Abstract
Abstract Due to higher demands on product diversity, flexible shift between productions of different products in one equipment becomes a popular solution, resulting in existence of multiple operation modes in a single process. In order to handle such multi-mode process, a novel double-layer structure is proposed and the original data are decomposed into common and specific characteristics according to the relationship between variables among each mode. In addition, both low and high order information are considered in each layer. The common and specific information within each mode can be captured and separated into several subspaces according to the different order information. The performance of the proposed method is further validated through a numerical example and the Tennessee Eastman (TE) benchmark. Compared with previous methods, superiority of the proposed method is validated by the better monitoring results.
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