A method based on random-fuzzy variables for online estimation of the measurement uncertainty of DSP-based instruments

The evaluation of the uncertainty of the result of a measurement performed by a DSP-based instrument is usually a complex and difficult task. The sources of uncertainty are the instrument input stage and the analog-to-digital converter (ADC), so that each input sample to the instrument can be considered a measurement result with its associated uncertainty. The uncertainty on the final measurement result is obtained as the combination of the uncertainty values of each sample, according to the measurement algorithm implemented on the digital signal processing (DSP) system. This paper proposes an innovative approach, based on the representation of the measurement result and its associated uncertainty in terms of random-fuzzy variables, that, after having suitably characterized the metrological performance of the input stage and analog-to-digital converter, provides an online estimation of the measurement uncertainty. The method has been validated experimentally, and the results of the experimental work are reported.