Errors in the Sampling Process When the Number of Samples in the Measurement Window Is Small

Sampling process is one of the most important part in acquiring information in a measurement system. This article presents an analysis of the sampling of a measured signal that originally takes place in the time space, when the number of samples in the measurement window interval is small. Sampling errors increase under incoherent sampling conditions when the absolute number of samples decreases and even more when the number of samples per signal period decreases. The analysis shows that the number of samples in the measurement interval has the greatest impact on the error in the evaluation of the signal amplitude. This is true if the duty cycle of the sampling pulse or the aperture time is much shorter than the sampling interval, which is a typical case for sampling systems. To determine the maximum sampling errors, incoherent sampling conditions were used with the frequency component positioned at the midpoint of the two frequency bins. The simulation analysis was also confirmed on a real measurement system. The sampling error decreases inversely proportional to the number of samples considering the basic rectangular window over the observation interval. This behavior can be improved by signal processing with stronger windows, such as RVI windows.