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Partial Inductance Model of Induction Machines for Fault Diagnosis

The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for hea...

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Autores principales: Pineda-Sanchez, Manuel, Puche-Panadero, Ruben, Martinez-Roman, Javier, Sapena-Bano, Angel, Riera-Guasp, Martin, Perez-Cruz, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069024/
https://www.ncbi.nlm.nih.gov/pubmed/30022017
http://dx.doi.org/10.3390/s18072340
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author Pineda-Sanchez, Manuel
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Riera-Guasp, Martin
Perez-Cruz, Juan
author_facet Pineda-Sanchez, Manuel
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Riera-Guasp, Martin
Perez-Cruz, Juan
author_sort Pineda-Sanchez, Manuel
collection PubMed
description The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases’ coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases’ inductances. The proposed method is validated using a commercial induction motor with forced broken bars.
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spelling pubmed-60690242018-08-07 Partial Inductance Model of Induction Machines for Fault Diagnosis Pineda-Sanchez, Manuel Puche-Panadero, Ruben Martinez-Roman, Javier Sapena-Bano, Angel Riera-Guasp, Martin Perez-Cruz, Juan Sensors (Basel) Article The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases’ coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases’ inductances. The proposed method is validated using a commercial induction motor with forced broken bars. MDPI 2018-07-18 /pmc/articles/PMC6069024/ /pubmed/30022017 http://dx.doi.org/10.3390/s18072340 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pineda-Sanchez, Manuel
Puche-Panadero, Ruben
Martinez-Roman, Javier
Sapena-Bano, Angel
Riera-Guasp, Martin
Perez-Cruz, Juan
Partial Inductance Model of Induction Machines for Fault Diagnosis
title Partial Inductance Model of Induction Machines for Fault Diagnosis
title_full Partial Inductance Model of Induction Machines for Fault Diagnosis
title_fullStr Partial Inductance Model of Induction Machines for Fault Diagnosis
title_full_unstemmed Partial Inductance Model of Induction Machines for Fault Diagnosis
title_short Partial Inductance Model of Induction Machines for Fault Diagnosis
title_sort partial inductance model of induction machines for fault diagnosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069024/
https://www.ncbi.nlm.nih.gov/pubmed/30022017
http://dx.doi.org/10.3390/s18072340
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