• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.85-95
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• 2012

In this thesis, we develop a spectral analysis scheme to eliminate the spurious peaks generated in HRR Millimeterwave Seeker based on FMICW system. In contrast to FMCW system, FMICW system generates spurious peaks in the spectrum of its IF signal, caused by the periodic discontinuity of the signal. These peaks make the accuracy of the system depend on the previously estimated range if a band pass filter is utilized to eliminate them and noise floor go to high level if random interrupted sequence is utilized and in case of using staggering process, we must transmit several waveforms to obtain overlapped information. Using the spectral analysis one of the schemes such as IAA(Iterative Adaptive Approach) and SPICE(SemiParametric Iterative Covariance-based Estimation method) which were introduced recently, the spurious peaks can be eliminated effectively. In order to utilize IAA and SPICE, since we must distinguish between reliable data and unreliable data and only use reliable data, STFT(Short Time Fourier Transform) is applied to the distinguishment process.

• Composites Research
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• v.16 no.3
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• pp.58-67
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• 2003

To perform the realtime strain and fracture monitoring of the smart composite structures, two optical fiber sensor systems are proposed. The two types of the coherent sources were used for fracture signal detection - EDFA with FBG and EDFA with Fabry-Perot filter. These sources were coupled to EFPI sensors imbedded in composite specimens. To understand the characteristics of matrix crack signals, at first, we performed tensile tests using surface attached PZT sensors by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as short time Fourier transform (STFT) and wavelet transform (WT) for the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes. And, from the test of tensile load monitoring using optical fiber sensor systems, measured strain agreed with the value of electric strain gage and the fracture detection system could detect the moment of damage with high sensitivity to recognize the onset of micro-crack fracture signal.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.69-80
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• 2012

In this paper, we studied the time-domain measurement and analysis techniques using a network analyzer for characterization UWB antenna link radiating impulse signal. For this purpose, we developed the CZT(Chirp z-Transform) algorithm which has characterized zoom-in function and transformed the acquired data from network analyzer to time domain format. Using the CZT algorithm, we proves that it would be better efficient and more faster than the DFT for analyzing the waveform and also be able to zoom-in the arbitrary region.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.429-434
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• 2012

This paper presents a technology for manipulating external devices by Brain Computer Interface (BCI) system. Recently, BCI based rehabilitation and assistance system for disabled people, such as patient of Spinal Cord Injury (SCI), general paralysis, and so on, is attracting tremendous interest. Especially, electroencephalogram (EEG) signal is used to organize the BCI system by analyzing the signals, such as evoked potential. The general findings of neurophysiology support an availability of the EEG-based BCI system. We concentrate on the event-related synchronization of motor imagery EEG signal, which have an affinity with an intention for moving control of external device. To analyze the brain activity, short-time Fourier transform and particle swarm optimization are used to optimal feature selection from the preprocessed EEG signals. In our experiment, we can verify that the power spectral density correspond to range mu-rhythm(${\mu}8$~12Hz) have maximum amplitude among the raw signals and most of particles are concentrated in the corresponding region. Result shows accuracy of subject left hand 40% and right hand 38%.

• Geomechanics and Engineering
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• v.34 no.1
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• pp.1-15
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• 2023

This study conducts uniaxial compression tests on intact and single crack-contained rocks to investigate the time-frequency domain characteristics of acoustic emission (AE) signals monitored during the deformation failure process. A processing approach, short-time Fourier transform (STFT), is performed to obtain the evolution characteristics of time-frequency domain of AE signals. The AE signal modes at different deformation stages of rocks are different. Five modes of AE signal are observed during the cracking process of rocks. The evolution characteristics of time-frequency domain of AE signals processed by STFT can be utilized to evaluate the damage process of rocks. The difference of time-frequency domain characteristics between intact and cracked rocks is comparatively analyzed. The distribution characteristics of frequency changing from a single band-shaped cluster to multiple band-shaped clusters can be regarded as an early warning information of damage and failure of rocks. Meanwhile, the attenuation of frequency enables the exploration of rock failure trends.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.1002-1009
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• 2012

This paper shows the research about radar target recognition using the measured radar signals from MSU(Michgan State University) bistatic radar system. In this research, we first did the bistatic measurements at $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ using F-14, Mig-29, and F-22 scale models. Then, we extract the target feature vectors using time-frequency analysis methods such as STFT(Short Time Fourier Transform) and CWT(Continous Wavelet Transform) and perform the target classification test using MLP(Multi-layerd Perceptron) neural network. The results show that the target classification performance is too much dependent on the bistatic angles and the best performance is obtained at the $60^{\circ}$ bistatic angle.

• Composites Research
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• v.13 no.1
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• pp.40-49
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• 2000

The objective of this research is to develop the impact monitoring techniques providing impact identification and damage diagnostics of smart composite laminates susceptible to impacts. This can be implemented simultaneously by using the acoustic waves by the impact loads and the acoustic emission waves from damage. In the previous research, we have discussed the impact location detection process in which impact generated acoustic waves are detected by PZT using the improved neural network paradigm. This paper describes the implementation of time-frequency analysis such as the Short-Time Fourier Transform (STFT) and the Wavelet Transform (WT) on the determination of the occurrence and the estimation of damage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.361-364
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• 2003

The safe operation and reliable maintenance of nuclear power plants is one of the most fundamental and important tasks. It is known that a loose part such as a disengaged and drifting metal inside of reactor coolant systems might lead to a serious damage because of their impact on the components of the coolant system. In order to estimate the impact position of a loose par, three accelerometers attached to the wall of the coolant system have been used. These accelerometers measure the vibration of the coolant system induced by loose part impact. In the conventional analysis system, the low pass filtered version of the vibration data was used for the estimation of the position of a loose part. It is often difficult to identify the initial point of the impact signal by using just a low passed time signal because the impact wave is dispersed during propagation into the sensor. In this paper, the impact signal is analysed by use of various time frequency methods including the short time Fourier transform(STFT), the wavelet transform, and the Wigner-Vill distribution for finding a convenient way to identify the starting point of a impact signal and their advantages and limits are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.513-517
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• 2005

The condition monitoring of rotating machinery such as turbines, pumps and compressors, determine what repairs are needed to avoid shutdown and disassembly of the machine in an industrial plant Many diagnosis methods have been developed for use when the machine is running at steady state, the stationary condition. But much information can be gained about a rotor's condition during non-stationary conditions such as run-up and run-down. Order tracking analysis is a powerful tool for analyzing the condition of a rotating machine when its speed changes over time. Powerful OTA using digital signal processing has some advantages(cheap hardware, the powerful methods, the accurate post processing) and also some disadvantages(calculation time, high speed sampling). New OTA tool based on the chirplet transform is similar to the short time Fourier transform. But, it has good resolution at high speed like other OTA methods based STFT and more resolution for constant frequency components than re-sampling OTA.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.981-989
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• 2011

In this paper, we performed radar target classification for the five scale models using ultra-wideband measured signal. In order to compare the performance, the 2 GHz(2~4 GHz), 4 GHz(2~6 GHz), and 6 GHz(2~8 GHz) bandwidth were used. Short time Fourier transform(STFT) and continuous wavelet transform(CWT) are used for target feature extraction. Extracted feature vectors are used as input for the multi-layerd perceptron(MLP) neural network classifier. The results show that as the bandwidth is wider, the performance is better.