Dynamic Analysis for Transportation of Barge-Jacket Assembly in Time-Frequency Domain

1988 ◽  
Vol 110 (2) ◽  
pp. 109-116
Author(s):  
F. Sun ◽  
C. Gao
Keyword(s):  
Computer Program ◽  
Frequency Domain ◽  
Time Domain ◽  
Fourier Transformation ◽  
Time History ◽  
Statistical Characteristics ◽  
Frequency Domain Method ◽  
Time Frequency ◽  
Random Seas ◽  
History Of

A combined time-frequency domain method is proposed to analyze the stresses of barge-jacket assembly during transportation. Starting with the motion of analysis in frequency domain, the time history of waves and motions in random seas are simulated, then the stresses are determined in time domain. The stress autocorrelation functions are calculated and the stress spectra and statistical characteristics are obtained through Fourier transformation. A computer program has been developed. The effects of barge flexibility and the forces caused by the immersion of jacket have been discussed.

Frequency Domain Fatigue Analysis for a Unbonded Flexible Riser: Damage Induced by Dynamic Bending

2020 ◽  
Author(s):  
Jiabei Yuan ◽  
Yucheng Hou ◽  
Zhimin Tan
Keyword(s):  
Tensile Stress ◽  
Frequency Domain ◽  
Fatigue Damage ◽  
Time Domain ◽  
Time History ◽  
Domain Analysis ◽  
Fatigue Analysis ◽  
Stress Spectrum ◽  
History Of ◽  
Frequency Domain Approach

Abstract The service life of flexible risers is a vital design parameter in offshore field development. The standard approach to calculate fatigue life is the nonlinear time-domain analysis. The approach uses time history of riser responses in local structure assessment to get the fatigue damage of tensile layers. Another approach is the linearized frequency-domain analysis. Instead of using time history of stress and rainflow counting technique, the approach uses stress spectrum and empirical mathematical terms to estimate the fatigue damage. The frequency domain approach is significantly faster. However, due to the whole system being linearized, the latter usually produces different results and is considered to be less accurate than the time domain approach. To address this issue, Baker Hughes previously developed an approach which uses the frequency domain technique as base solution and calibration factors from limited time domain cases. The approach is limited to tensile wires at the end fitting entrance where tension and tensile stress is directly linked. In this paper, a similar approach is proposed to be applied for tensile fatigue at all regions, whose tensile stress are induced by a combination of tension, pressure, bending and friction between layers. Since tensile stress is not directly related to any single riser response, the stress spectrum is predicted by using a transfer function. With the predicted stress spectrum, the fatigue damage of each case is calculated with Dirlik’s method and SN curves. The paper summarizes the development of the hybrid frequency domain approach. The fatigue damage of risers from several projects are acquired with both time domain and frequency domain approaches. The approach is significantly faster than traditional time domain approach and produces conservative results. Furthermore, discussions are made on options to improve the approach and reduce the conservatism in the frequency domain fatigue analysis.

Detection of Nonlinear Frequency Modulated Signal Based on Fractional Fourier Transform

2014 ◽  
Vol 989-994 ◽  
pp. 4042-4045
Author(s):  
Yan Jun Wu ◽  
Min Tao ◽  
Min Qi Zhou
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Fourier Transformation ◽  
Fractional Fourier Transform ◽  
Superior Performance ◽  
Nonlinear Frequency ◽  
Time Frequency ◽  
Energy Accumulation ◽  
Signal Detector ◽  
Time Frequency Distribution

Based on fractional Fourier transformation (FRFT), the feature of the signals which vary smoothly from time domain to frequency domain is given. The FRFT method is applied to the estimation and detection of nonlinear frequency modulated signals to which piecewise linearly approach. Wigner-Ville time frequency distribution of the signals is used after approaching and the masking results of the original signal accumulate energy as detecting statistic. A signal detector based on energy accumulation from time frequency domain in the angle of analysis of both time and frequency is proposed. Finally, a comparison with traditional non-coherent energy accumulation methods is made, which shows the proposed method has superior performance.

PROGRAM OF PREDICTION AND MANAGEMENT OF COINTEGED DYNAMIC ECONOMIC PROCESSES BASED ON THE CYBERNETIC APPROACH

2019 ◽  
Author(s):  
Olena Bundak ◽  
Nataliia Zubovetska
Keyword(s):  
Computer Program ◽  
Pair Correlation ◽  
Time History ◽  
Critical Area ◽  
Concrete Object ◽  
Graphic Arts ◽  
Ex Post ◽  
History Of ◽  
Successive Change ◽  
Rms Errors

A method and computer program ConRow, which prognostication of development of the dynamically CPLD economic transients is executed by, is described in the article. Such prognostication of economic processes is very important in the cases when their development can result in undesirable consequences, that to go out in the so-called critical area. Extrapolation in a critical area with the use of information about the conduct of the system at an area, near to it, allows to estimate to the lead through of experiment in the critical area of his consequence. For the imitation of conduct of object the function of review is set on entrance influence. For a concrete object this function can express, for example, dependence of change of level sale from time-history of charges on advertising and set as a numeral row. Statistics as a result of analysis of row are represented in a table, where the level of meaningfulness is set statistician, and also parameters of the handed over criteria. The graphic reflection of information is intended for visualization of analysis. Here represented on the points of graphic arts, the crooked smoothing which are calculated as полиномиальные regressions is added. The best approaching is controlled by sight on the proper graph, and also by minimization of their rms errors. Models of prognostication by sight and as formulas represented on graphic arts, the middle is here determined tailings and their chance is checked up on statistics of signs. After the got models determined also and prognosis values of influences and reviews. Establishing an order models of Сr(p) of co integrate regression is carried out separate custom controls. The coefficient of clay correlation of ruФ shows by itself pair correlation between lines with a successive change in relation to each other on a size to лагу of l = 1, 2, 3 . The program was tested on the example of ex-post prognosis at establishing an integration connection and possibility of prognostication of growth of nominal average monthly settlings on the basis of these statistical indexes of consumer inflation in Ukraine.

scholarly journals A research on fiber-optic vibration pattern recognition based on time-frequency characteristics

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881346 ◽  
Author(s):  
Tabi Fouda Bernard Marie ◽  
Dezhi Han ◽  
Bowen An ◽  
Jingyun Li
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Time Domain ◽  
Fiber Optic ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Vibration Pattern ◽  
The Time Domain

To detect and recognize any type of events over the perimeter security system, this article proposes a fiber-optic vibration pattern recognition method based on the combination of time-domain features and time-frequency domain features. The performance parameters (event recognition, event location, and event classification) are very important and describe the validity of this article. The pattern recognition method is precisely based on the empirical mode decomposition of time-frequency entropy and center-of-gravity frequency. It implements the function of identifying and classifying the event (intrusions or non-intrusion) over the perimeter to secure. To achieve this method, the first-level prejudgment is performed according to the time-domain features of the vibration signal, and the second-level prediction is carried out through time-frequency analysis. The time-frequency distribution of the signal is obtained by empirical mode decomposition and Hilbert transform and then the time-frequency entropy and center-of-gravity frequency are used to form the time-frequency domain features, that is, combined with the time-domain features to form feature vectors. Multiple types of probabilistic neural networks are identified to determine whether there are intrusions and the intrusion types. The experimental results demonstrate that the proposed method is effective and reliable in identifying and classifying the type of event.

The Time Domain Simulation of Non-Stationary Road Roughness

2013 ◽  
Vol 423-426 ◽  
pp. 1238-1242
Author(s):  
Hao Wang ◽  
Xiao Mei Shi
Keyword(s):  
Power Spectrum ◽  
Time Domain ◽  
Ride Comfort ◽  
Time History ◽  
Random Excitation ◽  
Power Spectrum Density ◽  
The Road ◽  
Road Roughness ◽  
Spectrum Density ◽  
History Of

The input of road roughness, which affects the ride comfort and the handling stability of vehicle, is the main excitation for the running vehicle. The time history of the road roughness was researched with the random phases, based on the stationary power spectrum density of the road roughness determined by the standards. Through the inverse Fourier transform, the random phases can be used to get the road roughness in time domain, together with the amplitude. Then, the time domain simulation of the non-stationary random excitation when the vehicle ran at the changing speed, would also be studied based on the random phases. It is proved that the random road excitation for the vehicle with the changing speed is stationary modulated evolution random excitation, and its power spectrum density is the stationary modulated evolutionary power spectrum density. And the numerical results for the time history of the non-stationary random inputs were also provided. The time history of the non-stationary random road can be used to evaluate the ride comfort of the vehicle which is running at the changing speed.

Spectrum analysis of moving average operator and construction of time-frequency hybrid sequence operator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Changhai Lin ◽  
Sifeng Liu ◽  
Zhigeng Fang ◽  
Yingjie Yang
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Moving Average ◽  
Spectral Characteristics ◽  
Complex Data ◽  
Time Data ◽  
Average Operator ◽  
Content Type ◽  
Time Frequency ◽  
Hybrid Sequence

PurposeThe purpose of this paper is to analyze the spectral characteristics of moving average operator and to propose a novel time-frequency hybrid sequence operator.Design/methodology/approachFirstly, the complex data is converted into frequency domain data by Fourier transform. An appropriate frequency domain operator is constructed to eliminate the impact of disturbance. Then, the inverse Fourier transform transforms the frequency domain data in which the disturbance is removed, into time domain data. Finally, an appropriate moving average operator of N items is selected based on spectral characteristics to eliminate the influence of periodic factors and noise.FindingsThrough the spectrum analysis of the real-time data sensed and recorded by microwave sensors, the spectral characteristics and the ranges of information, noise and shock disturbance factors in the data can be clarified.Practical implicationsThe real-time data analysis results for a drug component monitoring show that the hybrid sequence operator has a good effect on suppressing disturbances, periodic factors and noise implied in the data.Originality/valueFirstly, the spectral analysis of moving average operator and the novel time-frequency hybrid sequence operator were presented in this paper. For complex data, the ideal effect is difficult to achieve by applying the frequency domain operator or time domain operator alone. The more satisfactory results can be obtained by time-frequency hybrid sequence operator.

Dynamic Tilt Correction Using Direct Rotational Motion Measurements

2020 ◽  
Vol 91 (5) ◽  
pp. 2872-2880 ◽  
Author(s):  
Felix Bernauer ◽  
Joachim Wassermann ◽  
Heiner Igel
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Ground Deformation ◽  
Time Domain Method ◽  
Caldera Collapse ◽  
Frequency Domain Method ◽  
Test Cases ◽  
Ground Acceleration ◽  
Data Set ◽  
Domain Method

Abstract Inertial sensors like seismometers or accelerometers are sensitive to tilt motions. In general, from pure acceleration measurements, it is not possible to separate the tilt acceleration from the translational ground acceleration. This can lead to severe misinterpretation of seismograms. Here, we present three different methods that can help solving this problem by correcting translational records for dynamic tilt induced by ground deformation with direct measurements of rotational motions: (1) a simple time-domain method, (2) a frequency-domain method proposed by Crawford and Webb (2000) using a coherence-weighted transfer function between rotation and acceleration, and (3) an adapted frequency-domain method that corrects only those parts of the spectrum with coherence between translational acceleration and rotation angle higher than 0.5. These three methods are discussed in three different experimental settings: (1) a reproducible and precisely known laboratory test using a high-precision tilt table, (2) a synthetic test with a simulated volcanic very-long-period event, and (3) a real data set recorded during the 2018 Mt. Kīlauea caldera collapse. All the three test cases show severe influence of tilt motion on the acceleration measurements. The time-domain method and the adapted frequency-domain method show very similar performance in all three test cases. Those two methods are able to remove the tilt component reliably from the acceleration record.

Estimating interannual variability arising from weather events

2001 ◽  
Vol 38 (A) ◽  
pp. 274-288 ◽  
Author(s):  
Xiaogu Zheng ◽  
James Renwick
Keyword(s):  
Frequency Domain ◽  
Interannual Variability ◽  
Time Domain ◽  
Synthetic Data ◽  
Estimation Procedure ◽  
Frequency Domain Method ◽  
Domain Method ◽  
Weather Events ◽  
Long Time ◽  
The Time Domain

The advantages and limitations of frequency domain and time domain methods for estimating the interannual variability arising from day-to-day weather events are summarized. A modification of the time domain method is developed and its application in examining a precondition for the frequency domain method is demonstrated. A combined estimation procedure is proposed: it takes advantage of the strengths of both methods. The estimation procedures are tested with sets of synthetic data and are applied to long time series of three meteorological parameters. The impacts of the different methods on tests of potential long-range predictability for seasonal means are also discussed.

System Identification of Jack-Up Platform by Spectral Analysis

2010 ◽  
Author(s):  
X. M. Wang ◽  
C. G. Koh ◽  
T. N. Thanh ◽  
J. Zhang
Keyword(s):  
Spectral Analysis ◽  
System Identification ◽  
Time Domain ◽  
Time History ◽  
Offshore Structures ◽  
Wave Load ◽  
History Of ◽  
Structural Responses ◽  
Jack Up ◽  
Numerical Strategy

For the purpose of structural health monitoring (SHM), it is beneficial to develop a robust and accurate numerical strategy so as to identify key parameters of offshore structures. In this regard, it is difficult to use time-domain methods as the time history of wave load is not available unless output-only methods can be developed. Alternatively, spectral analysis widely used in offshore engineering to predict structural responses due to random wave conditions can be used. Thus the power spectral density (PSD) of structural response may be more appropriate than time history of structural responses in defining the objective (fitness) function for system identification of offshore structures. By minimizing PSD differences between measurements and simulations, the proposed numerical strategy is completely carried out in frequency domain, which can avoid inherent problems rising from random phase angles and unknown initial conditions in time domain. A jack-up platform is studied in the numerical study. A search space reduction method (SSRM) incorporating the use of genetic algorithms (GA) as well as a substructure approach are adopted to improve the accuracy and efficiency of identification. As a result, the stiffness parameters of jack-up legs can be well identified even under fairly noisy conditions.

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