• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2046-2052
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• 2016

Ramp metering is one of the most efficient and widely used control methods for an intelligent transportation management system on a freeway. Its objective is to control and upgrade freeway traffic by regulating the number of vehicles entering the freeway entrance ramp, in such a way that not only the alleviation of the congestion but also the smoothing of the traffic flow around the desired density level can be achieved for the maintenance of the maximum mainline throughput. When the cycle of the signal detection is larger than that of the system process, the density tracking problem needs to be considered in the form of the discrete-time system. Therefore, a discrete-time sliding mode control method is proposed for the ramp metering problem in the presence of both input constraint in the on-ramp and exogenous disturbance in the off-ramp considering the random behavior of the driver. Simulations were performed using a validated second-order macroscopic traffic flow model in Matlab environment and the simulation results indicate that proposed control method can achieve better performance than previously well-known ALINEA strategy in the sense that mainstream flow throughput is maximized and congestion is alleviated even in the presence of input constraint and exogenous disturbance.

• Journal of Power Electronics
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• v.13 no.3
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• pp.400-408
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• 2013

This paper presents a discrete state-space controller using state feedback control and feed-forward decoupling to provide a desirable control bandwidth and control stability for dynamic voltage restorers (DVR). The paper initially discusses three typical applications of a DVR. The load-side capacitor DVR topology is preferred because of its better filtering capability. The proposed DVR controller offers almost full controllability because of the multi-feedback of state variables, including one-beat delay feedback. Feed-forward decoupling is usually employed to prevent disturbances of the load current and source voltage. Directly obtaining the feed-forward paths of the load current and source voltage in the discrete domain is a complicated process. Fortunately, the full feed-forward decoupling strategy can be easily applied to the discrete state-space controller by means of continuous transformation. Simulation and experimental results from a digital signal processor-based system are included to support theoretical analysis.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.147-156
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• 2011

This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI's DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.567-575
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• 2001

This paper suggests new method to get fixed size parameter from different length of voice signals. The efficiency of speech recognizer is determined by how to compare the similarity(distance of each pattern) of the parameter from voice signal. But the variation of voice signal and the difference of speech speed make it difficult to extract the fixed size parameter from the voice signal. The method suggested in this paper is to normalize the parameter at fixed size by using the 2 dimension DCT(Discrete Cosine Transform) after representing the parameter by spectrogram. To prove validity of the suggested method, parameter extracted from 32 auditory filter-bank(it estimates auditory nerve firing probabilities) is used for the input of neural network after being processed by 2 dimension DCT. And to compare with conventional methods, we used one of conventional methods which solve time alignment problem. The result shows more efficient performance and faster recognition speed in the speaker dependent and independent isolated word recognition than conventional method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.6
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• pp.27-33
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• 1984

This paper is an experimental gaudy on the digital hardware implementation of the R2-MF Receiver for 32 channel configurations used in signalling systems between ESS. There are many methods to detect MF signal by DSP techniques, but the requirement for MF detection needs not sharp frequency response, needs only decision about some specific frequencies exist or not at discrete frequency sampling points. The hardware used to implement this algorithm is Am 2900 series "bit-slice microprocessor" chips based on the microprogramming techniques for real time signal processing. And we used the additional Z-80A processor chips for the system control and the decision about which is the right MF signal from the detected MF spectrums. Hence we could enhance the flexibilities of the hardware and the software, this leads that this system is well suits for signalling systems used in TDM ESS.n TDM ESS.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.26-38
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• 1988

This paper describes three methods for the estimation of the impulse reponse in an indoor acoustic transfer system which rather has long reverberation time by the cross spectrum. The first method, which is the conventional one, will use the white noise as the source signal. Therefore, the very long time window data and numerous number of DFT are necessary for this estimation. The second method has been disigned in order to shorten the length of time window of the first method by using a burst of noise as the source signal. The third method which will be suggested in this paper uses too types of definite signal with short duration time of the source signal. According to the view point of computation capacity, and estimation accuracy of the impulse response, the compared experimental results show that the third method will be better than the others.

• Journal of the Korean Magnetics Society
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• v.6 no.3
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• pp.174-178
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• 1996

A method was studied which simulate signal and noise for magneto-optical disk drive system Recorded mark patterns and incident laser beam were modeled and discretized. Using them readout waveformj and amplitude were simulated. Adding Gaussian random noise to the readout signal and executing one dimensional discrete FFT (Fast Fourier Transform) algorithm signal and noise spectrum was estimated. From the spectrum, CNR (Carrier to Noise Ratio) was obtained.

• Journal of the Korean Society of Safety
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• v.6 no.2
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• pp.21-30
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• 1991

In this paper, we study effect of waveness at the optical surface roughness measurement. In generally, waveness components cause errors in calculation of the roughness value of metal surface. We study about surface roughness signals In the frequency domain for separate two signal component of real roughness and waveness by digital signal processing methods. Thereafter, determine low and high Component of frequency spectrum. By this separating frequency value we design liner low and high pass filter which cutoff frequency is 1 Hz. After this process, converted each filtered spectrum by inverse discrete fourier transformation to time domain waveness and real roughness signals We calculate surface roughness value from filtered roughness signals. For evaluate this method, we use five specimens roughness signal which obtained from optical surface roughness measuring system in 3mm/s moving speed with 0.1 mm laser beam spot size As a result, we obtain more linerized roughness value than that of unfiltered roughness signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2329-2338
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• 1997

A conventional digital receiver sampled a baseband signal and processed it digitally for demodulation. But now we can sample at sufficiently high speed a wideband signal to take enough discrete data values due to the advent of economic high-speed ADC. With this technical background, a wideband frequency-division-multiplexed signal can be undersampled and channelized in digital domain by DFT analysis filter using the theory of polyphase. In this paper, we propose a new digital receiver which can digitally process the multichannel received signal by sampling at IF band, develop a mathematical theory and algorithm, and analyze the performance by using C-language simulaation. The proposed receiver can demodulate analog and digital FM signals.