• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.728-731
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• 1997

This paper discusses approximation modelling of discrete-time linear time-varying system(LTVS). The wavelet transform is considered as a tool for representing and approximating a LTVS. The joint time-frequency properties of wave analysis are appropriate for describing the LTVS. Simulation results is included to illustrate the potential application of the technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.8-15
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• 2005

The analysis of Rader signal that have non-linearity variable phase is signal that contact easily in several fields such as radar, telecommunication, seismic, sonar and biomedical applications. In generally, Non-stationary signal means that spectral characteristics are varying with time and instantaneous frequency is only one frequency or narrow range of frequencies varying as a function of time. Therefore, Instantaneous frequency is vary important variable that understanding physical characteristic of signal. This paper was describes continuous wavelet transform to determine instantaneous frequency at non-staionary signal and compare to existing method. When white noise or various frequency is overlapped each other in sign, existing method was can not decide corrected instantaneous frequency, but when used continuous wavelet transform, very well decide correctly frequency regardless of component of signal.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.585-587
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• 1998

It is suggested that the PWM inverter is controlled by Digital Software Programming. VVVF(Variable Voltage Variable Frequency) inverter control being used by PWM control for driving the motor with speed-varying, makes the PWM pattern with calculating the output voltage and frequency, and with controlling the carrier and signal, so actually this method is difficult to correspond with driving the motor by using voltage-varying and frequency-varying. Therefore this research suggested the new algorithm controlled by micro processor which is already stored by various PWM form of output voltage by using fundamental data of the carrier and signal. The PWM wave can be controlled with real time by using extra hardware and digital software and to speed up program processing, the control signals to switch the power semi-conductor of three phase PWM inverter, simultaneously use the output signal by microprocessor and extra hardware, and control signal by software. In the end, this method was proved by applying to Three Phase Voltage-type Inverter.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.26-32
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• 2003

We propose new time-frequency (TF) tools for analyzing linear time-varying (LTV) systems and nonstationary random processes showing hyperbolic TF structure. Obtained through hyperbolic warping the narrowband Weyl symbol (WS) and spreading function (SF) in frequency, the new TF tools are useful for analyzing LTV systems and random processes characterized by hyperbolic time shifts. This new TF symbol, called the hyperbolic WS, satisfies the hyperbolic time-shift covariance and scale covariance properties, and is useful in wideband signal analysis. Using the new, hyperbolic time-shift covariant WS and 2-D TF kernels, we provide a formulation for the hyperbolic time-shift covariant TF symbols, which are 2-D smoothed versions of the hyperbolic WS. We also propose a new interpretation of linear signal transformations as weighted superposition of hyperbolic time shifted and scale changed versions of the signal. Application examples in signal analysis and detection demonstrate the advantages of our new results.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1454-1462
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• 2008

This paper is focused on the analysis of the noise and vibration measured near the wheelset of the high-speed trains using a time-varying frequency transform as a preliminary research of running monitoring. Due to the non-stationary characteristics, it is necessary to examine noise and vibration of the train with time-varying frequency transforms. In this paper, the short-time Fourier transform method is utilized - the stored data is localized by modulating with a window function, and Fourier transform is taken to each localized data. For the examination, the non-stationary noise and vibration of the high-speed train's wheelset are measured by using some microphones and accelerometers, and those signals are stored in a on-board data acquisition system. The non-stationary random signal analyses with the short-time Fourier transform are performed, and the result are classified as follows; auto-spectral density, cross-spectral density, frequency response, and coherence functions. From those functions, it is possible to observe the frequency characteristics of sleepers, switchers, tunnels, and steel bridges. Also, some distinct peaks, which are not dependent upon the train's speed, are identified from the results.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.137-140
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• 2020

Orthogonal time frequency space (OTFS) modulation is considered as one of the solutions to cope with high mobility channel environments. It converts the time-varying channel to the near-constant channel response in the delay-Doppler domain. This modulation scheme also benefits from the diversity in two-dimensional modulation. According to recent researches, this method outperforms the conventional OFDM modulation, especially in high-speed channel conditions. In this paper, to investigate the performance of OTFS in a practical system, channel estimation in the delay-Doppler domain is compared with the conventional method in the time-frequency domain at different mobile speeds. Simulation results confirm that the delay-Doppler domain channel estimation brings a better performance compared to the conventional one under the same overhead rate.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2647-2655
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• 2002

This research presents an analytical model to investigate the stability due to the ball bearing waviness i n a rotating system supported by two ball bearings. The stiffness of a ball bearing changes periodically due to the waviness in the rolling elements as the rotor rotates, and it can be calculated by differentiating the nonlinear contact forces. The linearized equations of motion can be represented as a parametrically excited system in the form of Mathieu's equation, because the stiffness coefficients have time -varying components due to the waviness. Their solution can be assumed as a Fourier series expansion so that the equations of motion can be rewritten as the simultaneous algebraic equations with respect to the Fourier coefficients. Then, stability can be determined by solving the Hill's infinite determinant of these algebraic equations. The validity of this research is proved by comparing the stability chart with the time responses of the vibration model suggested by prior researches. This research shows that the waviness in the rolling elements of a ball bearing generates the time-varying component of the stiffness coefficient, whose frequency is called the frequency of the parametric excitation. It also shows that the instability takes place from the positions in which the ratio of the natural frequency to the frequency of the parametric excitation corresponds to i/2 (i=1,2,3..).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.181-189
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• 2002

This research presents an analytical model to investigate the stability due to the ball bearing waviness in a rotating system supported by two ball bearings. The stiffness of a ball bearing changes periodically due to the waviness in the rolling elements as the rotor rotates, and it can be calculated by differentiating the nonlinear contact forces. The linearized equations of motion can be represented as a parametrically excited system in the form of Mathieu's equation, because the stiffness coefficients have time-varying components due to the waviness. Their solution can be assumed as a Fourier series expansion so that the equations of motion can be rewritten as the simultaneous algebraic equations with respect to the Fourier coefficients. Then, stability can be determined by solving the Hill's infinite determinant of these algebraic equations. The validity of this research is proved by comparing the stability chart with the time responses of the vibration model suggested by prior researches. This research shows that the waviness in the rolling elements of a ball bearing generates the time-varying component of the stiffness coefficient, whose frequency is called the frequency of the parametric excitation. It also shows that the instability takes place from the positions in which the ratio of the natural frequency to the frequency of the parametric excitation corresponds to i/2 (i= 1,2,3..).

• Smart Structures and Systems
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• v.33 no.3
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• pp.201-215
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• 2024

Spline chirplet transform and local maximum synchrosqueezing are introduced to present a novel structural instantaneous frequency (IF) identification method named local maximum synchrosqueezing spline chirplet transform (LMSSSCT). Namely spline chirplet transform (SCT), a transform is firstly introduced based on classic chirplet transform and spline interpolated kernel function. Applying SCT in association with local maximum synchrosqueezing, the LMSSSCT is then proposed. The index of accuracy and Rényi entropy show that LMSSSCT outperforms the other time-frequency analysis (TFA) methods in processing analytical signals, especially in the presence of noise. Numerical examples of a Duffing nonlinear system with single degree of freedom and a two-layer shear frame structure with time-varying stiffness are used to verify the effectiveness of structural IF identification. Moreover, a nonlinear supported beam structure test is conducted and the LMSSSCT is utilized for structural IF identification. Numerical simulation and experimental results demonstrate that the presented LMSSSCT can effectively identify the IFs of nonlinear structures and time-varying structures with good accuracy and stability.