A New Method For Frequency Domain Analysis Of Offshore Structures: Comparison With Time Domain Analysis

1986 ◽  
Author(s):  
G.E. Deleuil ◽  
L.D. Des Déserts ◽  
C.G. Doris ◽  
A. Shive
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Offshore Structures ◽  
Frequency Domain Analysis ◽  
New Method

scholarly journals Analysis of Three-Phase Wye-Delta Connected LLC

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3606
Author(s):  
Jing-Yuan Lin ◽  
Chuan-Ting Chen ◽  
Kuan-Hung Chen ◽  
Yi-Feng Lin
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Operation Time ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Complete Analysis ◽  
Plane Analysis ◽  
Analysis Methods ◽  
Three Phase

Three-phase wye–delta LLC topology is suitable for voltage step down and high output current, and has been used in the industry for some time, e.g., for server power and EV charger. However, no comprehensive circuit analysis has been performed for three-phase wye–delta LLC. This paper provides complete analysis methods for three-phase wye–delta LLC. The analysis methods include circuit operation, time domain analysis, frequency domain analysis, and state–plane analysis. Circuit operation helps determine the circuit composition and operation sequence. Time domain analysis helps understand the detail operation, equivalent circuit model, and circuit equation. Frequency domain analysis helps obtain the curve of the transfer function and assists in circuit design. State–plane analysis is used for optimal trajectory control (OTC). These analyses not only can calculate the voltage/current stress, but can also help design three-phase wye-delta connected LLC and provide the OTC control reference. In addition, this paper uses PSIM simulation to verify the correctness of analysis. At the end, a 5-kW three-phase wye–delta LLC prototype is realized. The specification of the prototype is a DC input voltage of 380 V and output voltage/current of 48 V/105 A. The peak efficiency is 96.57%.

A Frequency Domain Analysis of Learning Control

1994 ◽  
Vol 116 (4) ◽  
pp. 781-786 ◽  
Author(s):  
C. J. Goh
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Linear Time ◽  
Planning Horizon ◽  
Time Domain Analysis ◽  
Learning Control ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Convergence Criterion ◽  
The Time Domain

The convergence of learning control is traditionally analyzed in the time domain. This is because a finite planning horizon is often assumed and the analysis in time domain can be extended to time-varying and nonlinear systems. For linear time-invariant (LTI) systems with infinite planning horizon, however, we show that simple frequency domain techniques can be used to quickly derive several interesting results not amenable to time-domain analysis, such as predicting the rate of convergence or the design of optimum learning control law. We explain a paradox arising from applying the finite time convergence criterion to the infinite time learning control problem, and propose the use of current error feedback for controlling possibly unstable systems.

Analysis of Electrocardio Signal Based on Approximate Entropy

2012 ◽  
Vol 429 ◽  
pp. 195-199
Author(s):  
Xiao Lei Zhao ◽  
Ming Rong Ren ◽  
Ya Ting Zhang ◽  
Pu Wang
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Approximate Entropy ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Spectrum Estimation ◽  
Transform Method ◽  
Time Frequency ◽  
Relationship Of

The research and detection of heart disease depends on the analysis of the characteristic of electrocardio signal. Current analysis methods mainly include: (1) time domain analysis is a common used approach. With experience learned by observation and calculation, researchers examine errors and interferences to calculate means and variances directly within time domain. Analysis quality of this method demands higher request for researchers’ experience and skill although it’s a direct and significant result. (2) Frequency domain analysis, such as spectrum estimation, is largely applied to electrocardio signal researches and clinical applications. The analysis reflects abundant electrocardio activities, but failed to show details of the characteristics due to lack of time information. (3) time-frequency domain analysis describes energy density under different time and frequency of electrocardio signal at one time. It clarifies the relationship of signal frequency’s changing along with time such as wavelet transform method. (4) Nonlinear analysis is generally applied to biomedicine signal research in recent years. Correlation dimension, kolmogorov entropy, lyapunov component are major research methods to estimate some nonlinear dynamic parameters to represent the characteristic of electrocardio signal.

Comparison of Time and Frequency Domain Analysis With Full Scale Data for the Horn Mountain Spar During Hurricane Isidore

2006 ◽  
Author(s):  
Arcandra Tahar ◽  
John Halkyard ◽  
Mehernosh Irani
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Full Scale ◽  
Frequency Domain Method ◽  
Drag Forces ◽  
The Time Domain ◽  
Scale Data

The Horn Mountain Spar is located in 1,654 m of water about 135 km from Venice, Louisiana in the Gulf of Mexico. The facility was instrumented extensively to measure key spar and riser response parameters (Edwards et. al. 2003). Halkyard et. al. (2004) and Tahar et. al. (2005) have compared measured spar responses such as motion and mooring line tensions with numerical predictions. This paper extends the work done on comparison of the full scale data during hurricane Isidore. All previous numerical simulations were based on a time domain analysis procedure. One concern related to this method is that it is computationally intensive and time consuming. In the initial stages of a project, a frequency domain solution may be an effective tool compared with a fully coupled time domain analysis. The present paper compares results of time domain and frequency domain simulations with field measurements. Particular attention has been placed on the importance of the phase relationship between motion and excitation force. In the time domain analysis, nonlinear drag forces are applied at the instantaneous position. Whereas in the frequency domain analysis, nonlinear drag forces are stochastically linearized and solutions are obtained by an iterative procedure. The time domain analysis has better agreement with the field data compared to the frequency domain. Overall, however, the frequency domain method is still promising for a quick and approximate estimation of relevant statistics. With advantages in terms of CPU time, the frequency domain method can be recommended as a tool in pre-front end engineering design or in a phase where an iterative nature of design of an offshore structure takes place.

Research on Electrohydraulic Position Servo System Control of Honing Machine

2013 ◽  
Vol 457-458 ◽  
pp. 1310-1313
Author(s):  
Zhi Hong Ma ◽  
Ya Zhou Huang ◽  
Shan Le Cai ◽  
Fu Fang Luo
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Servo System ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
System Control ◽  
Initial Value ◽  
Basic Principles ◽  
Matlab Software

This paper simply describes basic principles of the honing machine. And using MATLAB software this paper carries out frequency-domain analysis and time-domain analysis of this system. According to actual processing situation putting forward to control overshoot. Because this system cannot meet the needs, utilizing PID to adjust this system. At the same time putting parameters obtained from PID adjustment as initial value, this paper carries out optimization, and gets a better result.

scholarly journals Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Maria Romano ◽  
Luigi Iuppariello ◽  
Alfonso Maria Ponsiglione ◽  
Giovanni Improta ◽  
Paolo Bifulco ◽  
...  
Keyword(s):  
Heart Rate ◽  
Frequency Domain ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Clinical Results ◽  
Frequency Domain Analysis ◽  
Critical Survey ◽  
Foetal Heart Rate ◽  
Foetal Heart

Monitoring of foetal heart rate and its variability (FHRV) covers an important role in assessing health of foetus. Many analysis methods have been used to get quantitative measures of FHRV. FHRV has been studied in time and in frequency domain and interesting clinical results have been obtained. Nevertheless, a standardized definition of FHRV and a precise methodology to be used for its evaluation are lacking. We carried out a literature overview about both frequency domain analysis (FDA) and time domain analysis (TDA). Then, by using simulated FHR signals, we defined the methodology for FDA. Further, employing more than 400 real FHR signals, we analysed some of the most common indexes, Short Term Variability for TDA and power content of the spectrum bands and sympathovagal balance for FDA, and evaluated their ranges of values, which in many cases are a novelty. Finally, we verified the relationship between these indexes and two important parameters: week of gestation, indicator of foetal growth, and foetal state, classified as active or at rest. Our results indicate that, according to literature, it is necessary to standardize the procedure for FHRV evaluation and to consider week of gestation and foetal state before FHR analysis.

scholarly journals Determining heart rate variation: a comparison between direct results from V6 of the ECG and time domain, frequency domain and non-liniar analysis

2006 ◽  
Vol 25 (2) ◽  
pp. 67-81
Author(s):  
C. Grant ◽  
P. J. Becker ◽  
M. Viljoen
Keyword(s):  
Heart Rate ◽  
Frequency Domain ◽  
Time Domain ◽  
Fractal Analysis ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Mean Value ◽  
Rate Variation ◽  
Direct Results

Oscillation around a mean value is found in the intervals between consecutive heartbeats (R-R intervals). This oscillation is known as heart rate variability (HRV). Various methods can be used to estimate HRV, but the extent to which agreement exists between the results obtained by the different methods is not known. In this study HRV, as determined directly from the ECG, is compared to results obtained by time domain analysis, frequency domain analysis, Poincaré graphs and fractal analysis. Results showed that, in individuals with low HRV values, the results obtained by time domain analysis, frequency domain analysis, Poincaré graphs and alpha 1 of fractal analysis are comparable to those calculated directly from the ECG. However, time domain analysis, frequency domain analysis, Poincaré graphs and fractal analysis are less sensitive than direct ECG measurements in individuals with higher HRV.

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