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Fault prediction technology is important to avoid serious process failure. This paper is concerned with the fault prediction of dynamic industrial process with incipient faults and proposes a canonical variable trend analysis (CVTA) based fault prediction method. In the proposed method, canonical variate analysis (CVA) algorithm is firstly applied to analyze the process dynamics and extract the uncorrelated...
For batch process fault detection, regular data-driven methods cannot distinguish quality-irrelevant faults from quality-relevant faults. To solve such problem, we propose a multiway multi-subspace canonical variate analysis (MMCVA) method for the batch processes. First, the combination of batch-wise unfolding and variable-wise unfolding is adopted to unfold the three-way process and quality data...
Conventional rotation forest does not consider process dynamics. In order to use process dynamics and nonlinearity for classification, a canonical rotation forest (Canonical RF) is proposed and used for process fault diagnosis. For each time instant, a past vector and a future vector are formed. Canonical variate analysis is used for features extraction to obtain dynamic and uncorrelated features...
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