NDLI: Actuator fault monitoring and fault tolerant control in distillation columns

Content Provider	IEEE Xplore Digital Library
Author	Lawal, S.A. Jie Zhang
Copyright Year	2015
Description	Author affiliation: Sch. of Chem. Eng. & Adv. Mater., Newcastle Univ., Newcastle upon Tyne, UK (Lawal, S.A.; Jie Zhang)
Abstract	This work presents, from a practical viewpoint, an investigation of real-time actuator fault detection, propagation and accommodation in distillation columns. Addressing faults in industrial processes, coupled with the growing demand for higher performance, improved safety and reliability necessitates implementation of alternative control strategies in the events of malfunctions in actuators, sensors and or other system components. This work uses multivariate statistical process monitoring based fault detection and diagnosis techniques employing principal components analysis (PCA) and dynamic PCA for prompt and effective faults detection and isolation. The work also investigates effects of disturbances on fault propagation and detection. Alternative control strategy is then implemented to accommodate the actuator faults upon their identification. Specifically, the reflux and vapour boil-up control strategy used for the distillation column during normal operation is switched to one point control of the more valued composition by utilising the remaining healthy actuator. The proposed approach was implemented on a simulated methanol-water separation column to assess its effectiveness.
Starting Page	1
Ending Page	6
File Size	294296
Page Count	6
File Format	PDF
e-ISBN	9780992680114
DOI	10.1109/IConAC.2015.7313971
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-11
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Chinese Automation and Computing Society in the UK - CACS
Subject Keyword	Fault diagnosis Actuators Fault tolerant controller Fault detection Fault detection and diagnosis Inferential control Sensors Dynamic principal component analysis Distillation column Monitoring Principal component analysis
Content Type	Text
Resource Type	Article

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