Mykhaylo Dorozhovets

Estimation of the best measurement result and its standard uncertainty by input observations processing using the method of reference samples based on order statistics

In the paper the new method of the measurement observations processing, based on their comparison (after sorting) with several reference samples, which are corresponded to the models of the general population density distributions (so called reference distributions), is investigated and analyzed. The elements of reference samples are equal to the mathematical expectations of order statistics corresponding to the reference distribution. The mathematical models of the determination of the best result and its standard uncertainty are presented. The effectiveness of proposed method is investigated by the Monte Carlo method for 5 models of general population (Laplace, normal, triangular, uniform and arcsine) with the number of observations equal 9, 19, 29, 39 and 49. The proposed method can be used if the observations number is small. If the observations distribution significantly differs from normal distribution then the proposed method guarantees considerable decreases of the uncertainty result in comparison with the uncertainty of average value.

Using F - Test for the indirect detecting of the autocorrelation of random observations

A proposed test is realized by the separation of N registered observations into k shorter series containing n observations (N = n·k), estimation and comparing the variance of the mean values of these series with an average of their variances. If the ratio of these variance estimators after normalization by the number of degrees of freedom k - 1 and N - k is greater than the critical value Fcritic(1 - α, n - 1, N - n) from the F - distribution (α is a significance level) then it testifies to the auto correlation of observations. The effectiveness of the proposed test is investigated by the Monte-Carlo method.

Investigation of the direct and indirect conductivity distribution image reconstruction algorithms in electrical tomography

In this paper the two conductivity distribution reconstruction algorithms are presented. The first based on the previous resistivity reconstruction and the second one based on the usage of the inverse measured voltages. Efficiency of the presented algorithms compared with the direct conductivity distribution. Modeling results shows that these two algorithms provide better convergence of the iteration process of solving the inverse tomography problem.

The application of runs test for evaluation of the standard uncertainty of the arithmetic mean of autocorrelated observation

This paper presents the application of runs test for indirect consideration of observations autocorrelation in estimation of a standard uncertainty of arithmetic mean value. At first stage researches were performed by Monte Carlo (MC) simulation for two kinds random signals: first order autoregression (AR) and moving averaging (MA). Comparison of theoretical values of effective number of observations and determined by the runs test showed a good their convergence (Fig. 2, Fig. 3). This convergence increased when for AR signal level of autocorrelation decreased and for MA signal number of observation increased. To verify simulation results the runs test was used to analyses of random signal of known exponential autocorrelation function (exp (−i/fs·τf)) on output of first order RC low pass filter of time constant τf and different sample frequencies fs. Obtained results (Fig. 8) confirmed simulation results.

Measurement of a surface temperature distribution using multi-element resistance sensor

This paper presents some aspects of a spatial temperature distribution measurement using a planar multi-element resistance sensor. Metrological characteristics of this sensor are described and investigated in detail. The parameters of 16 channel data acquisition system based on Siemens 6ES7531-7KF00-0AB0 module are reviewed. The technique of a spatial temperature distribution reconstruction based on its previous approximation and the solution of inverse problem is considered in detail. A simulation of a temperature distribution reconstruction and errors are presented and analyzed.

Accuracy of Reconstruction of the Spatial Temperature Distribution Based on Surface Temperature Measurements by Resistance Sensors

In this paper, the method and instrumental aspects of the reconstruction of 2D temperature distribution are investigated. It is based on measurements of the resistance of planar temperature sensors. The first component depends on number of sensors and of the used 2D approximation of temperature distribution. The second component depends on the parameters (additive and multiplicative) of accuracy of used resistance measurements. The mean, root mean squared and maximum, minimum error parameters are determined and analyzed using Monte Carlo method.

Method of evaluation the measurement uncertainty of the minimal value of observations and its application in testing of plastic products

In this paper the non-standard statistical method for evaluating uncertainty, when a minimal observation is the measurement result, is proposed. This method is based on properties of minimal order statistic. As example, in measurement practice this method is used to evaluate the uncertainty of a percent elongation and tensile strength in testing plastic products. The accuracy of obtained experimental results is also investigated by Monte Carlo simulation. Proposed method can be used to uncertainty evaluation of another quantities, when the minimal (or maximal) value of several normally distributed random observations is the result of measurement.

Method of Improving Accuracy of Measurement of the Acoustic Pulses Time-of-Flight Based on Linear Modulation of Period

In this paper the main problems that appear in measurement of time-of-flight intervals in acoustic tomography are analyzed. They are related to the influence of noise and with a limited slew rate of the signal amplitude envelope. The method based on linear modulation of the acoustic pulses period is proposed. Correction of directly measured time interval is based on the additional measurement of duration of the given number of half periods of received signal when the signal envelope is stabilized at a sufficient level. The efficiency of proposed method of correction is investigated by simulation.

Processing of the random observations with Flatten — Gaussian distribution by approximate order statistics method

In the paper the method based on order statistics for processing of the random observations with so called Flatten - Gaussian distribution that is a convolution of rectangular and normal distributions, is proposed. This method gives a smaller standard uncertainty of a location parameter compared to a standard uncertainty of a mean value. The efficiency of the method increases with the increase content of the uniform component. The implementation of the proposed method does not require complicated calculations and based on an analytical expression of a normalized Flatten - Gaussian density distribution. The research results of method, which are the standard uncertainty depending on the relative content of components and the number of observations, are presented.

Data Acquisition System and Reference Model Used for the Investigation and Verification of the Resistance Tomography System

In this paper the data acquisition system (DAQ) and metrology verification technique of electrical resistivity tomography system is proposed and investigated. The verification is based on the reference model of resistivity distribution that is constructed as a network of the discrete resistors. Proposed technique permits to verify the DAQ, reconstruction algorithm and approximation effects jointly or separately. The reference network parameters and the stages of the verification algorithm are in details described. The DAQ 6-12-24-electrodes object current excitation and interelectrode voltage measurement using difference method.