Issues associated with automating the calibration of standard DC voltage measuring instruments are considered. An automatic calibration system is developed, studied, and implemented. This system comprises a hardware and software system containing measuring instruments from the National Standard of Voltage Unit -Volt and additional modules. The automatic system is created on the basis of the Python programming language using metrological principles. The studied calibration results of DC voltage standards, i.e., the obtained calibration results (assigned actual value with expanded uncertainty) are analyzed in automatic and manual modes, as well as using the 10 V Josephson voltage standard known as supraVOLTcontrol. As well as signifi cantly reducing labor costs, the application of this automatic system to study the integral instability (nonlinearity) of a digital voltmeter allows measurement duration to be reduced, as well as providing fl exibility and reconfi guration capability depending on issues that emerge during research.
Considered options for automating the calibration. An automatic calibration system has been developed, investigated and introduced into the production process, which is a software and hardware complex consisting of measuring instruments from the composition of the National standard of voltage unit – volt and additional modules. The automatic system was created on the basis of the modern programming language “Python” with the involvement of the experience of metrologists. A study of the results of calibration of reference voltage measures was carried out: the obtained results of the calibration of the DC voltage (assigned real value with expanded uncertainty) were analyzed in automatic and manual modes and using the “supraVOLTcontrol” system, which implements the Josephson effect. The automatic system was used in the study of the integral instability (nonlinearity) of a digital voltmeter, while a significant minimization of labor costs was obtained. The developed automatic calibration system allows to reduce labor intensity and duration of measurements, provides flexibility and ability to rebuild depending on emerging issues during research.
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