• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.7
• /
• pp.573-581
• /
• 2014

We proposed a hopping phase estimator to demodulate the received signals without any hopping information in frequency hopping spread spectrum systems. The demodulation process in this paper is as follows: hopped frequency tracking is accomplished by choosing a frequency component with maximum amplitude after taking discrete Fourier transform and a hopping frequency estimator which estimates the phase generated by hopped frequency is established through difference product and down-sampling. We obtained the probability density function and variance performance of the proposed estimator and confirmed that the analysis and the simulation results were agreed with each other.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.05a
• /
• pp.457-462
• /
• 2007

This paper reports on the research which investigates acoustic signals acquired in turning with rough and finish simultaneously. The material is aluminum thin pipe. Two acoustic sensors were set on CNC machine. One was set on the finish bite and the other the rough. Two signals were first analyzed in order to consider how much the acoustic signal from the finish bite was coupled by that from the rough. A simple data collecting system to acquire signals from the finish was then determined because two acoustic signals were little coupled. Second the fundamental experiments were accomplished to study the effects of machine vibration and material state. The signal characteristics due to surface defects were studied from the collected acoustic signal data. The signal analysis was based on real time data, root mean squared average and frequency spectrum by fast fourier transform. As a result, the acoustic signals were made effects by machine condition, material structure. The acoustic signal from the finish bite was closely correlated with surface quality. Two types surface micro defects were then evaluated by the signal characteristics.

• Wind and Structures
• /
• v.10 no.1
• /
• pp.45-60
• /
• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.2
• /
• pp.237-242
• /
• 2011

This paper proposes a detection algorithm for each section which detects the voiced section, unvoiced section, and the silence section at each frame using a multi-layer perceptron neural network. First, a power spectrum and FFT (fast Fourier transform) coefficients obtained by FFT are used as the input to the neural network for each frame, then the neural network is trained using these power spectrum and FFT coefficients. In this experiment, the performance of the proposed algorithm for detection of the voiced section, unvoiced section, and silence section was evaluated based on the detection rates using various speeches, which are degraded by white noise and used as the input data of the neural network. In this experiment, the detection rates were 92% or more for such speech and white noise when training data and evaluation data were the different.

• Journal of Sensor Science and Technology
• /
• v.24 no.3
• /
• pp.169-174
• /
• 2015

In this study, we developed a system to detect the various defects in the metallic objects using the phenomenon that the defects cause the changes of the natural resonant frequencies. Our system consists of a FFT Amp, an Auto Impact Hammer, a Hammer controller and a PC. Auto Impact Hammer creates vibrations in the metallic objects when tapped on the surface. These vibrational signals are converted to the voltage signals by an acceleration sensor attached to the metallic part surface. These analog voltage signals were fed into an ADC (analog-digital converter) and an FFT (fast fourier transform) conversion in the FFT Amp to obtain the digital data in the frequency domain. Labview graphical program was used to process the digital data from th FFT amp to display the spectrum. We compared those spectra with the standard spectrum to find the shifts in the resonant frequencies of the metal parts, and thus detecting the defects. We used PCB's acceleration sensor and TI's TMS320F28335 DSP (digital signal processor) to obtain the resolution of 2.93 Hz and to analyze the frequencies up to 44 kHz.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.3
• /
• pp.167-172
• /
• 2010

In this paper, we analyze and simulate the performance of a pilot signal detection algorithm based on fast Fourier transform (FFT) for several system parameters in order to detect advanced television system committee digital television (ATSC DTV) signals. Requirements for detecting DTV signals are analyzed. And the detection performance is compared according to sensing frequency and time. Form the simulation results, it is confirmed that the signal detection performance increases as the sensing frequency rises. The results of this paper can be applied for implementing cognitive radio (CR) systems in the frequency band of DTV signals.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.4
• /
• pp.959-966
• /
• 2010

Quantitative ultrasound analysis provides fundamental information of various ultrasound parameters using spectral information of the short-gated radiofrequency(RF) data. Therefore, accurate extraction of spectral information from backscattered RF signal is crucial for further analysis of medical ultrasound parameters. In this paper, we propose two techniques for calculating a more accurate power spectrum which are based on the phase-compensation using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio(SNR). The simulation results demonstrate that the proposed method estimates better results with 10% smaller estimation variances compared to the conventional methods.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.1
• /
• pp.8-14
• /
• 2014

Brightness temperature spectra acquired from FTIR(Fourier Transform Infrared)-SCADS (Standoff Chemical Agent Detection System) could be available for detection and identification of the chemical agents and pollutants from different background. IR spectrum range of 770 to 1350 $cm^{-1}$ is corresponding to "atmospheric window". A 2-dimensional(2D) brightness temperature spectrum was drawn from combining each data point through automatic continuous scanning of FTIR along with altitude and azimuth. At higher altitude, temperature of background was decreased but scattering effect of atmospheric gases was increased. Increase in temperature difference between background and blackbody in SCADS at higher temperature causes to increases in peak intensity of $SF_6$. This approach shows us a possibility that 2D visual information is acquired from scanning data with a single FTIR-SCADS.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.17 no.6 s.123
• /
• pp.507-514
• /
• 2007

This paper reports on the research which investigates acoustic signals acquired in turning with rough and finish simultaneously. The material is aluminum thin pipe. Two acousto-ultrasonic sensors were set on the finish and the rough bite of the CNC machine. It was first evaluated that one source was affected by the other. It was found that two signals were little affected each other, and that the acoustic signal from the finish bite was more related to the surface defects. Signals from the finish bite only were then analyzed in order to observe several types of surface defects. Second the fundamental experiments were accomplished to study the effects of machine vibration and material state. The signal characteristics due to surface defects were studied from the collected acoustic signals. The analysis was based on real time data, root mean squared average and frequency spectrum by fast fourier transform. As a result, the acoustic signals were made effects by machine condition, material structure. The acoustic signal from the finish bite was closely correlated with surface quality. Two types surface micro defects were then evaluated by the signal characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.11
• /
• pp.1914-1922
• /
• 2008

In this paper, examined characteristics of EEG(electroencephalogram) variation when the stimulation was given to lung-wan(CV12), Shin-gwol(CV8) and Gwan-won(CV4) which were some of the acupuncture point, through indirect moxibustion and No stimulation. The EEG signals were measured before the stimulation, during the stimulation, and 1 hour after the stimulation. The measured time domain data were converted to the frequency domain data FFT(Fast Fourier Transform) and frequency power spectrum. Then the $\alpha,\beta,\delta$, and $\theta$ waves were analyzed for variation to the amplitude of vibration according to the stages of stimulation.