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Process Fault Detection and Reconstruction by Principal Component Analysis

Lookup NU author(s): Dr Ruosen Qi, Dr Jie ZhangORCiD


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Existing fault reconstruction methods are very effective in dealing with sensor faults not involved in control loops where the fault direction is usually easy to determine. However, implementing fault reconstruction methods for process faults or sensor faults involved with control loops is quite challenging as the fault direction vectors are usually difficult to specify. Process faults usually affect a number of process variables with various extents. This paper introduces a principal component analysis (PCA) based fault reconstruction method for process faults. PCA is used to analyze historical process data with faults to extract fault directions, which are then used for fault reconstruction. The proposed method is demonstrated on a simulated continuous stirred tank reactor.

Publication metadata

Author(s): Qi R, Zhang J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 24th International Conference on Methods and Models in Automation and Robotics (MMAR2019)

Year of Conference: 2019

Pages: 594-599

Online publication date: 14/10/2019

Acceptance date: 20/05/2019

Publisher: IEEE


DOI: 10.1109/MMAR.2019.8864614

Library holdings: Search Newcastle University Library for this item

ISBN: 9781728109343