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Papers by Jacek Puchalski
Ukrainian Metrological Journal
The estimation of the accuracy of the linear regression method used for measurements based on the... more The estimation of the accuracy of the linear regression method used for measurements based on the GUM recommendations is considered. The impact of correlation and autocorrelation of the variable Y data together with type A and type B uncertainties, not provided in statistical literature about regression methods, is discussed. The theoretical backgrounds are given. The simulated examples of determining the uncertainty bands of the regression line fitted to the measured points with different cases of correlated values and absolute and relative uncertainties of type A and type B of the dependent variable Y are considered.
Pomiary Automatyka Robotyka
The work continues the series of publications on the estimation of the parameters of the equation... more The work continues the series of publications on the estimation of the parameters of the equation and the limits of the uncertainty band of the straight-line y = ax + b fitted to the measurement results of both coordinates of the tested points with the use of the linear regression method. A general case was considered when these coordinates have different uncertainties and there are all possible autocorrelations and cross-correlations. Description of matrix equations was used. The results of the coordinate measurements are presented as elements of the X and Y vectors. The propagation of their uncertainty was described by the UZ covariance matrix with four component matrices, i.e., UX and UY – for the uncertainties and autocorrelations of X and of Y, and UXY and its transposition U – for the cross-correlations. The equation of a straight line and of the borders of its uncertainty band are given. Obtained them for the function of parameters a and b satisfying the so-called total crite...
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej, 2019
Ukrainian Metrological Journal, 2020
The new extended mathematical model for evaluation uncertainties of indirect multivariable measur... more The new extended mathematical model for evaluation uncertainties of indirect multivariable measurements, which upgrades the method given in Supplement 2 of guide GUM, is presented. In this model the uncertainties and correlations of parameters of the processing function are taken also into account. This model can be used for multivariable measurements and to describe the accuracy of instruments and systems that perform such measurements. The estimation of uncertainties of voltage and current on the output of a twoport network from indirect measurements on its input with considering influences the uncertainties of twoport elements is included.
Pomiary Automatyka Robotyka, 2020
Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.... more Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.0 1. Wprowadzenie Metoda regresji liniowej jest podstawowym narzędziem matematycznym stosowanym do wyznaczania linii prostej, lub innej zlinearyzowanej funkcji, dopasowanej do danych pomiarowych według określonego kryterium [1-4]. Ocenę dokładności wyników pomiarów w służbach metrologicznych, nauce, przemyśle i wielu innych dziedzinach dokonuje się obecnie według zaleceń Przewodnika Wyznaczania Niepewności GUM [5], opisanych też w literaturze [6-9]. W literaturze o metodzie regresji liniowej dokładność wyznaczania parametrów linii prostej ocenia się statystycznie tylko z niepewności eksperymentu pomiarowego. Wpływu niepewności typu B nie rozpatrywano. Poprawna heurystyczna ocena tej niepewności jako spodziewanego skutku różnych oddziaływań, nieznanych co do wartości
Journal of Physics: Conference Series, 2018
Signal processing in a multi-variable indirect measurement system and its uncertainties is consid... more Signal processing in a multi-variable indirect measurement system and its uncertainties is considered. It was proposed to extend the vector method of estimating uncertainties, given in Supplement 2 to GUM for the use to describe the accuracy of instrumental systems for indirect multivariable measurements. A formula for the covariance matrix of relative uncertainties is also given. As the example, the covariance matrix for indirect measurements of the star form circuit resistances from its terminals was determined and influence of of the measurement channels uncertainties are analyzed.
Applied Optics, 1994
Two interpolants are presented for Runge-Kutta ray tracing using the four-component method. Such ... more Two interpolants are presented for Runge-Kutta ray tracing using the four-component method. Such a continuous interpolant of ray trajectory connects only two adjacent Runge-Kutta points and requires only the information needed to find the position and ray vector for interpolant of ray position and ray vector to the fourth-order error. However Runge-Kutta schemes in contrast to other schemes are not based on approximating the continuous ray path with a polynomial. For this reason an optimal interpolant is shown that gives the same accuracy for calculating ray position and ray vector as a single-step integration in the Runge-Kutta scheme.
OSA Annual Meeting
In this paper a new method for OPL computation for gradient-index media has been presented. This ... more In this paper a new method for OPL computation for gradient-index media has been presented. This method is suitable for use with the fast and accurate ray-trace procedures which were developed earlier.
Series on Advances in Mathematics for Applied Sciences, 2022
Advances in Intelligent Systems and Computing, 2020
This two-part paper presents an improved version of the method of evaluation uncertainties in the... more This two-part paper presents an improved version of the method of evaluation uncertainties in the multivariable indirect measurements. It has an extended scope of application compared to the method given in Supplement 2 of the international guide with the acronym GUM [1], which assumes a perfectly accurate parameters multidimensional function of processing input measurement data. Part 1 discussed the cases of various correlations of measured values. The law of variance propagation is described in the form of dependencies between input and output covariance matrices. General formulas for uncertainty and correlation coefficients at the output are given as well as formulas for several characteristic cases. It has been shown that for pairs of all measured quantities, the effect of correlation between sets of deviations with uncertainty for each of types A and B should be considered separately. Proposed is to calculate output covariance matrices of correlated variables separately for uncertainties type A and type B An example of associated two-parameter (2D) measurements is also discussed. In this Part 2, the effect of uncertainties of the processing function parameters on the elements of output multimeasurand covariance matrix has been determined. General formulas for full correlation and its absence are given. An example of the evaluation uncertainties of indirect current and voltage measurements on the inaccessible input of the T-type impedance twoport network based on measurements at its output is considered in detail. Final conclusions are given. The proposed upgraded method is versatile, because it allows both the estimation of the accuracy of indirect multivariable measurements as well a description of the accuracy of instruments and measuring systems performing such measurements. Keywords: Multivariable measurements Á Multi-measurand Á Propagation of uncertainties Á Covariance matrix Á Correlation coefficient Á Correlations of deviations of type A or type B Á Uncertainties of processing function
Advances in Intelligent Systems and Computing, 2021
In this paper three examples of processing uncertainties of a indirect multi-variable measurement... more In this paper three examples of processing uncertainties of a indirect multi-variable measurement system are considered. It was proposed to extend the vector method of estimating measurement uncertainties, given in Supplement 2 to GUM, on the statistical description of the accuracy of whole ranges of indirect multivariable measurement system. Formula for the covariance matrix of relative uncertainties of the vector measurand is given. The covariance matrixes of uncertainties of few DC electrical measurement circuits are presented, i.e.: for indirect measurement of three resistances with using them in three variants of balanced Wheatstone bridge or without disconnection this circuit but with apply unconventional current supplies; the measurement of three internal resistances of the star circuit from its terminals and estimation of uncertainty of powers of two currents if two other currents are measured and their uncertainties are known. Formulas for absolute and relative uncertainties and their correlation coefficients are given. The general conclusion is that in the description accuracy of multivariable measurement systems the relative uncertainties are sometimes preferable than the absolute ones, and uncertainties of their main measurement functions have been also considered.
2019 12th International Conference on Measurement, 2019
The paper presents an upgraded version of the vector method of evaluation of multiparameter measu... more The paper presents an upgraded version of the vector method of evaluation of multiparameter measurement uncertainties stated in the Supplement 2 to GUM guide. This was done on the example of two-parameter jointed measurements. It consists of the correlation of individual components of the type A and/or type B uncertainty of input measurands. The general formulas for the covariance matrix, final uncertainties, and correlation coefficient were determined. The 3D graph shows the correlation coefficients of the output quantities as a function of the type B contributions in the uncertainty of two input quantities. It has been demonstrated that the inclusion of correlations of uncertainty components makes the uncertainty evaluations more reliable and accurate.
Pomiary Automatyka Robotyka, 2020
Pomiary Automatyka Robotyka, 2019
Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.... more Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.0 1. Wprowadzenie W 1993 r. w międzynarodowym przewodniku wyznaczania niepewności pomiarów o angielskim akronimie GUM [1] wprowadzono nowe pojęcie "niepewność" do oceny dokładności pomiarów. Pojawiła się wówczas niejednolitość z dotychczas stosowanym opisem dokładności przyrządów, urządzeń i systemów pomiarowych przez błędy pomiarowe. Producenci aparatury pomiarowej podają nadal maksymalny dopuszczalny błąd przyrządu MPE (ang. maximum permissible error) [3]. Przy założeniu równomiernego rozkładu odchy
Pomiary Automatyka Robotyka, 2019
Pomiary Automatyka Robotyka, 2018
Pomiary Automatyka Robotyka, 2018
Ukrainian Metrological Journal
The estimation of the accuracy of the linear regression method used for measurements based on the... more The estimation of the accuracy of the linear regression method used for measurements based on the GUM recommendations is considered. The impact of correlation and autocorrelation of the variable Y data together with type A and type B uncertainties, not provided in statistical literature about regression methods, is discussed. The theoretical backgrounds are given. The simulated examples of determining the uncertainty bands of the regression line fitted to the measured points with different cases of correlated values and absolute and relative uncertainties of type A and type B of the dependent variable Y are considered.
Pomiary Automatyka Robotyka
The work continues the series of publications on the estimation of the parameters of the equation... more The work continues the series of publications on the estimation of the parameters of the equation and the limits of the uncertainty band of the straight-line y = ax + b fitted to the measurement results of both coordinates of the tested points with the use of the linear regression method. A general case was considered when these coordinates have different uncertainties and there are all possible autocorrelations and cross-correlations. Description of matrix equations was used. The results of the coordinate measurements are presented as elements of the X and Y vectors. The propagation of their uncertainty was described by the UZ covariance matrix with four component matrices, i.e., UX and UY – for the uncertainties and autocorrelations of X and of Y, and UXY and its transposition U – for the cross-correlations. The equation of a straight line and of the borders of its uncertainty band are given. Obtained them for the function of parameters a and b satisfying the so-called total crite...
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej, 2019
Ukrainian Metrological Journal, 2020
The new extended mathematical model for evaluation uncertainties of indirect multivariable measur... more The new extended mathematical model for evaluation uncertainties of indirect multivariable measurements, which upgrades the method given in Supplement 2 of guide GUM, is presented. In this model the uncertainties and correlations of parameters of the processing function are taken also into account. This model can be used for multivariable measurements and to describe the accuracy of instruments and systems that perform such measurements. The estimation of uncertainties of voltage and current on the output of a twoport network from indirect measurements on its input with considering influences the uncertainties of twoport elements is included.
Pomiary Automatyka Robotyka, 2020
Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.... more Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.0 1. Wprowadzenie Metoda regresji liniowej jest podstawowym narzędziem matematycznym stosowanym do wyznaczania linii prostej, lub innej zlinearyzowanej funkcji, dopasowanej do danych pomiarowych według określonego kryterium [1-4]. Ocenę dokładności wyników pomiarów w służbach metrologicznych, nauce, przemyśle i wielu innych dziedzinach dokonuje się obecnie według zaleceń Przewodnika Wyznaczania Niepewności GUM [5], opisanych też w literaturze [6-9]. W literaturze o metodzie regresji liniowej dokładność wyznaczania parametrów linii prostej ocenia się statystycznie tylko z niepewności eksperymentu pomiarowego. Wpływu niepewności typu B nie rozpatrywano. Poprawna heurystyczna ocena tej niepewności jako spodziewanego skutku różnych oddziaływań, nieznanych co do wartości
Journal of Physics: Conference Series, 2018
Signal processing in a multi-variable indirect measurement system and its uncertainties is consid... more Signal processing in a multi-variable indirect measurement system and its uncertainties is considered. It was proposed to extend the vector method of estimating uncertainties, given in Supplement 2 to GUM for the use to describe the accuracy of instrumental systems for indirect multivariable measurements. A formula for the covariance matrix of relative uncertainties is also given. As the example, the covariance matrix for indirect measurements of the star form circuit resistances from its terminals was determined and influence of of the measurement channels uncertainties are analyzed.
Applied Optics, 1994
Two interpolants are presented for Runge-Kutta ray tracing using the four-component method. Such ... more Two interpolants are presented for Runge-Kutta ray tracing using the four-component method. Such a continuous interpolant of ray trajectory connects only two adjacent Runge-Kutta points and requires only the information needed to find the position and ray vector for interpolant of ray position and ray vector to the fourth-order error. However Runge-Kutta schemes in contrast to other schemes are not based on approximating the continuous ray path with a polynomial. For this reason an optimal interpolant is shown that gives the same accuracy for calculating ray position and ray vector as a single-step integration in the Runge-Kutta scheme.
OSA Annual Meeting
In this paper a new method for OPL computation for gradient-index media has been presented. This ... more In this paper a new method for OPL computation for gradient-index media has been presented. This method is suitable for use with the fast and accurate ray-trace procedures which were developed earlier.
Series on Advances in Mathematics for Applied Sciences, 2022
Advances in Intelligent Systems and Computing, 2020
This two-part paper presents an improved version of the method of evaluation uncertainties in the... more This two-part paper presents an improved version of the method of evaluation uncertainties in the multivariable indirect measurements. It has an extended scope of application compared to the method given in Supplement 2 of the international guide with the acronym GUM [1], which assumes a perfectly accurate parameters multidimensional function of processing input measurement data. Part 1 discussed the cases of various correlations of measured values. The law of variance propagation is described in the form of dependencies between input and output covariance matrices. General formulas for uncertainty and correlation coefficients at the output are given as well as formulas for several characteristic cases. It has been shown that for pairs of all measured quantities, the effect of correlation between sets of deviations with uncertainty for each of types A and B should be considered separately. Proposed is to calculate output covariance matrices of correlated variables separately for uncertainties type A and type B An example of associated two-parameter (2D) measurements is also discussed. In this Part 2, the effect of uncertainties of the processing function parameters on the elements of output multimeasurand covariance matrix has been determined. General formulas for full correlation and its absence are given. An example of the evaluation uncertainties of indirect current and voltage measurements on the inaccessible input of the T-type impedance twoport network based on measurements at its output is considered in detail. Final conclusions are given. The proposed upgraded method is versatile, because it allows both the estimation of the accuracy of indirect multivariable measurements as well a description of the accuracy of instruments and measuring systems performing such measurements. Keywords: Multivariable measurements Á Multi-measurand Á Propagation of uncertainties Á Covariance matrix Á Correlation coefficient Á Correlations of deviations of type A or type B Á Uncertainties of processing function
Advances in Intelligent Systems and Computing, 2021
In this paper three examples of processing uncertainties of a indirect multi-variable measurement... more In this paper three examples of processing uncertainties of a indirect multi-variable measurement system are considered. It was proposed to extend the vector method of estimating measurement uncertainties, given in Supplement 2 to GUM, on the statistical description of the accuracy of whole ranges of indirect multivariable measurement system. Formula for the covariance matrix of relative uncertainties of the vector measurand is given. The covariance matrixes of uncertainties of few DC electrical measurement circuits are presented, i.e.: for indirect measurement of three resistances with using them in three variants of balanced Wheatstone bridge or without disconnection this circuit but with apply unconventional current supplies; the measurement of three internal resistances of the star circuit from its terminals and estimation of uncertainty of powers of two currents if two other currents are measured and their uncertainties are known. Formulas for absolute and relative uncertainties and their correlation coefficients are given. The general conclusion is that in the description accuracy of multivariable measurement systems the relative uncertainties are sometimes preferable than the absolute ones, and uncertainties of their main measurement functions have been also considered.
2019 12th International Conference on Measurement, 2019
The paper presents an upgraded version of the vector method of evaluation of multiparameter measu... more The paper presents an upgraded version of the vector method of evaluation of multiparameter measurement uncertainties stated in the Supplement 2 to GUM guide. This was done on the example of two-parameter jointed measurements. It consists of the correlation of individual components of the type A and/or type B uncertainty of input measurands. The general formulas for the covariance matrix, final uncertainties, and correlation coefficient were determined. The 3D graph shows the correlation coefficients of the output quantities as a function of the type B contributions in the uncertainty of two input quantities. It has been demonstrated that the inclusion of correlations of uncertainty components makes the uncertainty evaluations more reliable and accurate.
Pomiary Automatyka Robotyka, 2020
Pomiary Automatyka Robotyka, 2019
Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.... more Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.0 1. Wprowadzenie W 1993 r. w międzynarodowym przewodniku wyznaczania niepewności pomiarów o angielskim akronimie GUM [1] wprowadzono nowe pojęcie "niepewność" do oceny dokładności pomiarów. Pojawiła się wówczas niejednolitość z dotychczas stosowanym opisem dokładności przyrządów, urządzeń i systemów pomiarowych przez błędy pomiarowe. Producenci aparatury pomiarowej podają nadal maksymalny dopuszczalny błąd przyrządu MPE (ang. maximum permissible error) [3]. Przy założeniu równomiernego rozkładu odchy
Pomiary Automatyka Robotyka, 2019
Pomiary Automatyka Robotyka, 2018
Pomiary Automatyka Robotyka, 2018