The influence of quantization on level on an error of the digital voltmeter of alternating voltage

2021 ◽  
pp. 31-36
Author(s):  
Georgy I. Volovich
Keyword(s):  
Uniform Distribution ◽  
Digital Filter ◽  
Digital Voltmeter ◽  
Sampling Frequency ◽  
Quantization Error ◽  
Asynchronous Sampling ◽  
Level Quantization ◽  
Digit Capacity ◽  
Alternating Voltage

There are given the results of influence the level quantization to the accuracy of measured AC voltage by digital voltmeter. It is shown the influence of sampling frequency and the type of digital filter to effective digit capacity of conversion in case of synchronous and asynchronous sampling. There is obtained an estimate of error by representing the quantization error by centered noise with a uniform distribution. There are presented the results of modeling a digital voltmeter.

Design of Digital Filter Based on Numerical Simulation

2014 ◽  
Vol 539 ◽  
pp. 79-83
Author(s):  
Chuan Ting Wei ◽  
Quan Li Ning ◽  
Dong Chen
Keyword(s):  
Numerical Simulation ◽  
Mathematical Model ◽  
Digital Filter ◽  
Sampling Frequency ◽  
New Wave ◽  
Matlab Software ◽  
Frequency Wave

In MATLAB software, it has FDATool toolbox, which can design digital filter specific according to specific circuit, and analyze the performance of the filter according to the parameters of filter. In this paper we establish simulation mathematical model of digital filter based on the calculation principle of distributed multiplication accumulator. According to the logic algorithm we design delay algorithm of digital filter, and use MATLAB software to do simulation on amplitude frequency and phase frequency of digital filter. After superposition of different sampling frequency wave we get new waveform, and realize the digital filter for the new wave. It proves the availability of mathematical model and the program, and provides the technical reference for the design of digital filter.

Estimate of the Optimum Cutoff Frequency for the Butterworth Low-Pass Digital Filter

1999 ◽  
Vol 15 (3) ◽  
pp. 318-329 ◽  
Author(s):  
Bing Yu ◽  
David Gabriel ◽  
Larry Noble ◽  
Kai-Nan An
Keyword(s):  
Digital Filter ◽  
Cutoff Frequency ◽  
Sampling Frequency ◽  
Residual Analysis ◽  
Data Set ◽  
Raw Data ◽  
Standard Data ◽  
Cutoff Frequencies ◽  
Flexion Extension ◽  
Low Pass

The purposes of this study were (a) to develop a procedure for objectively determining the optimum cutoff frequency for the Butterworth low-pass digital filler, and (b) to evaluate the cutoff frequencies derived from the residual analysis. A set of knee flexion-extension angle data in normal gait was used as the standard data set. The standard data were sampled at different sampling frequencies. Random errors with different magnitudes were added to the standard data to create different sets of raw data with a given sampling frequency. Each raw data set was filtered through a Butterworth low-pass digital filter at different cutoff frequencies. The cutoff frequency corresponding to the minimum error in the second time derivatives for a given set of raw data was considered as the optimum for that set of raw data. A procedure for estimating the optimum cutoff frequency from the sampling frequency and estimated relative mean error in the raw data set was developed. The estimated optimum cutoff frequency significantly correlated to the true optimum cutoff frequency with a correlation determinant value of 0.96. This procedure was applied to estimate the optimum cutoff frequency for another set of kinematic data. The calculated accelerations of the filtered data essentially matched the measured acceleration curve. There is no correlation between the cutoff frequency derived from the residual analysis and the true optimum cutoff frequency. The cutoff frequencies derived from the residual analysis were significantly lower than the optimum, especially when the sampling frequency is high.

scholarly journals Methods of Forming Orthogonal Components of Input Signals for Relay Protection

2019 ◽  
Vol 62 (1) ◽  
pp. 5-14 ◽  
Author(s):  
F. A. Romaniuk ◽  
М. S. Loman ◽  
V. S. Kachenya
Keyword(s):  
Fundamental Frequency ◽  
Digital Filter ◽  
Sampling Frequency ◽  
Transient Phenomena ◽  
Advantages And Disadvantages ◽  
Input Signals ◽  
Orthogonal Components ◽  
Sine Signal ◽  
Aperiodic Component ◽  
The Mathematical Model

The existing frequency digital filters for allocation of the fundamental frequency of a sine signal are considered and their advantages and disadvantages are noted. Preference is given to the combined digital filter. The existing methods of determining the orthogonal components of a sine signal are analyzed and their disadvantages are pointed out. It is concluded that most of the existing methods for determining orthogonal components are sensitive to the fundamental frequency deviation of the sine signal. This is due to the fact that the deviation of the frequency alters the angle of one sample. The method for solving this problem has been proposed. The essence of the method is the dynamic recalculation of the angle of one sample depending on the calculated frequency. The mathematical model for research of ways of formation of orthogonal components is presented. The model includes transient generator taking into account the aperiodic component, combined digital filter and the methods of formation of orthogonal components under study. The method of transient phenomena formation that takes into account the aperiodic component is described. Coefficients of combined digital filter for sampling frequency of 1200 Hz are given. One of the implementations of the proposed method of formation of orthogonal components in the programming language MatLab is presented. One of the more popular methods and the proposed method acted as the formers of orthogonal components under study. The final part of the article presents the results of the research, as well as their analysis.

scholarly journals Implementasi Filter Finite Impulse Response (FIR) Window Hamming dan Blackman menggunakan DSK TMS320C6713

2018 ◽  
Vol 4 (1) ◽  
pp. 16
Author(s):  
LITA LIDYAWATI ◽  
PAULINE RAHMIATI ◽  
YULI SUNARTI
Keyword(s):  
Impulse Response ◽  
Digital Filter ◽  
Finite Impulse Response ◽  
Sampling Frequency ◽  
Test Results ◽  
Frequency Bandwidth ◽  
Magnitude Response ◽  
Frequency Bands ◽  
Stopband Attenuation ◽  
Simulation Results

ABSTRAKFilter didefinisikan sebagai proses atau rangkaian yang melewatkan pita frekuensi tertentu yang diinginkan dan meredam pita frekuensi lainnya. Salah satu metode perancangan filter digital Finite Impulse Response (FIR) adalah metode windowing. Dalam penelitian ini digunakan jenis window Hamming dan Blackman. Simulasi dilakukan dengan menggunakan software Matlab dengan memasukan frekuensi passband, frekuensi stopband, ripple passband, dan stopband attenuation. Dengan frekuensi sampling sebesar 15000 Hz, frekuensi passband sebesar 3000 Hz, frekuensi stopband sebesar 5000 Hz. Setelah simulasi dilakukan implementasi filter dengan parameter yang sama menggunakan DSK TMS 320C6713 dengan bantuan software CCS. Simulasi dan implementasi dilakukan pada semua band frekuensi. Hasil pengujian terhadap implementasi filter adalah respon magnitude, frekuensi cut-off, bandwidth, dan faktor kualitas dengan hasil simulasi tidak menunjukkan perbedaan yang signifikan.Kata kunci: filter digital, windowing, Hamming, Blackman, frekuensi cut-off.ABSTRACTFilter is defined as a process or series that skip certain desired frequency band and other frequency bands drown. One method of designing a digital filter Finite Impulse Response (FIR) is a windowing method. This study used the type of window Hamming and Blackman. Simulations performed using Matlab software by inserting a frequency passband, stopband frequency, passband ripple, and stopband attenuation. With a sampling frequency of 15,000 Hz, a frequency of 3000 Hz passband, stopband frequency of 5000 Hz. After the simulation is completed, implementation of the filter with the same parameters using TMS 320C6713 DSK with the help of software CCS. Simulation and implmentasi performed on all frequency bands. The test results of the implementation of the filter is the Magnitude response, the cut-off frequency, bandwidth, and quality factor with simulation results showed no significant difference.Keywords: digital filter, windowing, Hamming, Blackman, cut-off frequency.

scholarly journals Audio module to capture, store and reproduce sound

2021 ◽  
Author(s):  
Jason Leitón-Jiménez Leitón Jiménez
Keyword(s):  
Embedded System ◽  
Digital Filter ◽  
User Interaction ◽  
Quality Criteria ◽  
Digital Signal ◽  
Sampling Frequency ◽  
Production Costs ◽  
Analog Signal ◽  
Electronic Components ◽  
Development Platform

This poster explains the design of an audio module, which is capable of capturing sound signals and storing them for later reproduction. The development platform is an embedded system (Beaglebone black), which has GPIO pins for user interaction. One of the objectives of the module is to keep production costs low, so the electronic components will be chosen taking quality criteria in operation as well as their cost. In the software component, the fdatool tool will be use to design the digital filter, getting the differences equation. It should be noted two major challenges that the development of this project has are the presence of noise in the analog signal and the sampling frequency with which the samples are taken to obtain the digital signal.

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