A geometric framework for monitoring and fault detection for periodic processes. Issue 7 (2nd February 2017)

• Record Type: Journal Article
• Authors: Wang, Ray; Edgar, Thomas F.; Baldea, Michael
• Is Part Of: AIChE journal. Volume 63:Issue 7(2017)
• Page Start: 2719
• Page End: 2730
• Publication Date: 2017-02-02
• Subjects: periodic processes -- process monitoring -- data visualization -- fault detection -- cyclical processes; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.15638
• Languages: English
• ISSNs: 0001-1541

Abstract

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