Wetterich, Philipp ; Kuhr, Maximilian M. G. ; Pelz, Peter F. (2024)
Model-Based Condition Monitoring of Modular Process Plants.
In: Processes, 2023, 11 (9)
doi: 10.26083/tuprints-00026446
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
The process industry is confronted with rising demands for flexibility and efficiency. One way to achieve this is modular process plants, which consist of pre-manufactured modules with their own decentralized intelligence. Plants are then composed of these modules as unchangeable building blocks and can be easily re-configured for different products. Condition monitoring of such plants is necessary, but the available solutions are not applicable. The authors of this paper suggest an approach in which model-based symptoms are derived from a few measurements and observers that are based on the manufacturer’s knowledge. The comparisons of redundant observers lead to residuals that are classified to obtain symptoms. These symptoms can be communicated to the plant control and are inputs to an easily adaptable diagnosis. The implementation and validation at a modular mixing plant showcase the feasibility and potential of this approach.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Wetterich, Philipp ; Kuhr, Maximilian M. G. ; Pelz, Peter F. |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Model-Based Condition Monitoring of Modular Process Plants |
| Sprache: | Englisch |
| Publikationsjahr: | 5 Februar 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2023 |
| Ort der Erstveröffentlichung: | Basel |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Processes |
| Jahrgang/Volume einer Zeitschrift: | 11 |
| (Heft-)Nummer: | 9 |
| Kollation: | 15 Seiten |
| DOI: | 10.26083/tuprints-00026446 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/26446 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | The process industry is confronted with rising demands for flexibility and efficiency. One way to achieve this is modular process plants, which consist of pre-manufactured modules with their own decentralized intelligence. Plants are then composed of these modules as unchangeable building blocks and can be easily re-configured for different products. Condition monitoring of such plants is necessary, but the available solutions are not applicable. The authors of this paper suggest an approach in which model-based symptoms are derived from a few measurements and observers that are based on the manufacturer’s knowledge. The comparisons of redundant observers lead to residuals that are classified to obtain symptoms. These symptoms can be communicated to the plant control and are inputs to an easily adaptable diagnosis. The implementation and validation at a modular mixing plant showcase the feasibility and potential of this approach. |
| Freie Schlagworte: | condition monitoring, soft sensors, fault diagnosis, modularization |
| ID-Nummer: | Artikel-ID: 2733 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-264468 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Fluidsystemtechnik (FST) (seit 01.10.2006) |
| Hinterlegungsdatum: | 05 Feb 2024 10:39 |
| Letzte Änderung: | 06 Feb 2024 07:05 |
| PPN: | |
| Zugehörige Links: | |
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| Suche nach Titel in: | TUfind oder in Google |
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- Model-Based Condition Monitoring of Modular Process Plants. (deposited 05 Feb 2024 10:39) [Gegenwärtig angezeigt]
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