Publication:

Unsupervised Transfer Learning Across Different Data Modalities for Bearing's Speed Identification

Date

2024
Journal article
https://doi.org/10.20855/ijav.2024.29.22046
Simple item page Full metadata Statistics
 
dc.contributor.authorNieves Avendano, Diego
dc.contributor.authorDeschrijver, Dirk
dc.contributor.authorVan Hoecke, Sofie
dc.contributor.imecauthorDeschrijver, Dirk
dc.contributor.imecauthorVan Hoecke, Sofie
dc.contributor.imecauthorNieves Avendano, Diego
dc.contributor.orcidimecDeschrijver, Dirk::0000-0001-6600-1792
dc.contributor.orcidimecVan Hoecke, Sofie::0000-0002-7865-6793
dc.contributor.orcidimecNieves Avendano, Diego::0000-0001-6215-6439
dc.date.accessioned2025-08-25T06:59:23Z
dc.date.available2024-07-11T18:26:47Z
dc.date.available2024-07-31T10:23:15Z
dc.date.available2025-08-25T06:59:23Z
dc.date.embargo2024-12-31
dc.date.issued2024
dc.description.wosFundingTextThe authors would like to thank Bram Robberechts for per- forming the tests within the Smart Maintenance Living Lab project. The photos shown in Figure 3 and Figure 4 belong to the SMLL dataset. The authors thank Flanders Make for allowing the photos to be included. This work was supported by the Flemish Government under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" programme and the VLAIO subsidies for research.
dc.identifier.doi10.20855/ijav.2024.29.22046
dc.identifier.issn1027-5851
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44142
dc.publisherINT INST ACOUSTICS & VIBRATION
dc.source.beginpage175
dc.source.endpage186
dc.source.issue2
dc.source.journalINTERNATIONAL JOURNAL OF ACOUSTICS AND VIBRATION
dc.source.numberofpages12
dc.source.volume29
dc.subject.keywordsCONVOLUTION NEURAL-NETWORK
dc.subject.keywordsRESIDUAL LIFE
dc.subject.keywordsFAULT
dc.subject.keywordsPREDICTIONS
dc.subject.keywordsDIAGNOSTICS
dc.title

Unsupervised Transfer Learning Across Different Data Modalities for Bearing's Speed Identification

dc.typeJournal article
dspace.entity.typePublication
Files

Original bundle

Name:
DS780.pdf
Size:
4.69 MB
Format:
Unknown data format
Description:
Published version
Download
Name:
DS780_acc.pdf
Size:
4.6 MB
Format:
Unknown data format
Description:
Accepted version
Download
Publication available in collections:
Articles