce specific noise. Especially a vacuum cleaner produces a great deal of noise that is very annoying. So we need to study what sound metrics affect human sensibility. In this paper, we will study sound quality index for vacuum cleaner. The subjective evaluation of vacuum cleaner sound can be indicated to objective parameters by sound metrics of psychoacoustics. The artificial neural network can estimate the nonlinear characteristics of relation between subjective evaluation and sound metrics. We applied the artificial neural network to the development of sound quality index for vacuum sound.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.628-634
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• 2003

Rumbling sound is one of the most important interior sound of a passenger cu. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network th[ ory has been applied to derivation of sound quality index fur rumbling sound of a passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.727-730
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• 2005

Cellulose based Electro-Active Papers (EAPap) is very promising material due to its merits in terms of large bending deformation, low actuation voltage, ultra-lightweight, and biodegradability. These advantages make it possible to utilize applications, such as artificial muscles and achieving flapping wings, micro-insect robots and smart wall papers. This paper investigates the in-plane strains of EAPap under electric fields, which are useful for a contractile actuator application The preparation of EAPap samples and the in-plane strain measurement system are explained, and the test results are shown in terms of electric field, frequency and the oriental ions of the samples. The power consumption and the strain energy of EAPap samples are discussed. Although there are still unknown facts in EAPap material, this in-plane strain may be useful for artificial muscle applications.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.439-446
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• 2005

The theoretical method is developed to investigate the vibration characteristics of the combined cylindrical shells with an annular plate joined to the shell at any arbitrary axial position. The structural rotational coupling between shell and plate is simulated using the rotational artificial spring. For the translational coupling, the continuity conditions for the displacements of shell and plate are used. For the uncoupled annular plate, the transverse motion is considered and the in-plane motions are not. And the additional transverse and in-plane motions of the coupled annular plate by shell deformation are considered in analysis. Theoretical formulations are based on Love's thin shell theory. The frequency equation of the combined shell with an annular plate is derived using the Rayleigh-Ritz approach. The effect of inner-to-outer radius ratio, axial position and thickness of annular plate on vibration characteristics of combined cylindrical shells is studied. To demonstrate the validity of present theoretical method, the finite element analysis is performed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3186-3198
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• 1996

When a robot is to have contact with its enviornment, such as a medi-care robot, it would be advantageous for the robot to have a high compliance. For this reason, a robot having not only a flexible link but also an actuator with compliance, is desirable. This paper is concerned with the position and vibration control of 1 degree of freedom flexible robot using a pneumatic artificial muscle actuator. The dynamics of the manipulator assumed to be and Euler-Bernoulli beam are derived on the basis of the linear mathematical modle. Although this pneumatic artifical muscle actuator has many merits for the compliance robot, it is difficult to make an effective control scheme of this system because of ths nonlinearity and uncertainty on the dynamics of the actuator. By designing a controller using .mu.-synthesis, robust performance against measurement noise, various modeling uncertainties on the dynamics of the servo valve, actuator and mainpulator, is achieved. The effectiveness of the proposed control method is illustrated through simulations and experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1011-1016
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• 2015

Gas piping systems in power plants and factories are always influenced by the mechanical vibrations of rotational machines such as pumps, blowers, and compressors. Unusual vibrations in a gas piping system influence possible leakages of liquids or gases, which can lead to large explosive accidents. Real-time measurements of unusual vibrations in piping systems in situ prohibit them from being possible leakages owing to the repeated fatigue of vibrations. In this paper, a non-contact 3-dimensional measurement system that can detect the vibrations of a solid body and monitor its vibrational modes is introduced. To detect the displacements of a body, a stereoscopic camera system is used, through which the major vibration types of solid bodies (such as X-axis-major, Y-axis-major, and Z-axis-major vibrations) can be monitored. In order to judge the vibration types, an artificial neural network is used. The measurement system consists of a host computer, stereoscopic camera system (two-camera system, high-speed high-resolution camera), and a measurement target. Through practical application on a flat plate, the measured data from the non-contact measurement system showed good agreement with those from the original vibration mode produced by an accelerator.