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From Winding-Fault Geometry to Reliability: Estimation and Prognosis of Stator Inter-Turn Faults — arXiv:2609.13448

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.13448
License (as archived): CC0-1.0
Archived: 2026-10-16T02:55:44.809Z
SHA-256 of the archived text: 854b9ed4704343469c2ab4bcd05ef8aea794766c285154b40e158ec10eee18b2
Stable URL of this page: https://metraipolis.com/documento/dc_87f9c8f9beb2

How to cite

From Winding-Fault Geometry to Reliability: Estimation and Prognosis of Stator Inter-Turn Faults — arXiv:2609.13448 — arXiv (en), https://arxiv.org/abs/2609.13448 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_87f9c8f9beb2 (Metraipolis archive dc_87f9c8f9beb2, sha256 854b9ed4704343469c2ab4bcd05ef8aea794766c285154b40e158ec10eee18b2)

BibTeX

@misc{dc87f9c8f9beb2,
  title = {From Winding-Fault Geometry to Reliability: Estimation and Prognosis of Stator Inter-Turn Faults — arXiv:2609.13448},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.13448},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_87f9c8f9beb2; sha256 854b9ed4704343469c2ab4bcd05ef8aea794766c285154b40e158ec10eee18b2},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.13448. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

This paper develops an integrated framework for estimation, prognosis, and reliability assessment of stator inter-turn faults in induction motors. The fault is characterized by its severity, defined as the fraction of short-circuited turns, and its spatial orientation. A geometric fault model shows that the resulting output signature is affine in the fault severity and exhibits a fundamental spatial periodicity. Exploiting this structure, an augmented-state particle filter jointly estimates the nonlinear electromechanical state and the unknown fault severity while quantifying posterior uncertainty. The estimated degradation is then propagated using four prognostic models: linear trend, Holt exponential smoothing, Bayesian degradation, and particle-based forecasting. Their predictions are connected to threshold-crossing remaining useful life (RUL), first-passage reliability, degradation-dependent hazard reliability, and a Weibull lifetime benchmark, thereby providing both deterministic and probabilistic health assessments. Numerical results demonstrate accurate online fault estimation and output reconstruction, characterize the effects of degradation pattern and prediction horizon on prognosis, and show consistent reliability and threshold-crossing predictions. Moreover, estimation accuracy remains comparable across the distinct fault orientations induced by the spatial periodicity. The resulting framework provides a unified connection from physics-based inter-turn fault modeling to online diagnosis, degradation prognosis, and reliability assessment.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-09-15 in eess.SY).
Categorie arXiv: Systems and Control (eess.SY) ; Signal Processing (eess.SP).
Pagina del lavoro: https://arxiv.org/abs/2609.13448 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T02:45:08.513Z dalla pagina https://arxiv.org/catchup/eess.SY/2026-09-15?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).