Addressing Higher Order Serial Correlation in Techniques for Gross Error Detection

Abstract

Serial correlation present in the process measurement data may affect the performance of gross error detection (GED) techniques significantly. It has been our observation that most of the GED techniques assume that the data are not serially correlated. However, serial correlation can occur in measurement data due to delay in the process loop, signal processing elements, and other process phenomena. Performance of GED techniques depends on accurate estimation of variances of measured variables. Serial correlation in measured data increases the variance. Therefore, it is important to eliminate the effect of serial correlation in the measured data. Two approaches are proposed to handle serial correlation, one based on variance correction, and the other on prewhitening of residuals. This paper presents the performance of serial elimination techniques of higher order correlation applied in the measurement test (MT).