Development of a universal diagnostic system for stator winding faults of induction motor and PMSM based on transfer learning

Simple item record

Full item record

dc.contributor.authorSkowron, Maciej
dc.contributor.editorSkowron, Maciej
dc.contributor.organizationPolitechnika Wrocławskaen
dc.date.accessioned2024-04-05T07:16:20Z
dc.date.available2024-04-05T07:16:20Z
dc.date.issued2023-10-09
dc.description.abstractThis paper deals with the possibility of using transfer learning (TL) of a deep convolutional network (CNN) to develop a universal stator winding fault diagnostic system for the induction motor (IM) and the permanent magnet synchronous motor (PMSM). The proposed diagnostic system uses direct processing of phase current signals to detect and evaluate the degree of stator damage. The TL idea was based on using the CNN structure pre-trained for the IM diagnostic system in a diagnostic application dedicated to IM and PMSM. Experimental verification carried out on real objects confirmed very high precision of steady-state and transient damage detection and classification for both IM and PMSM. Furthermore, the detection time shown in the study for both types of machines did not exceed 0.07 seconds.en
dc.description.sponsorshipNational Science Centre Poland
dc.identifier.citationM. Skowron, "Development of a universal diagnostic system for stator winding faults of induction motor and PMSM based on transfer learning," 2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), Chania, Greece, 2023, pp. 517-523, doi: 10.1109/SDEMPED54949.2023.10271444.en
dc.identifier.isbn979-8-3503-2077-0
dc.identifier.urihttps://open.icm.edu.pl/handle/123456789/24139
dc.language.isoen
dc.publisherIEEEen
dc.relation2021/41/N/ST7/01673en
dc.rightsUznanie autorstwa 4.0 Międzynarodowe*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectfault diagnosticsen
dc.subjectPMSMen
dc.subjectinduction motorsen
dc.subjectconvolutional neural networksen
dc.subjecttransfer learningen
dc.titleDevelopment of a universal diagnostic system for stator winding faults of induction motor and PMSM based on transfer learningen
dc.typeconferencePaperen
Files for this record
Original bundle
Now showing 1 - 1 of 1
Name: Development_of_a_universal_diagnostic_system_for_stator_winding_faults_of_induction_motor_and_PMSM_based_on_transfer_learning.pdf
Size: 1.79 MB
Format: Adobe Portable Document Format
Description: Referat konferencyjny
Download
License files
Name: license.txt
Size: 233 B
Format: Plain Text
Description:
Download
Belongs to collection
Materiały konferencyjne / Conference papers