A learning algorithm for self-calibration of a voltage calibrator

A proposal is made to either extend the calibration period or reduce the measurement uncertainty of a DC voltage reference module used as a transfer, independent or working standard or as a reference module incorporated within a larger measuring system. An algorithm for self-calibration of a precision voltage calibrator is discussed. The basic concept is that the history of deviations in measured voltage differences during the calibration period can be taken as a learning period for a neural network which can numerically correct particular reference elements later in the working period. Results are obtained by simulation, and evaluated on the basis of real measurement data and simulated input functions. Hardware solutions are discussed.