Distillation Column: Review of Major Disturbances

Taqvi, Syed Ali Ammar; Zabiri, Haslinda; Tufa, Lemma Dendena; Fatima, Syeda Anmol; Maulud, Abdul Halim Shah

doi:10.1109/iccsce47578.2019.9068539

2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) 2019

DOI: 10.1109/iccsce47578.2019.9068539

|View full text |Cite

Distillation Column: Review of Major Disturbances

Syed Ali Ammar Taqvi

Haslinda Zabiri²,

Lemma Dendena Tufa

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2020

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Narx Network Based Data-Driven Algorithm for Detection of Tray Faults in Nonlinear Dynamic Distillation Column

Taqvi

Zabiri

Tufa³

et al. 2020

Jurnal Teknologi

View full text Add to dashboard Cite

Efficient monitoring of highly complex process industries is essential for better management, safer operations and high-quality production. Timely detection of various faults helps to improve the performance of the complex industries, prevent various unfavorable consequences and reduce the maintenance cost. Fault Detection and Diagnosis (FDD) for process monitoring and control has been an active field of research for the past two decades. Distillation columns are inherently nonlinear, and thus to have an accurate and robust performance, the fault detection methods should be based on nonlinear dynamic methods. The paper presents a robust data-driven fault detection approach for realistic tray upsets in the distillation column. The detection of tray faults in the distillation column is conducted by Nonlinear AutoRegressive with eXogenous Input (NARX) network with Tapped Delay Lines (TDL). Aspen Plus® Dynamic simulation has been used to generate normal and faulty datasets. The study shows that the proposed method can be used for the detection of tray faults in distillation column for dynamic process monitoring. The performance of the proposed method has been evaluated by the Missed Detection Rate (MDR) and the Detection Delay (DD).

show abstract

Narx Network Based Data-Driven Algorithm for Detection of Tray Faults in Nonlinear Dynamic Distillation Column

Taqvi

Zabiri

Tufa³

et al. 2020

Jurnal Teknologi

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Distillation Column: Review of Major Disturbances

Cited by 1 publication

References 16 publications

Narx Network Based Data-Driven Algorithm for Detection of Tray Faults in Nonlinear Dynamic Distillation Column

Narx Network Based Data-Driven Algorithm for Detection of Tray Faults in Nonlinear Dynamic Distillation Column

Contact Info

Product

Resources

About