One step forward for smart chemical process fault detection and diagnosis

•The definition and characteristics of smart fault detection and diagnosis are elaborated.•The four major challenges to implementing smart fault detection and diagnosis are addressed.•Recent advances related to smart fault detection and diagnosis are systematically reviewed.•A general outlook on the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computers & chemical engineering 2022-08, Vol.164, p.107884, Article 107884
Hauptverfasser: Bi, Xiaotian, Qin, Ruoshi, Wu, Deyang, Zheng, Shaodong, Zhao, Jinsong
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•The definition and characteristics of smart fault detection and diagnosis are elaborated.•The four major challenges to implementing smart fault detection and diagnosis are addressed.•Recent advances related to smart fault detection and diagnosis are systematically reviewed.•A general outlook on the future of process safety is discussed. Process fault detection and diagnosis (FDD) is an essential tool to ensure safe production in chemical industries. After decades of development, despite the promising performance of some FDD methods on specific tasks, most FDD methods are not smart enough to tackle the complex challenges in real industrial processes, rendering an absence of commercialized FDD tools. Therefore, the implementation of smart FDD becomes an ambitious goal for process safety. In this paper, we provide an overview of the concept and major challenges of smart FDD. Recent FDD methods are comprehensively evaluated with respect to the characteristics of smart FDD. We also present the researches done by our group, which we believe would be a step forward for smart FDD. A range of future opportunities and new perspectives are further discussed. This review aims to illuminate potential directions for process safety and to contribute to the realization of commercial FDD tools.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2022.107884