• Tunnel and Underground Space
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• v.15 no.5 s.58
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• pp.352-358
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• 2005

For non-destructive testing of concrete structures, time and frequency domain method were applied to detect cavity in underground model and pier model. To interpret the measured data, time domain method made use of tomography which was completed with first arrivaltime and inversion method. In this steady, frequency domain method using Fourier transform was tried. Maximum frequency in the frequency domain was analyzed to calculate location of cavity.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.674-679
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• 1994

Acoustic signal such as speech and scattered sound, are generally a nonstationary process whose frequency contents vary at any instant of time. For time-varying signal, whether a nonstationary or a deterministic transient signal, a traditional frequency domain representation does not reveal the contents of signal characteristics and may lead to erroneous results such as the loss of desired characteristics features or the mis-interpretation for a wrong conclusion. A time-frequency domain representation is needed to characterize such signatures. Pseudo Wigner-Ville distribution (PWVD) is ideally suited for portraying nonstationary signal time-frequency domain and carried out by adapting the fast Fourier transform algorithm. In this paper, the important properties of PWVD were investigated using both stationary and nonstationry signatures by numerical examples PWVD was applied to acoustic sigtnatures to demonstrate its application for time-ferquency domain analysis.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.151-156
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• 2015

In this paper, we have proposed personal multimodal biometric authentication system based on face detection, recognition and speaker verification for smart-phone environment. Proposed system detect the face with Modified Census Transform algorithm then find the eye position in the face by using gabor filter and k-means algorithm. Perform preprocessing on the detected face and eye position, then we recognize with Linear Discriminant Analysis algorithm. Afterward in speaker verification process, we extract the feature from the end point of the speech data and Mel Frequency Cepstral Coefficient. We verified the speaker through Dynamic Time Warping algorithm because the speech feature changes in real-time. The proposed multimodal biometric system is to fuse the face and speech feature (to optimize the internal operation by integer representation) for smart-phone based real-time face detection, recognition and speaker verification. As mentioned the multimodal biometric system could form the reliable system by estimating the reasonable performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.151-157
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• 2019

Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

• Smart Structures and Systems
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• v.22 no.3
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• pp.359-368
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• 2018

A method is proposed for the identification of instantaneous frequencies (IFs) in time-varying structures. The proposed method combines a maximum gradient algorithm and a smoothing operation. The maximum gradient algorithm is designed to extract the wavelet ridges of response signals. The smoothing operation, based on a polynomial curve fitting algorithm and a threshold method, is employed to reduce the effects of random noises. To verify the effectiveness and accuracy of the proposed method, a numerical example of a signal with two frequency modulated components is investigated and an experimental test on a steel cable with time-varying tensions is also conducted. The results demonstrate that the proposed method can extract IFs from the noisy multi-component signals and practical response signals successfully. In addition, the proposed method can provide a better IF identification results than the standard synchrosqueezing wavelet transform.

• Journal of Ship and Ocean Technology
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• v.9 no.2
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• pp.21-28
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• 2005

Recently moored offshore vessels like as FPSO(Floating Production Storage Offloading) are frequently deployed in seas for a long time. For successful operation, the motion behavior of such a vessel in waves must be clarified in advance either theoretically or experimentally. It is of particular interest to examine the behavior, when swells are superposed to seas with different incident angle. Such a situation is actually reported in some offshore oilfield. In this paper, the motion of a FPSO in irregular waves including swells is studied in time domain. Hydrodynamic coefficients and wave forces are calculated in frequency domain using three-dimensional singularity distribution method. Time memory function and added mass at infinite frequency are derived by Fourier transform utilizing hydrodynamic damping coefficients. In the process, the numerical accuracy of added mass at infinite frequency is carefully examined in association with free decay simulations. It is found from numerical simulations that swells significantly affect the vertical motion of FPSO mainly because of their longer period compared to the ordinary sea waves. In particular, the roll motion is largely amplified because the dominant period of swell is closer to the roll natural period than that of seas.

• Smart Structures and Systems
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• v.30 no.1
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• pp.107-119
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• 2022

Modal parameters are widely used in bridge damage detection, finite element model (FEM) updating and design optimization. However, the conventional modal identification approaches require large number of sensors, enormous data processing workload, but normally result in mode shapes with low accuracy. This paper proposes a modal identification method of time-varying vehicle-bridge system using a single sensor. Firstly, the essential physical relationship between the instantaneous frequency of the vehicle-bridge system and the bridge mode shapes are derived. Subsequently, based on the synchroextracting transform, the instantaneous frequency of the system is tracked through the dynamic response collected by a single sensor, and further the modal parameters are estimated by using the derived physical relationship. Then numerical and experimental examples are conducted to examine the feasibility and effectiveness of the proposed method. Finally, the modal parameters identified by the proposed method are applied in bridge FEM updating. The results manifest that the proposed method identifies the modal parameters with high accuracy via a single sensor, and can provide reliable data for the FEM updating.

• Coupled systems mechanics
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• v.8 no.1
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• pp.55-70
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• 2019

This investigation is focused on the variations in transversely isotropic thick circular plate due to time harmonic thermomechanical sources. The homogeneous thick circular plate in presence and absence of energy dissipation and two temperatures has been considered. Hankel transform is used for solving field equations. The analytical expressions of conductive temperature, displacement components, and stress components are computed in the transformed domain. The effects of frequency at different values are represented graphically. Some specific cases are also figured out from the current research.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.78-86
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• 2010

The Spectrum Sensing Technology is the core technology of the Cognitive Radio (CR) System that is one of the future wireless communication technologies. In this paper, we proposed the efficient Spectrum Sensing Method using the Short Time Fourier Transform (STFT) that is the algorithm for Time-Frequency analysis of the raw data. Applied window function to STFT algorithm is a Kaiser window, it is piled up its 50% range. For the simulation, the DVB-H signal with the 6MHz bandwidth is used as the Input Signal. And we confirm the Spectrum Sensing result using Modified Periodogram Method, Welch's Method for compared with Short Time Fourier Transform Algorithm. And also, Spectrum Sensing Module is implemented using embedded board.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.