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- W2372788581 abstract "Multiblock kernel principal component analysis (MBKPCA) has been proposed to isolate the faults and avoid the high computation cost. However, MBKPCA is not available for dynamic processes. To solve this problem, recursive MBKPCA is proposed for monitoring large scale processes. In this paper, we present a new recursive MBKPCA (RMBKPCA) algorithm, where the adaptive technique is adopted for dynamic characteristics. The proposed algorithm reduces the high computation cost, and is suitable for online model updating in the feature space. The proposed algorithm was applied to an industrial process for adaptive monitoring and found to efficiently capture the time-varying and nonlinear relationship in the process variables." @default.
- W2372788581 created "2016-06-24" @default.
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- W2372788581 date "2010-01-01" @default.
- W2372788581 modified "2023-09-23" @default.
- W2372788581 title "Adaptive multiblock kernel principal component analysis for monitoring complex industrial processes" @default.
- W2372788581 hasPublicationYear "2010" @default.
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