JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

2018 ◽  
Vol 12 (7-8) ◽  
pp. 76-83
Author(s):  
E. V. KARSHAKOV ◽  
J. MOILANEN
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Interval ◽  
Single Spectrum ◽  
Simultaneous Inversion ◽  
Homogeneous Half Space ◽  
Time Domain Data ◽  
The Time Domain

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

IDENTIFICATION OF INTERHARMONICS BASED ON WAVELET PACKET TRANSFORM

2021 ◽  
Vol 3 (1) ◽  
pp. 031-036
Author(s):  
S. A. GOROVOY ◽  
◽  
V. I. SKOROKHODOV ◽  
D. I. PLOTNIKOV ◽  
◽  
...  
Keyword(s):  
Fourier Transform ◽  
Simulation Model ◽  
Frequency Domain ◽  
Time Domain ◽  
Wavelet Packet ◽  
High Accuracy ◽  
Wavelet Packet Transform ◽  
Mathematical Apparatus ◽  
Nonlinear Load ◽  
The Time Domain

This paper deals with the analysis of interharmonics, which are due to the presence of a nonlinear load. The tool for the analysis was a mathematical apparatus - wavelet packet transform. Which has a number of advantages over the traditional Fourier transform. A simulation model was developed in Simulink to simulate a non-stationary non-sinusoidal mode. The use of the wavelet packet transform will allow to determine the mode parameters with high accuracy from the obtained wavelet coefficients. It also makes it possible to obtain information, both in the frequency domain of the signal and in the time domain.

Effects of Noise, Time-Domain Damping, Zero-Filling and the FFT Algorithm on the “Exact” Interpolation of Fast Fourier Transform Spectra

1988 ◽  
Vol 42 (5) ◽  
pp. 715-721 ◽  
Author(s):  
Francis R. Verdun ◽  
Carlo Giancaspro ◽  
Alan G. Marshall
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Word Length ◽  
Peak Position ◽  
Double Precision ◽  
Time Domain Data ◽  
Roundoff Errors ◽  
Data Points ◽  
Lorentzian Spectrum

A frequency-domain Lorentzian spectrum can be derived from the Fourier transform of a time-domain exponentially damped sinusoid of infinite duration. Remarkably, it has been shown that even when such a noiseless time-domain signal is truncated to zero amplitude after a finite observation period, one can determine the correct frequency of its corresponding magnitude-mode spectral peak maximum by fitting as few as three spectral data points to a magnitude-mode Lorentzian spectrum. In this paper, we show how the accuracy of such a procedure depends upon the ratio of time-domain acquisition period to exponential damping time constant, number of time-domain data points, computer word length, and number of time-domain zero-fillings. In particular, we show that extended zero-filling (e.g., a “zoom” transform) actually reduces the accuracy with which the spectral peak position can be determined. We also examine the effects of frequency-domain random noise and roundoff errors in the fast Fourier transformation (FFT) of time-domain data of limited discrete data word length (e.g., 20 bit/word at single and double precision). Our main conclusions are: (1) even in the presence of noise, a three-point fit of a magnitude-mode spectrum to a magnitude-mode Lorentzian line shape can offer an accurate estimate of peak position in Fourier transform spectroscopy; (2) the results can be more accurate (by a factor of up to 10) when the FFT processor operates with floating-point (preferably double-precision) rather than fixed-point arithmetic; and (3) FFT roundoff errors can be made negligible by use of sufficiently large (> 16 K) data sets.

scholarly journals Radiofrequency Microwave Double Resonance Experiments in Fourier Transform Technique

1988 ◽  
Vol 43 (3) ◽  
pp. 280-282 ◽  
Author(s):  
N. Heineking ◽  
W. Stahl ◽  
H. Dreizler
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Double Resonance ◽  
Fourier Transform Spectroscopy ◽  
Microwave Spectroscopy ◽  
Valuable Method ◽  
The Time Domain

Abstract Radiofrequency microwave double resonance has proved as a valuable method in microwave spectroscopy in the frequency domain. We present comparable experiments in the time domain Fourier transform spectroscopy.

scholarly journals The Comparison of the Effect of Haimming Window and Blackman Window in the Time-Scaling and Pitch-Shifting Algorithms

2011 ◽  
Vol 1 ◽  
pp. 221-225
Author(s):  
Zhi Wei Lin ◽  
Li Da ◽  
Hao Wang ◽  
Wei Han ◽  
Fan Lin
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Domain Method ◽  
Domain Type ◽  
Domain Method ◽  
Time Scaling ◽  
Window Functions ◽  
Inherent Frequency ◽  
The Time Domain

The real-time pitch shifting process is widely used in various types of music production. The pitch shifting technology can be divided into two major types, the time domain type and the frequency domain type. Compared with the time domain method, the frequency domain method has the advantage of large shifting scale, low total cost of computing and the more flexibility of the algorithm. However, the use of Fourier Transform in frequency domain processing leads to the inevitable inherent frequency leakage effects which decrease the accuracy of the pitch shifting effect. In order to restrain the side effect of Fourier Transform, window functions are used to fall down the spectrum-aliasing. In practical processing, Haimming Window and Blackman Window are frequently used. In this paper, we compare both the effect of the two window functions in the restraint of frequency leakage and the performance and accuracy in subjective based on the traditional phase vocoder[1]. Experiment shows that Haimming Window is generally better than Blackman Window in pitch shifting process.

scholarly journals Time-resolving the COVID-19 outbreak using frequency domain analysis

2020 ◽  
Author(s):  
Keno L. Krewer ◽  
Mischa Bonn
Keyword(s):  
Steady State ◽  
Severe Acute Respiratory Syndrome ◽  
Spectral Density ◽  
Frequency Domain ◽  
Time Domain ◽  
Case Fatality ◽  
Frequency Domain Analysis ◽  
Time Domain Data ◽  
Current Outbreak ◽  
The Time Domain

AbstractDifficulties assessing and predicting the current outbreak of the severe acute respiratory syndrome coronavirus 2 can be traced, in part, to the limitations of a static description of a dynamic system. Fourier transforming the time-domain data of infections and fatalities into the frequency domain makes the dynamics easily accessible. Defining a quantity like the “case fatality” as a spectral density allows a more sensible comparison between different countries and demographics during an ongoing outbreak. Such a case fatality informs not only how many of the confirmed cases end up as fatalities, but also when. For COVID-19, knowing this time and using the entire case fatality spectrum allows determining that an outbreak had entered a steady-state (most likely its end) about 14 days before this is obvious from time-domain data. The lag between confirmations and deaths also helps to estimate the effectiveness of contact management: The larger the lag, the less time the average confirmed person had to infect people before quarantine.

scholarly journals Study of Blockage Diagnosis for Hydrocyclone Using Vibration-Based Technique Based on Wavelet Denoising and Discrete-Time Fourier Transform Method

Processes ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 440 ◽  
Author(s):  
Guanghui Wang ◽  
Qun Liu ◽  
Chuanzhen Wang ◽  
Lulu Dong ◽  
Dan Dai ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Standard Deviation ◽  
Frequency Domain ◽  
Discrete Time ◽  
Time Domain ◽  
Wavelet Denoising ◽  
Transform Method ◽  
Fourier Transform Method ◽  
The Time Domain ◽  
Separation Devices

Hydrocyclones are extensively known as important separation devices which are used in many industrial fields. However, the general method to estimate device performance is time-consuming and has a high cost. The aim of this paper was to investigate the blockage diagnosis for a lab-scale hydrocyclone using a vibration-based technique based on wavelet denoising and the discrete-time Fourier transform method. The results indicate that the farther away the installation location from feed inlet the more regular the frequency is, which reveals that the installation plane near to the spigot generated the regular frequency distribution. Furthermore, the acceleration amplitude under blockage degrees 0%, 50% and 100% fluctuates as a sine shape with increasing time, meanwhile the vibration frequency of the hydrocyclone rises with increasing throughput. Moreover, the distribution of four dimensional and five non-dimensional parameters for the time domain shows that the standard deviation, compared to the others, reduced gradually with increases in blockage degree. Thus, the standard deviation was used to evaluate the online diagnosis of the blockage. The frequency domain distribution under different throughput reveals that the characteristic peaks consisting of the faulty frequency and multiple frequency were produced by the faulty blockage and the feed pump, respectively. Hence, the faulty peak of 16–17 Hz was adopted to judge the real-time blockage of the hydrocyclone, i.e., the presence of the characteristic peak marks the blockage, and its value is proportional to the blockage degree. The application of the online monitoring system demonstrates that the combination of the time domain and the frequency domain could admirably detect the running state and rapidly recognize blockage faults.

Research and analysis of the wheeled vehicle load spectrum editing method based on short-time Fourier transform

2019 ◽  
Vol 233 (14) ◽  
pp. 3671-3683
Author(s):  
Zongkai Liu ◽  
Chuan Peng ◽  
Xiaoqiang Yang
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Fatigue Damage ◽  
Time Domain ◽  
Short Time Fourier Transform ◽  
Load Spectrum ◽  
Statistical Parameters ◽  
Original Spectrum ◽  
The Time Domain ◽  
Short Time

The measured uniaxial-head load spectrum in the road simulation test has a large number of useless small loads. When applying the measured load spectrum directly, it will take a lot of time. This paper designs a comprehensive road spectrum measurement system to collect data and proposes a method for editing the uniaxial-head acceleration load spectrum using short-time Fourier transform to speed up the reliability test process and reduce time costs. In this method, the time domain and frequency domain information of the signal is obtained by short-time Fourier transform. The concept of accumulated power spectral density is proposed to identify the reduced load data, and the relative fatigue damage is used as the pass criterion. The length of the edited spectrum is only 66% of the original spectrum through the above-mentioned editing method and retains the relative damage amount of 91%. Finally, through the analysis of time domain, frequency domain, and fatigue statistical parameters, it demonstrates that the short-time Fourier transform–based acceleration load spectrum edition method could achieve a similar fatigue damage to the original spectrum in a shorter time.

Induction Motor Fault Diagnosis Using Voltage Spectrum of Auxiliary Winding and Lissajous Curve of its Park Components

2013 ◽  
Vol 805-806 ◽  
pp. 963-979 ◽  
Author(s):  
Lamiaâ El Menzhi ◽  
Abdallah Saad
Keyword(s):  
Fourier Transform ◽  
Fault Diagnosis ◽  
Frequency Domain ◽  
Induction Motor ◽  
Discrete Fourier Transform ◽  
Time Domain ◽  
New Method ◽  
Spectrum Simulation ◽  
Simulation Results ◽  
The Time Domain

In this paper, a new method for induction motor fault diagnosis is presented. It is based on the so-called an auxiliary winding voltage and its Park components. The auxiliary winding is a small coil inserted between two of the stator phases. Expressions of the inserted winding voltage and its Park components are presented. After that, discrete Fourier transform analyzer is required for converting the signals from the time domain to the frequency domain. A Lissajous curve formed of the two Park components is associated to the spectrum. Simulation results curried out for non defected and defected motor show the effectiveness of the proposed method.

Time‐domain solution for horizontal coaxial dipoles on a half‐space

Geophysics ◽  
1986 ◽  
Vol 51 (9) ◽  
pp. 1850-1852 ◽  
Author(s):  
David C. Bartel
Keyword(s):  
Frequency Domain ◽  
Half Space ◽  
Time Domain ◽  
Inverse Laplace Transform ◽  
Direct Solution ◽  
Current Waveform ◽  
Laplace Domain ◽  
Homogeneous Half Space ◽  
The Time Domain ◽  
The Magnetic Field

The practice of transforming frequency‐domain results into the time domain is fairly common in electromagnetics. For certain classes of problems, it is possible to obtain a direct solution in the time domain. A summary of these solutions is given in Hohmann and Ward (1986). Presented here is another problem which can be solved directly in the time domain—the magnetic field of horizontal coaxial dipoles on the surface of a homogeneous half‐space. Solutions are presented for both an impulse transmitter current and a step turnon in the transmitter current. The solution in the time domain is obtained by taking the inverse Laplace transform of the product of the frequency‐domain solution and the Laplace‐domain representation of the current waveform.

Time and Frequency Domain Performance Comparison for Wheeze Detection Using K-Nearest Neighbor

2014 ◽  
Vol 591 ◽  
pp. 163-166
Author(s):  
Syamimi Mardiah Shaharum ◽  
Kenneth Sundaraj
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
High Performance ◽  
Nearest Neighbor ◽  
Dominant Frequency ◽  
Performance Comparison ◽  
K Nearest Neighbor ◽  
Time Domain Data ◽  
The Time Domain ◽  
Domain Performance

In this Paper, the Comparison between the Performance of Wheezes Data Processing in the Frequency Domain and in the Time Domain is Evaluated Using K-Nearest Neighbor (KNN). the Purpose of this Paper is to Clarify the Confusion Regarding the Methods Used Nowadays, as many of the Previous Researchers have Stated that Wheezes Data are Better Processed in the Frequency Domain due to its Dominant Frequency Peaks but Not a Single Researcher has Made a Direct Comparison to Prove the Reliability of the Method Used. from the Evaluation Made, the Result Shows that the Performance of Wheeze Data Processed in the Frequency Domain is Better as Compared to the Data Processed in the Time Domain. A High Performance Accuracy with 97% is Obtained Comparing to an Accuracy Percentage of 83.13% were only Achieved by Using the Time Domain Data. Thus, this Paper has Successfully Made a Comparison between the Domains Proving the Reliability of the Frequency Domain for Wheeze Detection.

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