With increasing digitization, models are more important than ever. Especially their use as soft sensors during operation offers opportunities in cost saving, easy data acquisition and therefore additional functionality of systems. In soft sensor networks there is redundant data acquisition and consequently the occurrence of inconsistent values from different soft sensors is encouraged. The resolution of these data-induced conflicts allows for the detection of changing components characteristics. Hence soft sensor networks can be used to detect wear in system components. In this paper this approach is validated on a test rig. It is found, that the soft sensor network is capable to determine wear and its extent in eccentric screw pumps and valves via data induced conflicts with relatively simple models.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:71201 |
| Date | 25 June 2020 |
| Creators | Hartig, Jakob, Schänzle, Christian, Pelz, Peter F. |
| Contributors | Dresdner Verein zur Förderung der Fluidtechnik e. V. Dresden |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.25368/2020.7, urn:nbn:de:bsz:14-qucosa2-709173, qucosa:70917 |
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