• Title/Summary/Keyword: Short Time Fourier

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A Study on the Wavelet Transform of Acoustic Emission Signals Generated from Fusion-Welded Butt Joints in Steel during Tensile Test and its Applications (맞대기 용접 이음재 인장시험에서 발생한 음향방출 신호의 웨이블릿 변환과 응용)

  • Rhee, Zhang-Kyu
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.1
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    • pp.26-32
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    • 2007
  • This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

Effective time-frequency characterization of Lamb wave dispersion in plate-like structures with non-reflecting boundaries

  • Wang, Zijian;Qiao, Pizhong;Shi, Binkai
    • Smart Structures and Systems
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    • v.21 no.2
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    • pp.195-205
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    • 2018
  • Research on Lamb wave-based damage identification in plate-like structures depends on precise knowledge of dispersive wave velocity. However, boundary reflections with the same frequency of interest and greater amplitude contaminate direct waves and thus compromise measurement of Lamb wave dispersion in different materials. In this study, non-reflecting boundaries were proposed in both numerical and experimental cases to facilitate time-frequency characterization of Lamb wave dispersion. First, the Lamb wave equations in isotropic and laminated materials were analytically solved. Second, the non-reflecting boundaries were used as a series of frames with gradually increased damping coefficients in finite element models to absorb waves at boundaries while avoiding wave reflections due to abrupt property changes of each frame. Third, damping clay was sealed at plate edges to reduce the boundary reflection in experimental test. Finally, the direct waves were subjected to the slant-stack and short-time Fourier transformations to calculate the dispersion curves of phase and group velocities, respectively. Both the numerical and experimental results suggest that the boundary reflections are effectively alleviated, and the dispersion curves generated by the time-frequency analysis are consistent with the analytical solutions, demonstrating that the combination of non-reflecting boundary and time-frequency analysis is a feasible and reliable scheme for characterizing Lamb wave dispersion in plate-like structures.

A Study on the Wavelet Transform of Acoustic Emission Signals Generated from Fusion-Welded Butt Joints in Steel during Tensile Test and its Applications (맞대기 용접 이음재 인장시험에서 발생한 음향방출 신호의 웨이블릿 변환과 응용)

  • Rhee Zhang-Kyu;Yoon Joung-Hwi;Woo Chang-Ki;Park Sung-Oan;Kim Bong-Gag;Jo Dae-Hee
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2005.05a
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    • pp.342-348
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    • 2005
  • This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform (WFT or SIFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform (WT) is used to decompose the acoustic emission (AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

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Time-frequency Analysis of Train Vibration Using Order Analysis and Correlation (오더분석 및 상관관계를 활용한 철도차량 진동 데이터의 시간-주파수 분석)

  • Choi, Sung-Hoon;Igusa, Takeru;Park, Choon-Soo
    • Journal of the Korean Society for Railway
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    • v.12 no.6
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    • pp.989-995
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    • 2009
  • Short-time Fourier transforms (STFT) are useful for analyzing signals with harmonics that vary with time. If the variation of the harmonics with time is smooth, such as in kinematic vibrations in vehicles, then it is possible to improve the STFT using order spectra and correlation analysis. In this paper, it is shown how correlation analysis can be performed when the speed signal is noisy or unknown and then it is shown how order spectra become simple to compute after this analysis. The results are illustrated by an analysis of axle and car body vibrations in the prototype high-speed train, HSR-350x.

Power Quality Disturbances Detection and Classification using Fast Fourier Transform and Deep Neural Network (고속 푸리에 변환 및 심층 신경망을 사용한 전력 품질 외란 감지 및 분류)

  • Senfeng Cen;Chang-Gyoon Lim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.1
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    • pp.115-126
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    • 2023
  • Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

Extraction Method of Ultrasound Spectral Information using Phase-Compensation and Weighted Averaging Techniques (위상 보상과 가중치 평균을 이용한 의료 초음파 신호의 주파수 특성 추출 방법)

  • Kim, Hyung-Suk;Yi, Joon-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.4
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    • pp.959-966
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    • 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.

Representation of cutting forces and tool deflection in end milling using Fourier series (엔드밀 가공에서 푸리에 급수를 이용한 절삭력 및 공구변형 표현)

  • Ryu S.H.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.781-785
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    • 2005
  • Cutting forces and tool deflection in end milling are represented as the closed form of tool rotational angle and cutting conditions. The discrete cutting forces caused by tool entry and exit are continued using the Fourier series expansion. Tool deflection is predicted by direct integration of the distributed loads on cutting edges. Cutting conditions, tool geometry, run-outs and the stiffness of tool clamping pan are considered for cutting forces and tool deflection estimation. Compared to numerical methods, the presented method has advantages in short prediction time and the effects of feeding and run-outs on cutting forces and tool deflection can be analyzed quantitatively. This research can be effectively used in real time machining error estimation and cutting condition selection for error minimization since the ferm accuracy is easily predicted by tool deflect ion curve.

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A Study on Propagation of Guided Waves in a Steam Generator Tube (증기발생기 세관에서의 유도초음파 전파에 관한 연구)

  • 송성진;박준수;김재희;김준영;김영환
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.5
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    • pp.353-361
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    • 2004
  • Propagation of the guided waves in a steam generator (SG) tube was investigated. Dispersion curves and the incident angles corresponding to the specific modes were calculated for the SG tube. The modes of guided wave were identified by time-frequency diagrams obtained by short time Fourier transform. Group velocities were also determined from the time-frequency diagrams obtained at the different separations of transducers. In experiment. distinct mode conversion was not observed when the guided ultrasound passed curved region of the S/G tube. The optimum mode of guided wave for the inspection of SG tube was suggested and verified by experiments.

Analysis of Impulse Dispersion for IR-UWB Antenna Using Time-Frequency Analysis (시간-주파수 분석을 이용한 IR-UWB 안테나 임펄스 분산 특성 분석)

  • Koh, Young-Mok;Ra, Keuk-Hwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.21 no.12
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    • pp.1371-1379
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    • 2010
  • This paper presents an analysis of impulse dispersion for impulse radio ultra-wide band(IR-UWB) antenna. A set of antenna structure configurations are highlighted with verification based on the STFT(Short Time Fourier Transform) in 3.1~5.1 GHz: first, a taper-slotted antenna allowing the optimal impulse transmission, and second, 4 types of the omni-directional IR-UWB antenna using different feed structures(microstrip line, and CPW(Coplanar Waveguide)). The proposed STFT allows the analysis of the IR-UWB antenna's dispersion characteristic.