Artificial Intelligence in Monitoring and Diagnostics of Electrical Energy Conversion Systems

Toomas Vaimann, Anton Rassõlkin, Ants Kallaste, Raimondas Pomarnacki, Anouar Belahcen, Van Khang Hyunh

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

6 Citations (Scopus)

Abstract

Diagnostics and prognostics of electrical energy conversion systems are moving forward with the rapid development of IT and artificial intelligence possibilities. This also broadens the horizons for classical and advanced condition and operation monitoring techniques, resulting in more accurate fault detection, degradation prognosis and calculation of remaining life of energy conversion systems, utilized in every aspect and field of industry today. This paper gives an overview of the necessity for condition monitoring and diagnostics of the mentioned systems, explaining the classical and advanced techniques for diagnostics. Methodology to diagnose and prognose the energy conversion units, where classical maintenance techniques are not sufficient in the economic, environmental and safety reasons is proposed. An extensive state of art in the field of diagnostics, regarding the aforementioned problems and techniques is provided.

Original languageEnglish
Title of host publicationProceedings of the 27th International Workshop on Electric Drives
Subtitle of host publicationMPEI Department of Electric Drives 90th Anniversary, IWED 2020
PublisherIEEE
Number of pages4
ISBN (Electronic)9781728141589
DOIs
Publication statusPublished - Jan 2020
MoE publication typeA4 Article in a conference publication
EventInternational Workshop on Electric Drives - Moscow, Russian Federation
Duration: 27 Jan 202030 Jan 2020
Conference number: 27

Workshop

WorkshopInternational Workshop on Electric Drives
Abbreviated titleIWED
CountryRussian Federation
CityMoscow
Period27/01/202030/01/2020

Keywords

  • Artificial intelligence
  • Energy conversion
  • Fault detection
  • Machine learning

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