Optimizing calibration interval of measuring instrument dynamically based on grey Markov forecasting model

According to the character of calibration parameters, a data-preprocessed statistical models for forecasting the calibration trends of measuring instrument is proposed. The solution of the statistical models is got by the merits combination of both gray forecast and Markov forecast, a grey system model is used to forecast the general trend of the calibration status, and a time series Markov chain model is used to forecast data's fluctuant changing along the general trend. The calibration interval is optimized according to the forecast trends. A preliminary validation of the models is provided based on a collected sample of experimental data. Results demonstrate that the model can well and truly forecast the evolvement and changing trends of the calibration status, the optical calibration interval improved the problem of insufficient calibration and superfluous calibration.