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Abstract

The paper addresses the problem of experimental studies of miniature tilt sensors based on low-range accelerometers belonging to Microelectromechanical Systems (MEMS). A custom computer controlled test rig is proposed, whose kinematics allows an arbitrary tilt angle to be applied (i.e. its two components: pitch and roll over the full angular range). The related geometrical relationships are presented along with the respective uncertainties resulting from their application. Metrological features of the test rig are carefully evaluated and briefly discussed. Accuracy of the test rig is expressed in terms of the respective uncertainties, as recommended by ISO; its scope of application as well as the related limitations are indicated. Even though the test rig is mostly composed of standard devices, like rotation stages and incremental angle encoder, its performance can be compared with specialized certified machines that are very expensive. Exemplary results of experimental studies of MEMS accelerometers realized by means of the test rig are presented and briefly discussed. Few ways of improving performance of the test rig are proposed.
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Abstract

Prior knowledge of the autocorrelation function (ACF) enables an application of analytical formalism for the unbiased estimators of variance s2a and variance of the mean s2a(xmacr;). Both can be expressed with the use of so-called effective number of observations neff. We show how to adopt this formalism if only an estimate {rk} of the ACF derived from a sample is available. A novel method is introduced based on truncation of the {rk} function at the point of its first transit through zero (FTZ). It can be applied to non-negative ACFs with a correlation range smaller than the sample size. Contrary to the other methods described in literature, the FTZ method assures the finite range 1 < neff ≤ n for any data. The effect of replacement of the standard estimator of the ACF by three alternative estimators is also investigated. Monte Carlo simulations, concerning the bias and dispersion of resulting estimators sa and sa(×), suggest that the presented formalism can be effectively used to determine a measurement uncertainty. The described method is illustrated with the exemplary analysis of autocorrelated variations of the intensity of an X-ray beam diffracted from a powder sample, known as the particle statistics effect.
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Abstract

Determination of the phase difference between two sinusoidal signals with noise components using samples of these signals is of interest in many measurement systems. The samples of signals are processed by one of many algorithms, such as 7PSF, UQDE and MSAL, to determine the phase difference. The phase difference result must be accompanied with estimation of the measurement uncertainty. The following issues are covered in this paper: the MSAL algorithm background, the ways of treating the bias influence on the phase difference result, comparison of results obtained by applying MSAL and the other mentioned algorithms to the same real signal samples, and evaluation of the uncertainty of the phase difference.
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Abstract

It is now widely recognized that the evaluation of the uncertainty associated with a result is an essential part of any quantitative analysis. One way to use the estimation of measurement uncertainty as a metrological critical evaluation tool is the identification of sources of uncertainty on the analytical result, knowing the weak steps, in order to improve the method, when it is necessary. In this work, this methodology is applied to fuel analyses and the results show that the relevant sources of uncertainty are: beyond the repeatability, the resolution of the volumetric glassware and the blank in the analytical curve that are little studied.
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