Diagnostics of Interturn Short Circuits in PMSMs With Online Fault Indicators Estimation
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Date
2024-02-27
Authors
0000-0002-3183-2438Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
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Abstract
This article presents novel model-based diagnostics of interturn short circuits in permanent magnet synchronous machines that enable estimating fault location and its severity, even during transients. The proposed method utilizes recursive parametric estimation and model comparison approaches cast in a decision-making framework to track motor parameters and fault indicators from a machine's discrete-time model. The discrete-time prototype is derived from an advanced motor model that reflects the stator winding arrangement in a motor's case. The fault detection is then performed by tracking the changes in the estimated probability density function of the electrical parameters, using the Kullback–Leibler divergence. The fault location is subsequently evaluated by performing a recursive comparison of the predefined fault models in the different phases, utilizing a growing-window approach. Ultimately, a parametric estimation algorithm applied to the fault current model allows identifying the fault severity. The diagnostic algorithm has been validated via laboratory experiments, and its capabilities are compared with other approaches enabling severity estimation.
Description
Citation
IEEE Transactions on Industrial Electronics. 2024, 11 p.
https://ieeexplore.ieee.org/document/10449893
https://ieeexplore.ieee.org/document/10449893
Document type
Peer-reviewed
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Published version
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en