Artificial Intelligence-Based Condition Monitoring and Predictive Maintenance of Medium Voltage Cables: An Integrated System Development Approach
Approved
Classifications
MinEdu publication type
A4 Article in conference proceedings (peer-reviewed)
Definition
Article
Target group
Scientific
Peer reviewed
Peer-reviewed
Article type
Other article
Host publication type
Conference platform
Publication channel information
Title of host publication
2024 10th International Conference on Condition Monitoring and Diagnosis (CMD)
ISBN (print)
979-8-3503-5387-7
ISBN (electronic)
978-8-9865-1022-5
Name of conference
International Conference on Condition Monitoring and Diagnosis (CMD)
Title of journal/series
IEEE International conference on condition monitoring and diagnosis
ISSN (print)
2374-0167
ISSN (electronic)
2644-271X
ISSN (linking)
2374-0167
Publisher
IEEE
Publication forum ID
91121
Publication forum level
1
Publication appears in FT-list
No
Country of publication
United States
Internationality
Yes
Detailed publication information
Publication year
2024
Reporting year
2024
Page numbers
191-195
DOI
10.23919/cmd62064.2024.10766104
Language of publication
English
Co-publication information
International co-publication
Yes
Co-publication with a company
No
Availability
Link to online publication
Link to self-archived version
Classification and additional information
MinEdu field of science classification
213 Electronic, automation and communications engineering, electronics
Keywords
MV cable; condition monitoring; AI; big data platform; maintenance strategies
Funding information
Funding information in the publication
This work has been done as a part of “Smart Grid 2.0”-project funded by Business Finland with grant No. 1386/31/2022. The first author acknowledges Fortum and Neste Foundation for providing grant (grant reference No. 20220101) for this research work.
Funders
Funder
Business Finland
Name of funding
-
Funding decision
-
Source database ID
Scopus ID
2-s2.0-85214383898