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Details van artikel 51 van 129 gevonden artikelen
| Titel: |
Diagnosing batch processes with insufficient fault data: generation of pseudo batches |
| Auteur: |
Cho, H. -W. Kim, K. -J. |
| Verschenen in: |
International journal of production research |
| Paginering: | Jaargang 43 (2005) nr. 14 pagina's 2997-3009 |
| Jaar: |
2005-07-15 |
| Inhoud: |
To ensure the safety of a batch process and the quality of its final product, one needs to quickly identify an assignable cause of a fault. Cho and Kim (2003) recently proposed a diagnosis method for batch processes using Fisher's Discriminant Analysis (FDA), which showed a satisfactory performance on industrial batch processes. However, their method (or any other method based on empirical models) has a major limitation when the fault batches available for building an empirical diagnosis model are insufficient. This is a highly critical issue in practice because sufficient fault batches are likely to be unavailable. In this work, we propose a method to handle the insufficiency of the fault data in diagnosing batch processes. The basic idea is to generate so-called pseudo batches from known fault batches and utilise them as part of the diagnosis model data. The performance of the proposed method is demonstrated using a real data set from a PVC batch process. The proposed method is shown to be capable of handling the data insufficiency problem successfully, and yields a reliable diagnosis performance. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 51 van 129 gevonden artikelen
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