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- W2006209546 abstract "To ensure safety of a batch process and quality of its final product, one needs to quickly identify an assignable cause of a fault. To solve the diagnosis problem of a batch process, Cho and Kim 6 proposed a new statistical diagnosis method based on Fisher discriminant analysis (FDA). They showed satisfactory diagnosis performance on industrial batch processes. However, the diagnosis method of Cho and Kim 6 has a major limitation: it does not work when the fault data available for building the discriminant model are insufficient. In this work, we propose a method to handle the insufficiency of the fault data in diagnosing batch processes. The diagnosis performance of the proposed method is demonstrated using a data set from a PVC batch process. The proposed method is shown to be able to handle the data insufficiency problem, and yield reliable diagnosis performance." @default.
- W2006209546 created "2016-06-24" @default.
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- W2006209546 date "2003-06-01" @default.
- W2006209546 modified "2023-09-27" @default.
- W2006209546 title "Handling Data Insufficiency Problem in Diagnosing Batch Processes" @default.
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- W2006209546 doi "https://doi.org/10.1142/s021853930300107x" @default.
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