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dc.contributor.authorSaucedo Dorantes, Juan Jose
dc.contributor.authorOsornio Rios, Roque A.
dc.contributor.authorDelgado Prieto, Miquel
dc.contributor.authorRomero Troncoso, René de Jesús
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2018-07-30T10:01:11Z
dc.date.issued2017
dc.identifier.citationSaucedo, J., Osornio, R., Delgado Prieto, M., Romero-Troncoso, R. Diagnosis Methodology Based on Statistical-time Features and Linear Discriminant Analysis Applied to Induction Motors. A: IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives. "2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED 2017)". 2017, p. 517-523.
dc.identifier.isbn9781509004102
dc.identifier.otherhttps://ieeexplore-ieee-org.recursos.biblioteca.upc.edu/document/8062404/
dc.identifier.urihttp://hdl.handle.net/2117/120232
dc.description.abstractThe development of condition monitoring strategies is necessary to ensure the efficiency and reliability of the operation on electric machines. The feature calculation is an important signal processing step used to obtain a characterization related to the working condition of machinery. In order to address this issue, this work proposes a diagnosis methodology based on the calculation of a statistical-time set of features applied to identify the appearance of different faults in an induction motor. In the proposed methodology three acquired stator current signals are characterized by calculating its statistical-time features. Then, such statistical-time sets of features are compressed and represented into a 2-dimentional space through Linear Discriminant Analysis. And, finally a Neuro Fuzzy- based classifier is used to diagnose the different considered conditions. The performance of the proposed diagnosis methodology is evaluated in an experimental test bench; the obtained results make the proposed methodology suitable to be applied in industrial processes.
dc.format.extent7 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
dc.subject.lcshSignal processing
dc.subject.lcshRotors
dc.subject.lcshElectric motors, Induction
dc.subject.otherInduction Motors
dc.subject.otherCondition Monitoring
dc.subject.otherFault Diagnosis
dc.subject.otherTime-domain analysis
dc.subject.otherLinear Discriminant Analysis
dc.subject.otherCurrent Measurement
dc.titleDiagnosis Methodology Based on Statistical-time Features and Linear Discriminant Analysis Applied to Induction Motors
dc.typeConference report
dc.subject.lemacTractament del senyal
dc.subject.lemacRotors
dc.subject.lemacMotors elèctrics d'inducció
dc.contributor.groupUniversitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
dc.identifier.doi10.1109/DEMPED.2017.8062404
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac23242615
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorSaucedo, J.; Osornio, R.; Delgado Prieto, M.; Romero-Troncoso, R.
local.citation.contributorIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
local.citation.publicationName2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED 2017)
local.citation.startingPage517
local.citation.endingPage523


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