[2003. 01. 24.] 박사과정 조현우, INFORMS 학회 발표
작성자
quality
작성일
2020-02-16 00:42
조회
1507
Cho, H. and Kim, K., “Fault Diagnosis of Batch Processes: A New Statistical Approach Using Discriminant Model,” INFORMS Annual Meeting, San Jose, California, November 17-20, 2002.
<요약문>
A new statistical diagnosis method for a batch process is proposed. The proposed method consists of two phases: off-line model building and on-line diagnosis. The off-line model building phase constructs an empirical model, called a discriminant model, using various past batch runs. When an out-of-control state of a new batch is detected, the on-line diagnosis phase is initiated. The behavior of the new batch is referenced against the model, developed in the off-line model building phase, to make a diagnostic decision. The diagnosis performance of the proposed method is tested using a dataset from a PVC batch process. It has been shown that the proposed method outperforms existing PCA-based diagnosis methods, especially at the onset of a fault.
<요약문>
A new statistical diagnosis method for a batch process is proposed. The proposed method consists of two phases: off-line model building and on-line diagnosis. The off-line model building phase constructs an empirical model, called a discriminant model, using various past batch runs. When an out-of-control state of a new batch is detected, the on-line diagnosis phase is initiated. The behavior of the new batch is referenced against the model, developed in the off-line model building phase, to make a diagnostic decision. The diagnosis performance of the proposed method is tested using a dataset from a PVC batch process. It has been shown that the proposed method outperforms existing PCA-based diagnosis methods, especially at the onset of a fault.
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