• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.478-485
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• 1998

The interior of open cavities exposed to a grazing flow is known to experience, strong periodic pressure, oscillations sustained for a wide range of flow velocities. In this study, an original approach was followed to develop a describing function model for the flow-excitation mechanism, governed by the shedding of discrete vortices within the shear layer over the orifice. A feedback loop analysis was performed to predict the frequency and the amplitude of the interior pressure fluctuations. Furthermore, a limit cycle stability analysis based on the extended Nyquist Stability criterion allowed the predictions of the onset and termination velocities for various modes. The analytical model was verified experimentally.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.619-623
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• 2008

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, it presents a study on the application of vibration signals to diagnose faults for a rotating machinery using the Mahalanobis distance-Taguchi system. RMS, crest factor and Kurtosis that is known as the statistical methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.412-430
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• 2003

In many practical problems in signal processing and control, the signal values are often restricted to belong to a finite number of levels. These questions are generally referred to as "finite alphabet" problems. There are many applications of this class of problems including: on-off control, optimal audio quantization, design of finite impulse response filters having quantized coefficients, equalization of digital communication channels subject to intersymbol interference, and control over networked communication channels. This paper will explain how this diverse class of problems can be formulated as optimization problems having finite alphabet constraints. Methods for solving these problems will be described and it will be shown that a semi-closed form solution exists. Special cases of the result include well known practical algorithms such as optimal noise shaping quantizers in audio signal processing and decision feedback equalizers in digital communication. Associated stability questions will also be addressed and several real world applications will be presented.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.1
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• pp.11-19
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• 2007

This paper presents two novel compensation circuits for leakage current and power supply noise (PSN) in phase locked loop (PLL) using a nanometer CMOS technology. The leakage compensation circuit reduces the leakage current of the charge pump circuit which becomes more serious problem due to the thin gate oxide and small threshold voltage in nanometer CMOS technology and the PSN compensation circuit decreases the effect of power supply variation on the output frequency of VCO. The PLL design is based on a 32nm predictive CMOS technology and uses a 0.9V power supply voltage. The simulation results show that the proposed PLL achieves a 88% jitter reduction at 440MHz output frequency compared to the PLL without leakage compensator and its output frequency drift is little to 20% power supply voltage variations. The PLL has an output frequency range of $40M{\sim}725MHz$ with a multiplication range of 11023, and the RMS and peak-to-peak jitter are 5ps and 42.7ps, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.31-38
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• 2018

Based on the measured data in the south western sea of Jeju Island during the SAVEX15(Shallow Water Acoustic Variability EXperiment 2015), the effect of internal waves on the PPD (Predictive Probability of Detection) of a sonar system was analyzed. The southern west sea of Jeju Island has complex flows due to internal waves and USC (Underwater Sound Channel). In this paper, sonar performance is predicted by probabilistic approach. The LFM (Linear Frequency Modulation) and MLS (Maximum Length Sequence) signals of 11 kHz - 31 kHz band of SAVEX15 data were processed to calculate the TL (Transmission Loss) and NL (Noise Level) at a distance of approximately 2.8 km from the source and the receiver. The PDF (Probability Density Function) of TL and NL is convoluted to obtain the PDF of the SE (Signal Excess) and the PPD according to the depth of the source and receiver is calculated. Analysis of the changes in the PPD over time when there are internal waves such as soliton packet and internal tide has confirmed that the PPD value is affected by different aspects.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.347-349
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• 2014

Model verification and validation (V&V) is a current research topic to build computational models with high predictive capability by addressing the general concepts, processes and statistical techniques. The hypothesis test for validity check is one of the model validation techniques and gives a guideline to evaluate the validity of a computational model when limited experimental data only exist due to restricted test resources (e.g., time and budget). The hypothesis test for validity check mainly employ Type I error, the risk of rejecting the valid computational model, for the validity evaluation since quantification of Type II error is not feasible for model validation. However, Type II error, the risk of accepting invalid computational model, should be importantly considered for an engineered products having high risk on predicted results. This paper proposes a technique named as the response-adaptive experimental design to reduce Type II error by adaptively designing experimental conditions for the validation experiment. A tire tread block problem and a numerical example are employed to show the effectiveness of the response-adaptive experimental design for the validity evaluation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.121-124
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• 2004

In this paper, we address an active vibration control system, which suppresses the vibration engaged by magnetically levitated stage. The stage system consists of a levitating platen with four permanent magnetic linear synchronous motors in parallel. Each motor generates vertical force fer suspension against gravity and propulsion force horizontally as well. This stage can generate six degrees of freedom motion via the vertical and horizontal forces. In the stage system, which represents the settling-time critical system. the motion of the platen vibrates mechanically. We designed an active vibration control system for suppressing vibration due to the stage moving. The command feedforward with inertial feedback algorithm is used fer solving stage system's critical problems. The components of the active vibration control system are accelerometers for detecting stage table's vibrations, a digital controller with high precise signal converters, and electromagnetic actuators.