Dynamic Decentralized Monitoring for Large-Scale Industrial Processes Using Multiblock Canonical Variate Analysis Based Regression
Author:
Affiliation:
1. Department of System Engineering and Automatic Control, School of Industrial Engineering, Universidad de Valladolid, Valladolid, Spain
Funder
Spanish Government through the Ministerio de Ciencia e Innovación (MICINN) / Agencia Estatal de Investigación
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10068246.pdf?arnumber=10068246
Reference42 articles.
1. Integrate weighted dependence and skewness based multiblock principal component analysis with Bayesian inference for large-scale process monitoring
2. A Novel Decentralized Process Monitoring Scheme Using a Modified Multiblock PCA Algorithm
3. Decentralized fault detection and diagnosis via sparse PCA based decomposition and Maximum Entropy decision fusion
4. Decentralized Monitoring of Dynamic Processes Based on Dynamic Feature Selection and Informative Fault Pattern Dissimilarity
5. Canonical variate analysis-based contributions for fault identification
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