Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis
Joint Authors
Li, Xiangshun
Wei, Di
Lei, Cheng
Li, Zhiang
Wang, Wenlin
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-30
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Independent Component Analysis (ICA), a type of typical data-driven fault detection techniques, has been widely applied for monitoring industrial processes.
FastICA is a classical algorithm of ICA, which extracts independent components by using the Newton iteration method.
However, the choice of the initial iterative point of Newton iteration method is difficult; sometimes, selection of different initial iterative points tends to show completely different effects for fault detection.
So far, there is still no good strategy to get an ideal initial iterative point for ICA.
To solve this problem, a modified ICA algorithm based on biogeography-based optimization (BBO) called BBO-ICA is proposed for the purpose of multivariate statistical process monitoring.
The Newton iteration method is replaced with BBO here for extracting independent components.
BBO is a novel and effective optimization method to search extremes or maximums.
Comparing with the traditional intelligent optimization algorithm of particle swarm optimization (PSO) and so on, BBO behaves with stronger capability and accuracy of searching for solution space.
Moreover, numerical simulations are finished with the platform of DAMADICS.
Results demonstrate the practicability and effectiveness of BBO-ICA.
The proposed BBO-ICA shows better performance of process monitoring than FastICA and PSO-ICA for DAMADICS.
American Psychological Association (APA)
Li, Xiangshun& Wei, Di& Lei, Cheng& Li, Zhiang& Wang, Wenlin. 2018. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
Modern Language Association (MLA)
Li, Xiangshun…[et al.]. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
American Medical Association (AMA)
Li, Xiangshun& Wei, Di& Lei, Cheng& Li, Zhiang& Wang, Wenlin. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205789