Computer simulation technique on the investigation of statistical regularities

Lemeshko, B. Yu.; Postovalov, S. N.; Chimitova, Ekaterina V.; Pomadin, S.S.; Ponomarenko, Volodymir; Frantsuzov, A.V.; Mirkin, E. P.; Lemeshko, S. B.

doi:10.1109/korus.2004.1555573

Cited by 4 publications

(7 citation statements)

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“…To test hypotheses about the belonging of the analyzed RV (Brinell hardness) to a certain distribution it is necessary to calculate its parameters and check the proximity of the theoretical and sample distribution densities according to the corresponding criterion, for example, the Pearson's chi-squared test ( 2 ) [59] or using more modern and popular [60] Kolmogorov-Smirnov, Cramer-von Mises, and Anderson-Darling goodness-of-fit tests.…”

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

“…There is a problem of choice of criteria of consent. It is noted in [60] that in the minds of many researchers, a strong opinion has formed about criteria of the type  2 as poor goodness of fit criteria. The authors of [60,61] do not agree with this opinion and emphasize that in the case of testing simple hypotheses and meeting a number of conditions, the fit criterion  2 is preferable to the nonparametric fit tests of Kolmogorov, Cramer-Mises-Smirnov, and Anderson-Darling.…”

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

“…It is noted in [60] that in the minds of many researchers, a strong opinion has formed about criteria of the type  2 as poor goodness of fit criteria. The authors of [60,61] do not agree with this opinion and emphasize that in the case of testing simple hypotheses and meeting a number of conditions, the fit criterion  2 is preferable to the nonparametric fit tests of Kolmogorov, Cramer-Mises-Smirnov, and Anderson-Darling. Let us agree with the arguments of the authors of [60,61] and stop in our studies on the goodness of fit criterion  2 .…”

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

“…3 shows the assessment results of the sample and theoretical hardness distribution densities for hH=4. A large number of formulas are known that allow choosing the number of intervals n in histograms, most of them are mentioned in [60]. For the sample size N>1000, it is recommended to choose n in the range from 12 to 16.…”

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

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Non-destructive testing of steel pipes that are long-term exploited according by statistical hardness parameters

Goncharov,

Osipov,

Brusnik

2023

Preprint

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The features of non-destructive testing of steel pipes with a long service life in terms of dynamic hardness parameters are considered. The limited applicability of normal and lognormal distributions, the Weibull and Gumbel distributions to describe the distribution density of hardness estimates for steels that have been in long-term operation in harsh meteorological and functional conditions of Siberia and the Far North is shown. A number of experiments were carried out on the formation of digital images of the hardness distribution over the surface of the tested products. Hypotheses are formulated regarding the use of such images to assess the current technical state of metal products and the dynamics of its change. The possibility of describing the hardness of steel specimens used for a long time in difficult conditions of Siberia by a weighted sum of two normal distributions has been experimentally proved.

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Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

Section: Assessment Of Belonging Of Random Variables To Distribution ...mentioning

confidence: 99%

See 2 more Smart Citations

Non-destructive testing of steel pipes that are long-term exploited according by statistical hardness parameters

Goncharov,

Osipov,

Brusnik

2023

Preprint

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“…Прийняття рішення про наявність сигналу здійснюється на основі перевірки двох статистичних гіпотез [19] відносно кумулянта другого порядку суміші ( )…”

Section: адитивна суміш сигналу та завадиunclassified

Detection of Noise Signal in the Additive Mixture Based on the Second-Order Cumulant

Bereznytskyi¹

2021

Electron. & Acoust. Eng.

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In order to determine the technical condition of energetic objects with the objective of ensuring their operational reliability, durability and safety, systems of noise diagnostics, which are based on the analysis of acoustic diagnostic signals. A promising area of noise diagnostics are cumulant methods, based on cumulant analysis, which involves the use of cumulants and cumulant coefficients. In known literature no characteristics of detection of a signal within an interference-containing additive mixture with the use of a second-order cumulant (variance) can be found. That is why the objective of the paper is to study the use of cumulant method on the basis of point estimations of variance for a sample of momentary values for detection of an acoustic signal against the background of noise interference. The research was carried out by way of modeling the additive mixture of signal and interference using the MATLAB® software package. Interference is a model of a noise acoustic signal, which accompanies the operation of properly functional equipment. Signal is a model of an acoustic signal which is created with the occurrence of a malfunction. Signal and interference are independent random variables, so the property of additivity of cumulants was used – the variance of a mixture equals the sum of variances of signal and interference. The decision about the presence of a signal was made on the basis of testing two statistical hypotheses. The null hypothesis – the signal is absent, variance equals to the variance of the interference. The first hypothesis – the signal is present, variance equals to the variance of the mixture. Additional parameters: probability of a Type I error 0,01, probability of correct determination 0,99. The relative error of estimation determined the minimal sample size. These values allowed for the calculation of the threshold value, upon the exceeding of which by the variance estimation, the decision on the presence of signal is made. For each sample, assessments of variance were made. Experimental probability of correct determination is calculated as a total number of decisions taken regarding the presence of a signal, divided by the number of realizations, and corresponds to the value of the specified probability of correct determination. Its relative error was calculated in order to control the validity of the results. Also, kernel density estimation of the probability of the variance assessment for the case of a signal with normal distribution. As shown by the graphs, the assessments have a distribution that is close to normal. The conducted study proves that a variance -based cumulant method allows to detect a signal against the background of noise interference. The necessary sample size, which shows the number of the necessary momentary values, is given in the paper. That is to say that with the help of the frequency of an analogue digital converter the needed duration of the recording of a real for assessment of its variance can be obtained, and the decision on the presence or absence of a signal is to be made on the basis of the specified threshold values. The results of the study can be added to the known sample sizes and threshold values for the coefficients of asymmetry and excess with different distributions. Application of the described method requires additional testing on real acoustic signals and has the areas of use in systems of noise diagnostics.

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Specific Features of Harmonic Conditions at the Node Connecting a Pulp-And-Paper Mill to a Supply Network

Luong

Ngo

Коверникова³

et al. 2020

Journal of Siberian Federal University. Engineering &Amp; Technologies

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The paper presents the results of the analysis on measured parameters of harmonics at the node of the high-voltage network. The measurements were made at the node connecting the pulp-and-paper mill to the 220 kV supply network. This load is nonlinear and has a large capacity. Particular attention is paid to the distributions of the current and voltage harmonics. The paper clearly shows probabilistic properties of the measured parameters of harmonics

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Computer simulation technique on the investigation of statistical regularities

Cited by 4 publications

References 0 publications

Non-destructive testing of steel pipes that are long-term exploited according by statistical hardness parameters

Non-destructive testing of steel pipes that are long-term exploited according by statistical hardness parameters

Detection of Noise Signal in the Additive Mixture Based on the Second-Order Cumulant

Specific Features of Harmonic Conditions at the Node Connecting a Pulp-And-Paper Mill to a Supply Network

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