A geometric framework for monitoring and fault detection for periodic processes

Abstract

Although cyclical operation systems are relatively widespread in practice (notably in the realm of physical separations, for example, pressure‐swing adsorption and chromatography), the development of specific fault detection mechanisms has received little attention compared to the extensive efforts dedicated to continuous or batch processes. Here, a novel geometric approach for process fault detection is proposed. Specifically, a time‐explicit multivariable representation of data collected from the process, which provides a natural framework for defining “normal” operation and the corresponding confidence regions is developed. On this basis, a two‐step fault detection approach is proposed, based on detecting intercycle variations to locate a faulty cycle, and intracycle changes to determine the exact timing of a fault. The theoretical developments are illustrated with two simulation case studies. © 2017 American Institute of Chemical Engineers AIChE J, 63: 2719–2730, 2017