It is the continuation of a previous paper, in which limitations of uncertainty type A estimation due international guide GUM, are shortly discussed and method of elimination of influence of unknown systematic components: trend and oscillation, are introduced. Below two next proposals of development and upgrading of the method type A are presented, i.e. taking in estimation the influence of autocorrelation of observation resultants and choosing the adequate type of their probability distribution by ?2 criterion, if is different that normal one, are considered. It is illustrated by numerical examples of normal, rectangular and Laplace distribution. Results are compared to parameters calculated by the actual GUM method. Conclusions and background literature are included.

This paper is about the design and the construction of a system for the measurement of the RMS voltage. One or more of these systems can be employed as building blocks for a wide range of applications in the field of electrical metrology. The first implementation demonstrated its functionality and the possibility to reach a stability of the AC voltage measurement in a wide frequency range with an accuracy within 10 parts in 10⁶, limited only by the DC voltage accuracy of the DAC employed.

A credible reconstruction of a continuous two-dimensional earth surface potential distribution from a discrete set of noisy samples is essential for correct identification of regions with high values of touch and step voltages, as a part of grounding grid safety assessment procedure. This research provides some new and useful insights on the earth surface potential distribution reconstruction quality, focused mainly on the most commonly used radial basis function (RBF) interpolation kernels. The RBF approach to reconstruction was chosen because of the underlaying algorithm simplicity and the fact that it provides natural mathematical framework for smooth interpolation and approximation of potential fields from irregular sampling sets. Since the quality of potential distribution reconstruction is heavily influenced by the choice of interpolation method, sampling layout and a priori knowledge of the grounding grid structure under test, this research also elaborates some heuristic guidelines for planning proper sampling procedure and illustrates some examples of reconstructed functional shape distortions due to poor sampling layouts.

The present paper describes a novel application of a well known Build-In-Self-Test (BIST) method in order to evaluate the operational condition of a certain type of sensors which are widely used in environmental monitoring instruments (especially in water quality monitoring). It is actually an automated evaluation procedure of the operating conditions of electrochemical sensors (mainly dissolve oxygen and pH sensors for on-line monitoring of water). Such self-validation procedures increase the operating life and the reliability of a sensor, and extend the time-between calibrations or replacements of chemical consumables (electrolyte). The proposed technique is mostly suitable for stand-alone monitoring systems (such as data-loggers or remote stations) which operate continuously in the field of environmental monitoring of water ecosystems (on-line monitoring). This work uses a microcontroller measuring scheme in order to implement the above functionalities and proposes a measuring circuit (that is also described) which is needed to implement such “intelligent features”.

The present paper sets out an intelligent instrument for a quantitative measurement of air quality, consisting of a some gas sensors, each of them being embedded into a adaptation module, an data processing and acquisition module provided with a microcontroller and a decision making, display and alarm system. An electronic nose composed of a high-sensitivity and low selectivity micro-sensors array, a data measurement, transmittal and normalization system and an intelligent decision making system is presented of an example of a qualitative assessment in air quality monitoring.