Implementation of gauss error integral for assessment of the metrological characteristics of information measuring system converter
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- Category: Information technologies, systems analysis and administration
- Last Updated on 29 July 2014
- Published on 17 October 2013
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Authors:
S.I. Melnychuk, Cand. Sci. (Tech.), Associate Professor, Private Higher Educational Institution “Galytska Academy”, Head of the Computer and Software Engineering Department, Ivano-Frankivsk, Ukraine.
I.Z. Manuliak Private Higher Educational Institution “Galytska Academy”, Assistant Lecturer of the Computer and Software Engineering Department, Ivano-Frankivsk, Ukraine.
Abstract:
Background. The main indicator of the primary converter is its accuracy. Modern methods of obtaining of relevant metrological characteristics can be divided on two groups: the group for of error definition and the group for uncertainty assessment. But this methods have insufficient information capacity concerning probabilistic characteristics of the measured value and consequently the results ambiguity is unsatisfactory. The purpose of the study is to investigate the possibility of application of the Gaussian error integral to analyze the sensor’s metrological characteristics.
Methodology. During the numerical simulation we have processed several sets of test signals with different aperture of amplitude and standard deviation. The results of statistical analysis of each set showed that the increase of the number of observations decreases the uncertainty of the A-type, and this greatly complicates the sensors metrological characteristics adequate evaluation. To amend this disadvantage we have used the credibility functions of measuring signal. Their analysis allows us to assess the probability error characteristics.
Findings. The proposed approach has been imple-mented for analysis of the characteristics of the exploratory prototype of the gas flow transducer. As the initial data we have used the results of the experimental studies of conversion error on the standard machine. Based on the results we have found that, given confidence level of observations of the measured value we can estimate the random component of the error in the previous development phases of the information-measuring systems primary transmitters.
Originality. We propose to use the Gaussian error integral for the signal analysis of transducers. This allows us to determine the probability if the measured value falls in the given interval, which is defined (limited) by acceptable error.
Practical value. The proposed approach allows us to interpret precisely the measurement results, and thus to obtain the reasonable, accurate and almost complete information about the uncertainty of the primary converter measurement.
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