Application of optimization methods for improved electrical metrology

In electrical quantities metrology numerous examples of stochastic processes exist and a need for optimal solutions is posed. Here stochastic genetic algorithm optimization is used for solving two typical metrological problems: 1) minimization of the metrological parameters (final accuracy) in the design process of instruments and 2) predicting metrological reference standard’s time-drift, i.e. re-calibration interval. The first case is the optimal metrological design of a combined instrument transformer and the second case is the analysis of resistance standard time-drift.