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Projekt: Feldetektering i elektriska maskiner
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Boliden, Sverige.
2013 (Swedish)Other (Other (popular science, discussion, etc.))
Abstract [sv]

Syftet med projektet är att utveckla och experimentellt utvärdera nya algoritmer för att upptäcka och isolera fel i elmotorer.

Place, publisher, year, edition, pages
2013.
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-36320Local ID: f9a6ceda-8f7e-4f12-a671-d69cb8df6966OAI: oai:DiVA.org:ltu-36320DiVA: diva2:1009579
Note

Publikationer: Broken Bars Fault Diagnosis Based on Uncertainty Bounds Violation for Three Phase Induction Motors; Principal component analysis of the start-up transient and hidden Markov modeling for broken rotor bar fault diagnosis in asynchronous machines; Fault classification scheme for three phase induction motor; A fault diagnosis scheme for three phase induction motors based on uncertainty bounds; Fault detection based on set membership identification for three phase induction motors; A Robust Linear Discrimination Fault Classification Scheme for Three Phase Induction Motors; Faults detection and diagnosis for three phase induction machines; Broken bar fault detection based on set membership identification for three phase induction motors; Broken rotor bar fault detection based on uncertainty ellipsoidal intersection for three phase induction motors; Experimental evaluation of a broken rotor bar fault detection scheme based on uncertainty bounds violation; Detecting broken rotor bars in induction motors with model-based support vector classifiers; Status: Pågående; Period: 01/06/2011 → …

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2016-10-03Bibliographically approved

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