Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach
He, B, Yang, X, Chen, T and Zhang, J (2012) Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach Journal of Process Control, 22 (7). pp. 1228-1236.
Available under License : See the attached licence file.
Identification of faulty variables is an important component of multivariate statistical process monitoring (MSPM); it provides crucial information for further analysis of the root cause of the detected fault. The main challenge is the large number of combinations of process variables under consideration, usually resulting in a combinatorial optimization problem. This paper develops a generic reconstruction based multivariate contribution analysis (RBMCA) framework to identify the variables that are the most responsible for the fault. A branch and bound (BAB) algorithm is proposed to efficiently solve the combinatorial optimization problem. The formulation of the RBMCA does not depend on a specific model, which allows it to be applicable to any MSPM model. We demonstrate the application of the RBMCA to a specific model: the mixture of probabilistic principal component analysis (PPCA mixture) model. Finally, we illustrate the effectiveness and computational efficiency of the proposed methodology through a numerical example and the benchmark simulation of the Tennessee Eastman process. © 2012 Elsevier Ltd. All rights reserved.
|Divisions :||Faculty of Engineering and Physical Sciences > Chemical and Process Engineering|
|Date :||August 2012|
|Identification Number :||https://doi.org/10.1016/j.jprocont.2012.05.010|
|Additional Information :||NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Process Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Process Control, 22(7), August 2012, DOI 10.1016/j.jprocont.2012.05.010.|
|Depositing User :||Symplectic Elements|
|Date Deposited :||17 May 2013 17:26|
|Last Modified :||23 Sep 2013 20:07|
Actions (login required)
Downloads per month over past year