• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.181-189
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• 2002

This research presents an analytical model to investigate the stability due to the ball bearing waviness in a rotating system supported by two ball bearings. The stiffness of a ball bearing changes periodically due to the waviness in the rolling elements as the rotor rotates, and it can be calculated by differentiating the nonlinear contact forces. The linearized equations of motion can be represented as a parametrically excited system in the form of Mathieu's equation, because the stiffness coefficients have time-varying components due to the waviness. Their solution can be assumed as a Fourier series expansion so that the equations of motion can be rewritten as the simultaneous algebraic equations with respect to the Fourier coefficients. Then, stability can be determined by solving the Hill's infinite determinant of these algebraic equations. The validity of this research is proved by comparing the stability chart with the time responses of the vibration model suggested by prior researches. This research shows that the waviness in the rolling elements of a ball bearing generates the time-varying component of the stiffness coefficient, whose frequency is called the frequency of the parametric excitation. It also shows that the instability takes place from the positions in which the ratio of the natural frequency to the frequency of the parametric excitation corresponds to i/2 (i= 1,2,3..).

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.699-703
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• 1993

When the error path can be modeled as a pure delay, an adaptive algorithm for slowly time varying system is proposed to minimize the sound pressure level. This algorithm makes it possible to use the fittered-x LMS algorithm with on-line delay modeling of the error path. Another simple adaptive algorithm for pure tone noise is proposed which eliminates the cross term in the multiple error filtered-x LMS algorithm.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.117-124
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• 1988

A new implementation of a noise tracking filter is prposed to eliminate time-varying 60 Hz noise and its harmonics and baselins wandering in biological signals. This technique was applied to ECG. Filter's notch frequency could track the power line frequency well and it showed much better characteristics than the conventional method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.10a
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• pp.55-59
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• 1993

Interaction between system and disturbance results in system with time-dependent parameter. Parameter variation due to interaction has random characteristics. Most of the randomly varying parameters in control problem is regarded as white noise random process, which is not a realistic model. In real situation those random variation is colored noise random process. Modified F-P-K equation is proposed to get the response of the random parametric system using some correction factor. Proposed technique is employed to obtain the colored noise parametric system response and confirmed via Monte-Carlo Simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.7
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• pp.644-650
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• 2010

Among various elements to affect customer's evaluation of vehicle quality, BSR(Buzz, Squeak, Rattle) are considered to be a mostly contributing factor. In this paper, we provide the test method which can be used to reduce the BSR noise of instrument panel in a vehicle. First, potential source regions of the instrument panel for BSR are localized by using the vibration-excitor and near-acoustic field visualization system. Then, subjective evaluation of BSR noise from the detected potential noise source regions is made with the Zwicker's loudness and time-varying loudness methods. This illustrative analysis reveals that current experimental methods can be used as a test procedure to systematically tackle BSR issues in early stage of the vehicle development cycle, which can result in the reduction of the production cost.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.46-50
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• 2001

Adaptive signal processing is used to acoustic echo canceller. adaptive noise canceller and adaptive algorithm among adaptive algorithms is mainly used because the structure is simple and computa LMS algorithm has trade-off between the converge speed and the steady state error. In this paper, step-size of adaptive algorithm is varied with orthogonality Principles of optimal filter to get fasts though small steady state error. Time varying step-size is determined proportional to the maximum vector of LMS algorithm. As results of simulations, the adaptive algorithm with proposed time-v compared with conventional ones.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.605-615
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• 2010

Intercarrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) systems, which causes substantial performance degradation in time-varying fading channels, is analyzed. An equivalent spreading code formulation is derived based on the analogy of OFDM and code division multiple access (CDMA) systems. Techniques as linear multiuser detection in CDMA systems are applied to suppress the ICI in OFDM systems. The performance of linear detection, measured using multiuser efficiency and asymptotic multiuser efficiency, is analyzed given the assumption of perfect channel state information (CSI), which serves as an upper bound for the performance of practical systems. For systems without CSI, time domain and frequency domain channel estimation based linear detectors are proposed. The performance gains and robustness of a linear minimum mean square error (LMMSE) filter over a traditional filter (TF) and matched filter (MF) in the high signal-to-noise ratio (SNR) regime are demonstrated with numerical simulation results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.722-725
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• 2014

The spatial focusing of time reversal Lamb waves on a plate has attracted considerable attention for identifying the location of an input source. This study investigates the spatial focusing performance on a plate with respect to the number of piezoelectric (PZT) sensors for varying locations of input sources. In particular, a small number of PZT sensors produce spatial focusing through the virtual sensor effect due to reflection of Lamb waves at plate edges. The spatial focusing performance with respect to the number of PZT sensors is quantified in terms of signal to noise ratio through numerical simulation and its implication is discussed.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.473-480
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• 2004

In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.