• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.4
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• pp.281-287
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• 2016

Fiber Bragg grating (FBG) sensors are applied in structural health monitoring (SHM) in various application fields because of their ease of multiplexing and capability of performing absolute measurements. Moreover, the packaging methods of FBG sensors accelerate their commercialization rapidly. However, long-term SHM exposes the FBG sensors to cyclic thermal loads, and a investigation is required because it finally leads to the signal instability of the FBG sensors. In this study, the effects of sensor packaging methods two methods are generally used for the FBGs: (bonding both sides of the FBG or bonding the FBG directly on signal stability of FBG sensors are investigated. Tests are conducted on specimens in a thermal chamber, over a temperature range from $-20^{\circ}C$ to $60^{\circ}C$ for 300 cycles. Signal characteristics such as Bragg wavelength, light intensity and full width at half maximum are examined and are compared with those of the FBG sensors, obtained in a previous study under direct bonding conditions. From the comparison, it is observed that the FBG sensors with bonding on both sides of the FBG demonstrate higher signal stabilities when exposed to cyclic thermal loads during long-term SHM. Consequently, it guarantees more effectiveness when packaging the FBG sensors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.507-515
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• 2008

In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.231-239
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• 2009

The filtered-x LMS (FX-LMS) algorithm has been applied to the active noise control (ANC) system in an acoustic duct. This algorithm is designed based on the FIR (finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filteredu LMS algorithm (FU-LMS) based on infinite impulse response (IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter. In this paper, the recursive LMS algorithm with variable step size and smoothing error filter is designed. This recursive LMS algorithm, called FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct such as the intake system of an automotive. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal of which the instantaneous frequency is variable. Test results demonstrate that the FU-VSSLMS algorithm has superior convergence performance to the FX-LMS algorithm and FX-LMS algorithm. It is successfully applied to the ANC system in a short duct.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.146-155
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• 2012

The filtered-x LMS(FX-LMS) algorithm has been applied to the active noise control(ANC) system in an acoustic duct. This algorithm is designed based on the FIR(finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm(FU-LMS) based on infinite impulse response(IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter. In this paper, the recursive LMS algorithm with variable step size and smoothing error filter is designed. This recursive LMS algorithm, called FU-VSSLMS algorithm, uses an IIR filter. With fast convergence and good stability, this algorithm is suitable for the ANC system in a short acoustic duct such as the intake system of an automotive. This algorithm is applied to the ANC system of a short acoustic duct. The disturbance signals used as primary noise source are a sinusoidal signal embedded in white noise and the chirp signal of which the instantaneous frequency is variable. Test results demonstrate that the FU-VSSLMS algorithm has superior convergence performance to the FX-LMS algorithm and FX-LMS algorithm. It is successfully applied to the ANC system in a short duct.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.967-974
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• 2017

In this paper, a differential-braking-based yaw moment control system was developed to guarantee robust performance against road bank angle. A new target yaw rate model was established by combining the signal from a lateral acceleration sensor and 2-DOF single track model. In addition, a disturbance observer was utilized to take into account parameter uncertainties in yaw dynamics and to improve robust performance of the controller. CARSIM, which is a multi-DOF vehicle dynamic simulation tool, was used to verify the performance of the proposed controller in various driving scenarios. The simulation results indicate that the stability of the vehicle was robustly maintained by the controller, which is characterized by the reflection of the signal of a lateral acceleration sensor signal and by the compensation of the errors in the model parameters via the disturbance observer.

• Journal of Power Electronics
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• v.17 no.2
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• pp.501-513
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• 2017

The fundamental small-signal modeling of lithium-ion (Li-ion) batteries and a parameter evaluation approach are investigated in this study to describe the dynamic behaviors of small signals accurately. The main contributions of the study are as follows. 1) The operational principle of the small signals of Li-ion batteries is revealed to prove that the sinusoidal voltage response of a Li-ion battery is a result of a sinusoidal current stimulation of an AC small signals. 2) Three small-signal measurement conditions, namely stability, causality, and linearity, are proved mathematically proven to ensure the validity of the frequency response of the experimental data. 3) Based on the internal structure and electrochemical operational mechanism of the battery, an AC small-signal model is established to depict its dynamic behaviors. 4) A classical least-squares curve fitting for experimental data, referred as Levy's method, are introduced and developed to identify small-signal model parameters. Experimental and simulation results show that the measured frequency response data fit well within reading accuracy of the simulated results; moreover, the small-signal parameters identified by Levy's method are remarkably close to the measured parameters. Although the fundamental and parameter evaluation approaches are discussed for Li-ion batteries, they are expected to be applicable for other batteries.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.33-35
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• 2000

We propose a intelligent controller for FACTS(Flexible AC Transmission System) device to stabilize a power system. In order to identify the nonlinear characteristics of the power system and to estimate a control signal, an artificial neural network is utilized. The control signal which is provided for FACTS device installed in the network is produced. The proposed controller is applied to Unified Power Flow Controller(UPFC) to verified the effectiveness of the proposed control system. The results show that the proposed nonlinear FACTS controller is able to enhance the transient stability of three machine nine bus power system.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.4
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• pp.94-99
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• 1997

A new method of stbilizing the sagnac interferometric fiber optic current sensor inteh presence of birefringences and phase is presented. This method is realized by dividing the output of the ac current signal with the modulation signal output. Using the technique the stability of the current sensor was improve dmore than 4.5 times at 800Arms for 2 hours. The current sensor also shows good linearity up to 100Arms.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.249-256
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• 1990

In this study, LPC cepstrum coefficients are used as feature vector extracted from AR model of EMG signal, and a reduced-connection network whlch has reduced connection between nodes is constructed to classify and recognize EMG functional classes. The proposed network reduces learning time and improves system stability Therefore it is Ehown that the proposed network is appropriate in recognizing function of EMG signal.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.6
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• pp.376-382
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• 1988

A small-signal low-frequency disturbance of the input line affects the regulated-output voltage of the series resonant converter. To mitigate the detrimental effect, the output feedback PI-controller is employed. Small-signal linear models are represented to characterize the closed loop series resonant converter system. Design equations for the PI-controller which satisfy stability and percent ripple conditions are derived from the closed-loop linear model. Experimental results are presented which show excellent correlation with theory.