Investigation of the Method of RMS Measurement Based on Moving Averaging

Currently, the measurement method of root mean square value (RMS), based on samples accumulation, is the most popular. The advantages of this method include ease of implementation, high accuracy and additional opportunities to reduce the methodological component of the total measurement error. Studies show that increasing measurement time also contributes to a reduction in error. However, in a number of measurement and automatic control problems, one of the main requirements is to reduce the measurement time. This problem can be solved by a method based on moving averaging, that includes the advantages of the "classical" method, but is largely devoid of its shortcomings. An algorithm of RMS measurement for implementation on the basis of recursive and non-recursive moving average filters is proposed. The influence of the sinusoidal signal parameters on the RMS measurement error is analyzed. An analytical expression is obtained that allows to estimate the RMS measurement error from the signal parameters and the number of samples. Approaches are proposed for reducing the RMS measurement error when applying the measurement method under consideration. It is shown that the application of post-filtration of RMS measurement results can reduce the final RMS measurement error. The veracity of the analytical expressions obtained in the paper is confirmed by the results of simulation at check points.