This paper describes the failure detection system of an electro-hydraulic actuator with dual modular redundancy based on a hybrid twin TM concept. Hybrid twin TM is a combination of virtual twin that operates in parallel with the actuator and represents its ideal behaviour, and a digital twin that identifies possible failures using the sensor readings residuals. Simulation-based system reliability analysis helps to generate a dataset for training the digital twin using machine learning algorithms. A systematic failure detection approach based on decision trees and the process of analysing the quality of the result is described.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:71268 |
| Date | 26 June 2020 |
| Creators | Andreev, Maxim, Kolesnikov, Artem, Grätz, Uwe, Gundermann, Julia |
| 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 | 10.25368/2020.8, urn:nbn:de:bsz:14-qucosa2-709188, qucosa:70918 |
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