Establishing the State of Operation on Vibration Behavior of the Industrial Robot

2012 ◽  
Vol 186 ◽  
pp. 247-253 ◽  
Author(s):  
Dan Niculescu ◽  
Marek Vagaš ◽  
Adrian Olaru ◽  
Mikuláš Hajduk ◽  
Adrian Ghionea
Keyword(s):  
Fourier Transform ◽  
Life Cycle ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Preventive Maintenance ◽  
Industrial Robot ◽  
Maintenance Management ◽  
Automatic Diagnosis ◽  
Made In

Diagnosis measurement of vibration and noise, should allow monitoring of equipment defects, through a system of preventive maintenance, predictive. Automatic diagnosis of machinery and equipment was made in order to ensure a higher reliability of these and how to obtain a more extended life cycle without the occurrence of defects. Vibrations are always measured in analog format (time domain) and must be transformed into the frequency domain. Therefore Fast Fourier Transform (FFT) method is used to evaluate vibration Almega AX-V6 robot. The application of preventive and predictive maintenance management supports enterprise, because it proves effective, the information you provide in making decisions.

scholarly journals Problem Pengolahan Data Gaya Berat Mikro antar Waktu

2016 ◽  
Vol 3 (02) ◽  
pp. 130
Author(s):  
Supriyadi S
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Groundwater Level ◽  
Time Lapse ◽  
Density Change ◽  
Gravity Survey ◽  
Micro Gravity

<span>At time lapse microgravity survey will be got data in place for difference period. The Anomaly <span>caused by subsidence and density change under surface which related to groundwater level <span>change. This matter become problem when will take one of the anomaly sources to processed <span>is furthermore. Reduction one of anomaly source cannot be done direct but must be done with <span>filtering process. Process filtering done by using FFT (Fast Fourier Transform), its principal is <span>to move data from time domain to frequency domain. At frequency domain this is mathematics <span>process conducted. On subsidence case study in Semarang by using this technique indicate that <span>subsidence value from time lapse micro gravity survey have tendency is equal to result from <span>geodesy survey.</span></span></span></span></span></span></span></span><br /></span>

scholarly journals Data-Driven Modeling of a Commercial Photovoltaic Microinverter

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Hayder D. Abbood ◽  
Andrea Benigni
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Simulated Data ◽  
Data Driven ◽  
System Level ◽  
Operating Modes ◽  
System Level Simulation ◽  
Data Driven Modeling

We present a data-driven modeling (DDM) approach for static modeling of commercial photovoltaic (PV) microinverters. The proposed modeling approach handles all possible microinverter operating modes, including burst mode. No prior knowledge of internal components, structure, and control algorithm is assumed in developing the model. The approach is based on Artificial Neural Network (ANN) and Fast Fourier Transform (FFT). To generate the data used to train the model, a Power Hardware in the Loop (PHIL) approach is applied. Instantaneous inputs-outputs data are collected from the terminals of a commercial PV microinverter at time domain. Then, the collected data are converted to the frequency domain using Fast Fourier Transform (FFT). The ANNs that are the core of the DDM are developed in frequency domain. The outputs of the ANNs are then converted back to time domain for validation and use in system level simulation. The comparison between measured and simulated data validates the performance of the presented approach.

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 Application of two-dimensional fast Fourier transform algorithm, analog of the Cooley-Tukey algorithm, for 4k fixed format digital image of satellite data in frequency domain processing

2020 ◽  
Vol 149 ◽  
pp. 02010 ◽  
Author(s):  
Mikhail Noskov ◽  
Valeriy Tutatchikov
Keyword(s):  
Fourier Transform ◽  
Numerical Experiment ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Discrete Fourier Transform ◽  
Satellite Data ◽  
Digital Image ◽  
Digital Images ◽  
Two Dimensional ◽  
Fast Fourier Transform Algorithm

Currently, digital images in the format Full HD (1920 * 1080 pixels) and 4K (4096 * 3072) are widespread. This article will consider the option of processing a similar image in the frequency domain. As an example, take a snapshot of the earth's surface. The discrete Fourier transform will be computed using a two-dimensional analogue of the Cooley-Tukey algorithm and in a standard way by rows and columns. Let us compare the required number of operations and the results of a numerical experiment. Consider the examples of image filtering.

Current spectrum estimation using Prony's estimator and coherent resampling

2014 ◽  
Vol 33 (3) ◽  
pp. 989-997 ◽  
Author(s):  
Michał Lewandowski ◽  
Janusz Walczak
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Domain Model ◽  
Spectrum Estimation ◽  
Nonlinear Load ◽  
Frequency Model ◽  
Content Type ◽  
Base Frequency ◽  
Current Spectrum

Purpose – A highly accurate method of current spectrum estimation of a nonlinear load is presented in this paper. Using the method makes it possible to evaluate the current injection frequency domain model of a nonlinear load from previously recorded time domain voltage and current waveforms. The paper aims to discuss these issues. Design/methodology/approach – The method incorporates the idea of coherent resampling (resampling synchronously with the base frequency of the signal) followed by the discrete Fourier transform (DFT) to obtain the frequency spectrum. When DFT is applied to a synchronously resampled signal, the spectrum is free of negative DFT effects (the spectrum leakage, for example). However, to resample the signal correctly it is necessary to know its base frequency with high accuracy. To estimate the base frequency, the first-order Prony's frequency estimator was used. Findings – It has been shown that the presented method may lead to superior results in comparison with window interpolated Fourier transform and time-domain quasi-synchronous sampling algorithms. Research limitations/implications – The method was designed for steady-state analysis in the frequency domain. The voltage and current waveforms across load terminals should be recorded simultaneously to allow correct voltage/current phase shift estimation. Practical implications – The proposed method can be used in case when the frequency domain model of a nonlinear load is desired and the voltage and current waveforms recorded across load terminals are available. The method leads to correct results even when the voltage/current sampling frequency has not been synchronized with the base frequency of the signal. It can be used for off-line frequency model estimation as well as in real-time DSP systems to restore coherent sampling of the analysed signals. Originality/value – The method proposed in the paper allows to estimate a nonlinear load frequency domain model from current and voltage waveforms with higher accuracy than other competitive methods, while at the same time its simplicity and computational efficiency is retained.

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