LAPSE:2023.17489
Published Article
LAPSE:2023.17489
Methods of Condition Monitoring and Fault Detection for Electrical Machines
March 6, 2023
Nowadays, electrical machines and drive systems are playing an essential role in different applications. Eventually, various failures occur in long-term continuous operation. Due to the increased influence of such devices on industry, industrial branches, as well as ordinary human life, condition monitoring and timely fault diagnostics have gained a reasonable importance. In this review article, there are studied different diagnostic techniques that can be used for algorithms’ training and realization of predictive maintenance. Benefits and drawbacks of intelligent diagnostic techniques are highlighted. The most widespread faults of electrical machines are discussed as well as techniques for parameters’ monitoring are introduced.
Record ID
Keywords
Artificial Intelligence, condition monitoring, failure detection, fault diagnosis, fuzzy logic, Machine Learning, neural networks, reliability
Subject
Suggested Citation
Kudelina K, Asad B, Vaimann T, Rassõlkin A, Kallaste A, Khang HV. Methods of Condition Monitoring and Fault Detection for Electrical Machines. (2023). LAPSE:2023.17489
Author Affiliations
Kudelina K: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Asad B: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Vaimann T: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Rassõlkin A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Kallaste A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Khang HV: Department of Engineering Sciences, University of Agder, 4604 Kristiansand, Norway [ORCID]
Asad B: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Vaimann T: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Rassõlkin A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Kallaste A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Khang HV: Department of Engineering Sciences, University of Agder, 4604 Kristiansand, Norway [ORCID]
Journal Name
Energies
Volume
14
Issue
22
First Page
7459
Year
2021
Publication Date
2021-11-09
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14227459, Publication Type: Review
Record Map
Published Article
LAPSE:2023.17489
This Record
External Link
doi:10.3390/en14227459
Publisher Version
Download
Meta
Record Statistics
Record Views
99
Version History
[v1] (Original Submission)
Mar 6, 2023
Verified by curator on
Mar 6, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.17489
Original Submitter
Auto Uploader for LAPSE
Links to Related Works