• 제목/요약/키워드: Mode Decomposition Technique

검색결과 96건 처리시간 0.041초

Identification of flutter derivatives of bridge decks using stochastic search technique

  • Chen, Ai-Rong;Xu, Fu-You;Ma, Ru-Jin
    • Wind and Structures
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    • 제9권6호
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    • pp.441-455
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    • 2006
  • A more applicable optimization model for extracting flutter derivatives of bridge decks is presented, which is suitable for time-varying weights for fitting errors and different lengths of vertical bending and torsional free vibration data. A stochastic search technique for searching the optimal solution of optimization problem is developed, which is more convenient in understanding and programming than the alternate iteration technique, and testified to be a valid and efficient method using two numerical examples. On the basis of the section model test of Sutong Bridge deck, the flutter derivatives are extracted by the stochastic search technique, and compared with the identification results using the modified least-square method. The Empirical Mode Decomposition method is employed to eliminate noise, trends and zero excursion of the collected free vibration data of vertical bending and torsional motion, by which the identification precision of flutter derivatives is improved.

강체모드분리와 급수전개를 통한 준해석적 민감도 계산 방법의 개선에 관한 연구(I) - 정적 문제 - (A Refined Semi-Analytic Sensitivity Study Based on the Mode Decomposition and Neumann Series Expansion (I) - Static Problem -)

  • 조맹효;김현기
    • 대한기계학회논문집A
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    • 제27권4호
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    • pp.585-592
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    • 2003
  • Among various sensitivity evaluation techniques, semi-analytical method(SAM) is quite popular since this method is more advantageous than analytical method(AM) and global finite difference method(FDM). However, SAM reveals severe inaccuracy problem when relatively large rigid body motions are identified fur individual elements. Such errors result from the numerical differentiation of the pseudo load vector calculated by the finite difference scheme. In the present study, an iterative method combined with mode decomposition technique is proposed to compute reliable semi-analytical design sensitivities. The improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes and the error of SAM caused by numerical difference scheme is alleviated by using a Von Neumann series approximation considering the higher order terms for the sensitivity derivatives.

Construction stage effect on the dynamic characteristics of RC frame using operational modal analysis

  • Arslan, Mehmet Emin;Durmus, Ahmet
    • Computers and Concrete
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    • 제12권1호
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    • pp.79-90
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    • 2013
  • In this study, dynamic characteristics such as natural frequencies, mode shapes and damping ratios of RC frame is determined for different construction stages using Operational Modal Analyses method under ambient vibration. Full scaled, one bay and one story RC frames are selected as an application for different construction stages such as plane, brick in-filled and brick in-filled with plaster. The RC frame is vibrated by natural excitations with small impact effects and the response signals are measured using sensitive accelerometers during ambient vibration tests. Measurement time-frequency span and effective mode number are determined by considering similar studies in literature. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, output-only system identification technique is employed namely; Enhanced Frequency Domain Decomposition technique in the frequency domain. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of RC frames.

Runoff Prediction from Machine Learning Models Coupled with Empirical Mode Decomposition: A case Study of the Grand River Basin in Canada

  • Parisouj, Peiman;Jun, Changhyun;Nezhad, Somayeh Moghimi;Narimani, Roya
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.136-136
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    • 2022
  • This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

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첩릿변환을 이용한 비틀림 유도파 모드분리 (Mode Separation in Torsional Guided Waves Using Chirplet Transform)

  • 김영완;박경조
    • 한국소음진동공학회논문집
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    • 제24권4호
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    • pp.324-331
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    • 2014
  • The sensor configuration of the magnetostrictive guided wave system can be described as a single continuous transducing element which makes it difficult to separate the individual modes from the reflected signal. In this work we develop the mode decomposition technique employing chirplet transform based on the maximum likelihood estimation, which is able to separate the individual modes from dispersive and multimodal waveform measured with the magnetostrictive sensor, and estimate the time-frequency centers and individual energies of the reflection, which would be used to locate and characterize defects. Simulation results on a carbon steel pipe are presented, which show the accurate mode separation and more discernible time-frequency representation could become enabled using the proposed technique.

Wear Detection in Gear System Using Hilbert-Huang Transform

  • Li, Hui;Zhang, Yuping;Zheng, Haiqi
    • Journal of Mechanical Science and Technology
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    • 제20권11호
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    • pp.1781-1789
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    • 2006
  • Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.

화염 전달함수 및 DMD 기법을 이용한 모형 가스터빈의 연소불안정성 평가 (Evaluation of Combustion Instability in a Model Gas Turbine Adopting Flame Transfer Function and Dynamic Mode Decomposition)

  • 손진우;손채훈;윤지수;윤영빈
    • 한국연소학회지
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    • 제22권2호
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    • pp.1-8
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    • 2017
  • To evaluate the combustion instability of a gas turbine combustor, the DMD technique was applied. The mode frequency results for each fuel composition were compared with FFT(Fast Fourier Transform) results. The damping coefficient, which is a quantitative parameter for combustion instability, was evaluated for 5 experimental cases. The flame transfer function (FTF) was calculated in the most unstable test case. In deriving the FTF, gain and phase were calculated using DMD technique. As a result of the analysis of the OH radical perturbation of the DMD, the heat release fluctuation was the highest at 100 Hz, at which the highest value of gain is observed. The frequency of FFT and FTF were different. In order to clarify the reason for this, FTF for various resonance frequencies was performed and it shows that the pattern of gain was similar to FFT.

HHT method for system identification and damage detection: an experimental study

  • Zhou, Lily L.;Yan, Gang
    • Smart Structures and Systems
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    • 제2권2호
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    • pp.141-154
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    • 2006
  • Recently, the Hilbert-Huang transform (HHT) has gained considerable attention as a novel technique of signal processing, which shows promise for the system identification and damage detection of structures. This study investigates the effectiveness and accuracy of the HHT method for the system identification and damage detection of structures through a series of experiments. A multi-degree-of-freedom (MDOF) structural model has been constructed with modular members, and the columns of the model can be replaced or removed to simulate damages at different locations with different severities. The measured response data of the structure due to an impulse loading is first decomposed into modal responses using the empirical mode decomposition (EMD) approach with a band-pass filter technique. Then, the Hilbert transform is subsequently applied to each modal response to obtain the instantaneous amplitude and phase angle time histories. A linear least-square fit procedure is used to identify the natural frequencies and damping ratios from the instantaneous amplitude and phase angle for each modal response. When the responses at all degrees of freedom are measured, the mode shape and the physical mass, damping and stiffness matrices of the structure can be determined. Based on a comparison of the stiffness of each story unit prior to and after the damage, the damage locations and severities can be identified. Experimental results demonstrate that the HHT method yields quite accurate results for engineering applications, providing a promising tool for structural health monitoring.

Condition Monitoring of Low Speed Slewing Bearings Based on Ensemble Empirical Mode Decomposition Method

  • Caesarendra, W.;Park, J.H.;Choi, B.H.;Kosasih, P.B.
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2012년도 추계학술대회 논문집
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    • pp.388-393
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    • 2012
  • Vibration condition monitoring at low rotational speeds is still a challenge. Acoustic emission (AE) is the most used technique when dealing with low speed bearings. At low rotational speeds, the energy induced from surface contact between raceway and rolling elements is very weak and sometimes buried by interference frequencies. This kind of issue is difficult to solve using vibration monitoring. Therefore some researchers utilize artificial damage on inner race or outer race to simplify the case. This paper presents vibration signal analysis of low speed slewing bearings running at a low rotational speed of 15 rpm. The natural damage data from industrial practice is used. The fault frequencies of bearings are difficult to identify using a power spectrum. Therefore the relatively improved method of empirical mode decomposition (EMD), ensemble EMD (EEMD) is employed. The result is can detect the fault frequencies when the FFT fail to do it.

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DMD 기법을 적용한 모형 가스터빈의 연소불안정성 평가에 관한 실험적 연구 (An Experimental Study on the Combustion Instability Evaluation by Using DMD)

  • 손진우;손채훈;윤지수;윤영빈
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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    • pp.59-60
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    • 2017
  • 가스터빈 연소기의 연소불안정성을 평가하기 위해 동적모드분해(dynamic mode decomposition, DMD) 기법을 적용하였다. DMD 기법으로 도출된 감쇠계수(damping coefficient)와 FFT 결과를 비교 분석 하였다. 또한 화염전달함수 (flame transfer function, FTF)를 도출하는 실험적 방법에 DMD 기법을 적용하여 분석을 시도하였다. 기존에 제시된 열방출 섭동을 추출하는 방법에서 개선된, OH PLIF 이미지를 이용하여 열방출 섭동을 추출하는 방법을 사용하였다. 분석 결과, 열방출 섭동의 추출 위치에 따라 화염전달함수의 이득(gain)이 변하는 것을 확인하였다.

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