• 제목/요약/키워드: time-frequency analysis methods

검색결과 956건 처리시간 0.031초

Synchrosqueezed wavelet transform for frequency and damping identification from noisy signals

  • Montejo, Luis A.;Vidot-Vega, Aidcer L.
    • Smart Structures and Systems
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    • 제9권5호
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    • pp.441-459
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    • 2012
  • Identification of vibration parameters from the analysis of the dynamic response of a structure plays a key role in current health monitoring systems. This study evaluates the capabilities of the recently developed Synchrosqueezed Wavelet Transform (SWT) to extract instant frequencies and damping values from the simulated noise-contaminated response of a structure. Two approaches to estimate the modal damping ratio from the results of the SWT are presented. The results obtained are compared to other signal processing methods based on Continuous Wavelet (CWT) and Hilbert-Huang (HHT) transforms. It was found that the time-frequency representation obtained via SWT is sharped than the obtained using just the CWT and it allows a more robust extraction of the individual modal responses than using the HHT. However, the identification of damping ratios is more stable when the CWT coefficients are employed.

쑥뜸치료가 암환자의 심박변이도에 미치는 영향 (The Effects of Moxibustion on Heart Rate Variability in Cancer Patients)

  • 김옥희;최정은;윤정원;유화승
    • 대한암한의학회지
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    • 제16권1호
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    • pp.15-31
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    • 2011
  • Objective : The study aims to investigate the effect of moxibustion treatments on autonomic nervous system function of cancer patients through the evaluation of heart rate variability (HRV) biofeedback testing. Materials and Methods : Six cancer patients from inpatient care unit of Dunsan Oriental Hospital, Daejeon University were given three moxibustion treatment sessions every other day over one week period on five Oriental Medicine meridian points CV4, CV6, CV12, KD1, and PC8. HRV biofeedback was conducted before and after each treatment sessions. Three areas of analyses were done from the test conducted; Time Domain Analysis, Frequency Domain Analysis and Autonomic Nervous System (ANS) balance analysis. Results : Time Domain Analysis has shown increased Standard Deviation of all Normal R-R Intervals (SDNN), and decreased Mean Heart Rate and Physical Stress Index (PSI) levels, with statistical significance (P<0.05). In Frequency Domain Analysis, series of moxa treatments have increased Total Power (TP), Very Low Frequency Oscillation Power (VLF), High Frequency Oscillation Power (HF), normalized HF values while decreasing Low Frequency Oscillation Power (LF), normalized LF and LF/HF ratio with statistical significance (P<0.05). The values of ANS activity, ANS balance, Stress resistance, Stress index, have also shown significant changes. For cardiac stability stroke volume power (SP) and Blood Vessel Tension (BVT) were followed, which were both increased after treatment. All changes were statistically significant (P<0.05). Conclusion : The results have shown a positive correlation between the moxibustion treatments and autonomic nervous system responses on cancer patients through the HRV biofeedback testing. This study suggests possible application of moxibustion treatments for managing ANS functions of cancer patients, although additional studies with larger population are necessary to confirm the data.

한·중·일 환율 사이의 움직임 분석 - 분수공적분과 진동수영역의 인과성 - (Comovement and Forecast of won/dollar, yuan/dollar, yen/dollar: Application of Fractional Cointegration approach and Causal Analysis of Frequency Domain)

  • 정수관;원두환
    • 국제지역연구
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    • 제21권2호
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    • pp.3-20
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    • 2017
  • 본 연구는 원/달러 환율, 엔/달러 환율, 위안/달러 환율 사이의 관계를 분석하였다. 전통적인 공적분 방법은 환율 변수 사이에 공적분 관계를 명확하게 판별하기 어려운 것으로 알려졌다. 이를 고려하여 분수공적분 방법과 진동수영역의 인과성 분석이 이용되었다. 분석 결과 환율변수 사이에 분수공적분 관계가 존재하는 것을 확인할 수 있었다. 환율 사이에 장기적으로 동조화가 이루어지지만, 충격으로 발생한 이탈은 상당 기간 지속하는 장기기억을 가지는 것을 의미한다. 시간영역의 인과성 분석과 진동수영역의 인과성 분석결과는 다소 차이가 있지만, 원/달러 환율을 예측하는 데 엔/달러 환율이 유용한 것으로 나타났다. 분수공적분 접근방법과 진동수영역의 인과성 분석을 적절하게 활용한다면 기존 방법으로부터 설명되지 못하는 유용한 정보를 획득할 수 있을 것이다.

A Goodness-Of-Fit Test for Adaptive Fourier Model in Time Series Data

  • Lee, Hoonja
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.955-969
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    • 2003
  • The classical Fourier analysis, which is the typical frequency domain approach, is used to detect periodic trends that are of the sinusoidal shape in time series data. In this article, using a sequence of periodic step functions, describes an adaptive Fourier series where the patterns may take general periodic shapes that include sinusoidal as a special case. The results, which extend both Fourier analysis and Walsh-Fourier analysis, are applies to investigate the shape of the periodic component. Through the real data, compare the goodness-of-fit of the model using two methods, the adaptive Fourier method which is proposed method in this paper and classical Fourier method.

비정상 호흡 감지를 위한 신호 분석 (Signal Analysis for Detecting Abnormal Breathing)

  • 김현진;김진현
    • 센서학회지
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    • 제29권4호
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    • pp.249-254
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    • 2020
  • It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

Adaptive Complex Interpolator for Channel Estimation in Pilot-Aided OFDM System

  • Liu, Guanghui;Zeng, Liaoyuan;Li, Hongliang;Xu, Linfeng;Wang, Zhengning
    • Journal of Communications and Networks
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    • 제15권5호
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    • pp.496-503
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    • 2013
  • In an orthogonal frequency division multiplexing system, conventional interpolation techniques cannot correctly balance performance and overhead when estimating dynamic long-delay channels in single frequency networks (SFNs). In this study, classical filter analysis and design methods are employed to derive a complex interpolator for maximizing the resistible echo delay in a channel estimator on the basis of the correlation between frequency domain interpolating and time domain windowing. The coefficient computation of the complex interpolator requires a key parameter, i.e., channel length, which is obtained in the frequency domain with a tentative estimation scheme having low implementation complexity. The proposed complex adaptive interpolator is verified in a simulated digital video broadcasting for terrestrial/handheld receiver. The simulation results indicate that the designed channel estimator can not only handle SFN echoes with more than $200{\mu}s$ delay but also achieve a bit-error rate performance close to the optimum minimum mean square error method, which significantly outperforms conventional channel estimation methods, while preserving a low implementation cost in a short-delay channel.

Applicability Comparison of Transmission Line Parameter Extraction Methods for Busbar Distribution Systems

  • Hasirci, Zeynep;Cavdar, Ismail Hakki;Ozturk, Mehmet
    • Journal of Electrical Engineering and Technology
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    • 제12권2호
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    • pp.586-593
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    • 2017
  • Modeling busbar distribution system as a transmission line is an important subject of power line communication in the smart grid concept. This requires extraction of busbar RLGC parameters, accurately. In this study, a comparison is made between conventional and modified method for the aspect of optimum RLGC parameters extraction in the 1 MHz to 50 MHz frequency band. The usefulness of these methods is shown both in time and frequency-domain analysis. The frequency-domain analyzes show that the inherent power of modified method can eliminate the errors especially due to the discontinuities arise in conventional method. This makes the modeling approach of modified method more advantageous for the busbars due to its robustness against disturbances in the S-parameters measurements which cannot be eliminated with the calibration procedure. On the other hand, time-domain simulations show that the transmission line representation of the modified method is closer to physical reality by handling causality issues.

A combined spline chirplet transform and local maximum synchrosqueezing technique for structural instantaneous frequency identification

  • Ping-Ping Yuan;Zhou-Jie Zhao;Ya Liu;Zhong-Xiang Shen
    • Smart Structures and Systems
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    • 제33권3호
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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.

Modal parameters identification of heavy-haul railway RC bridges - experience acquired

  • Sampaio, Regina;Chan, Tommy H.T.
    • Structural Monitoring and Maintenance
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    • 제2권1호
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    • pp.1-18
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    • 2015
  • Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

Vibration-based damage monitoring of harbor caisson structure with damaged foundation-structure interface

  • Lee, So-Young;Nguyen, Khac-Duy;Huynh, Thanh-Canh;Kim, Jeong-Tae;Yi, Jin-Hak;Han, Sang-Hun
    • Smart Structures and Systems
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    • 제10권6호
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    • pp.517-546
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    • 2012
  • In this paper, vibration-based methods to monitor damage in foundation-structure interface of harbor caisson structure are presented. The following approaches are implemented to achieve the objective. Firstly, vibration-based damage monitoring methods utilizing a variety of vibration features are selected for harbor caisson structure. Autoregressive (AR) model for time-series analysis and power spectral density (PSD) for frequency-domain analysis are selected to detect the change in the caisson structure. Also, the changes in modal parameters such as natural frequency and mode shape are examined for damage monitoring in the structure. Secondly, the feasibility of damage monitoring methods is experimentally examined on an un-submerged lab-scaled mono-caisson. Finally, numerical analysis of un-submerged mono-caisson, submerged mono-caisson and un-submerged interlocked multiple-caissons are carried out to examine the effect of boundary-dependent parameters on the damage monitoring of harbor caisson structures.