Simulating a Jammed Rotor Fault on SynRM and Integrate Results with Machine Learning

The increasing use of synchronous reluctance motors (SynRM) in various types of electric drives is explained by its advantages. Different models of SynRM are used to study and control electric drives. In the article, a non-iterative model for electric drive research is proposed. Different types of faults can be simulated using this model. Jammed rotor fault mode is simulated. The obtained simulation results are diagnosed by machine learning, and the diagnosis accuracy is more than 98%.

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Publication Details

Journal
WSEAS TRANSACTIONS ON SYSTEMS
Published
2025-05-06
DOI
https://doi.org/10.37394/23202.2025.24.26
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Simulating a Jammed Rotor Fault on SynRM and Integrate Results with Machine Learning

Nikolay Djagarov, Hristo Milushev, Georgi Enchev
WSEAS TRANSACTIONS ON SYSTEMS
Fault Detection and Control Systems
article

Simulating a Jammed Rotor Fault on SynRM and Integrate Results with Machine Learning

Nikolay Djagarov, Hristo Milushev, Georgi Enchev
article en

Abstract

The increasing use of synchronous reluctance motors (SynRM) in various types of electric drives is explained by its advantages. Different models of SynRM are used to study and control electric drives. In the article, a non-iterative model for electric drive research is proposed. Different types of faults can be simulated using this model. Jammed rotor fault mode is simulated. The obtained simulation results are diagnosed by machine learning, and the diagnosis accuracy is more than 98%.

WSEAS TRANSACTIONS ON SYSTEMSVol. 24
Nikola Vaptsarov Naval Academy (BG)
Openalex Percentile: Top 90%
Fault Detection and Control Systems
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