A novel process control method for remote calibration based on improved multiscale permutation entropy and dynamic Hotelling's T^2 control chart.

Remote calibration (RC) is a new promising technology for electric power instrument calibration. However, due to the inevitable impact of external environmental changes and internal insulation aging during the transportation, installation, and measurement processes involved in RC, the metrological performance of relevant instruments may deteriorate. Therefore, quality control of electric power instruments during RC is of great significance. In this paper, a novel process control method for RC is proposed. First, from the physical characteristic perspective, an improved multiscale permutation entropy (IMPE) algorithm is designed to detect the complexity change point of the instrument system. Second, from the statistical characteristic perspective, a dynamic multivariable Hotelling's T 2 control chart (DMHTCC) is developed to detect the outliers within a time series measurement signal. Finally, a fusion scheme of IMPE and DMHTCC is presented to promote the validity and reliability of process control. The effectiveness of the proposed approach and its superiority over some traditional process control techniques is demonstrated through both simulative and experimental case studies.