• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2149-2151
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• 2004

The time-frequency domain reflectometry(TFDR) is well known to detect and locate a fault in a coaxial cable[3]. Traditional reflectometry methods have been achieved in either the time domain or frequency domain only. However, the time-frequency domain reflectometry utilizes time and frequency information of a reflected signal passed through a cable to detect and locate the fault. The purpose of this paper is to find appropriate time-frequency distribution function suitable for a TFDR system. Choosing the appropriate time-frequency distribution function implies one can detect the fault and estimate the location accurately. We consider and compare adequate time-frequency distribution function on the basis of experimental results.

• Structural Engineering and Mechanics
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• v.49 no.3
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• pp.411-425
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• 2014

This paper presents the processing of nonlinear features associated with a damage event by quadratic time-frequency distributions for damage identification in a frame structure. A time-frequency distribution is a function which distributes the total energy of a signal at a particular time and frequency point. As the occurrence of damage often gives rise to non-stationary, nonlinear structural behavior, simultaneous representation of the dynamic response in the time-frequency plane offers valuable insight for damage detection. The applicability of the bilinear time-frequency distributions of the Cohen class is examined for the damage assessment of a frame structure from the simulated acceleration data. It is shown that the changes in instantaneous energy of the dynamic response could be a good damage indicator. Presence and location of damage can be identified using Choi-Williams distribution when damping is ignored. However, in the presence of damping the Page distribution is more effective and offers better readability for structural damage detection.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.827-832
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• 2003

There has been a number methods for the presentation of time-frequency analysis of non-stationary signal. In this paper, STFT(short time Fourier transform), wavelet transform, Wigner distribution, and higher order Wigner distribution are discussed in details with simulation signals. They are also applied to the analysis of the wave propagation of a semi finite beam. Wigner distribution and higher order Wigner distribution have good time-frewuency resolutions. Wavelet transform is required for impact analysis but should be applied carefully. STFT suffers from time-frequency resolutions. Each method is has its advantage and disadvantage depending on each application signals.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.268-275
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• 2008

In this paper, we introduce a new method for detecting and estimating faults on a power line using the time-frequency domain reflectometry system. The system rests upon time-frequency signal analysis and uses a chirp signal which is multiplied by Gaussian envelope. The chirp signal is used as a reference signal, and we can get the reflected signal from a fault on a wire. To detect and estimate faults, we analyze the reflected signal by Wigner time-frequency distribution function and normalized time-frequency cross correlation function. In this paper we design an optimal reference signal for power line and implement a system for estimating fault distance on a power line with the TFDR implemented by PXI equipments. This approach is verified by some experiments with HIV 2.25mm power lines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1060-1067
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• 2005

In this paper, we generalize the shift-invariance properties of linear time-frequency distributions to the fractional Fourier domains that interpolate between the time and frequency domains. Magnitude-wise shift invariance in arbitrary fractional Fourier domains distinguishes the short-time Fourier transform (STFT) among all linear time-frequency distributions and simplifies the interpretation of the resultant distribution. We prove that the STFT is the only linear distribution that satisfies the magnitude-wise shift-invariance property in the fractional Fourier domains.

• Wind and Structures
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• v.20 no.5
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• pp.661-682
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• 2015

This study investigates the use of time-frequency coherence analysis for detecting and evaluating coherent "structures" of surface pressures and wind turbulence components, simultaneously on the time-frequency plane. The continuous wavelet transform-based coherence is employed in this time-frequency examination since it enables multi-resolution analysis of non-stationary signals. The wavelet coherence quantity is used to identify highly coherent "events" and the "coherent structure" of both wind turbulence components and surface pressures on rectangular prisms, which are measured experimentally. The study also examines, by proposing a "modified" complex Morlet wavelet function, the influence of the time-frequency resolution and wavelet parameters (i.e., central frequency and bandwidth) on the wavelet coherence of the surface pressures. It is found that the time-frequency resolution may significantly affect the accuracy of the time-frequency coherence; the selection of the central frequency in the modified complex Morlet wavelet is the key parameter for the time-frequency resolution analysis. Furthermore, the concepts of time-averaged wavelet coherence and wavelet coherence ridge are used to better investigate the time-frequency coherence, the coherently dominant events and the time-varying coherence distribution. Experimental data derived from physical measurements of turbulent flow and surface pressures on rectangular prisms with slenderness ratios B/D=1:1 and B/D=5:1, are analyzed.

• Journal of KSNVE
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• v.6 no.3
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• pp.341-347
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• 1996

Vibration analysis is one of the most powerful tools available for the detection and isolation of incipient faults in mechanical systems. The methods of vibration analysis in use today and under continuous study are broad band vibration monitoring, time domain analysis, and frequency domain analysis. In recent years, great interest has been generated concerning the use of time- frequency repesentation and its application for a machinery diagnostics and condition monitoring system. The objective of the study described in this paper was to develop a new diagnostic tool for the rotating machinery. This paper introduces a new time frequency representation. Directional Winger-Ville Distribution, which analyese the time-frequency structure of the rotating machinery vibration.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.2 s.21
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• pp.38-48
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• 2005

Instantaneous frequency of doppler signals is used to get the information of the relative velocity and the miss distance between a missile and a corresponding target. In this paper, we have performed time-frequency analysis and instantaneous frequency estimation with Short Time Fourier Transform(STFT), Wigner Ville Distribution(WVD) and Continuous Wavelet Transform(CWT) about the doppler signals generated by moving targets. Performance evaluation was performed using simulated doppler signals generated by a single moving target and two moving targets. From the results of the time-frequency analysis, we found that WVD method was the most efficient instantaneous frequency estimator among the three methods. But in case of two moving targets, WVD method got cross talks and CWT method got oscillation when two doppler frequencies were close to each other.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.729-734
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• 2008

Vibroarthrographic(VAG) signals, emitted by human knee joints, are non-stationary and multi-component in nature and time-frequency distributions(TFD) provide powerful means to analyze such signals. The objective of this paper is to classify VAG signals, generated during joint movement, into two groups(normal and patient group) using the characteristic parameters extracted by time-frequency transform, and to evaluate the classification accuracy. Noise within TFD was reduced by singular value decomposition and back-propagation neural network(BPNN) was used for classifying VAG signals. The characteristic parameters consist of the energy parameter, energy spread parameter, frequency parameter, frequency spread parameter by Wigner-Ville distribution and the amplitude of frequency distribution, the mean and the median frequency by fast Fourier transform. Totally 1408 segments(normal 1031, patient 377) were used for training and evaluating BPNN. As a result, the average value of the classification accuracy was 92.3(standard deviation ${\pm}0.9$)%. The proposed method was independent of clinical information, and showed good potential for non-invasive diagnosis and monitoring of joint disorders such as osteoarthritis and chondromalacia patella.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.270-276
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• 1999

Fourier transform has been one of the most commonly used tools in study of frequency characteristics of signal. However, based on the Fourier transform. it is hard to tell whether a signal's frequency contents evolve in time or not. Recently, to overcome Fourier transform fault. not to represent non-stationary signal, time-frequency analysis methods are developed and those can represent informations of signal's time and frequency at the same time. In this study we analysed ultrasonic signal for degraded SUS 316 with time-frequency analysis method. In particular the methods such as short time Fourier(STFT) and Wigner-Ville distribution(WVD) were used to extract frequency contents and characteristics from ultrasonic signals.