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Failure Diagnosis and Prognosis of AC Rotating Machines

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 2852

Special Issue Editor


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Guest Editor
Laboratoire Ampère UMR5005, Univ. Lyon, Université Claude Bernard Lyon 1, Lyon, France
Interests: condition monitoring; digital twin; electrical drives; failure diagnosis; failure prognosis; control; pattern recognition; induction machines; synchronous machines; power electronic
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Special Issue Information

Dear Colleagues,

Induction or synchronous machines present numerous advantages due to their robustness and their power–weight ratio. However, they are subject to several electrical and mechanical faults. Many methods have been developed to diagnose such failures and prevent unwanted stoppage. These can be based on MCSA, vibrations, noise, electrical or magnetic field, etc. Different techniques have been developed, such as model-based and data-driven approaches. Data-driven methods deal with signal processing, statistical tools, data mining, and artificial intelligence.

Recent trends include improvements in diagnostic reliability and accuracy, and new prognostic techniques have been developed for assessing the remaining useful life of these electrical drives and, thus, optimizing maintenance scheduling.

This Special Issue deals with the most recent research on incipient failure diagnosis of induction and synchronous machines, the prognosis of their remaining useful life in steady state or in variable speed, and the operation in degraded mode.

Prof. Dr. Guy Clerc
Guest Editor

Manuscript Submission Information

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Keywords

  • induction machine
  • synchronous machine
  • permanent magnet synchronous machine
  • failure diagnosis
  • failure prognosis
  • short circuit
  • open bars
  • eccentricity
  • artificial intelligence
  • model-based approach
  • data-driven approach
  • degraded mode

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Published Papers (2 papers)

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Research

10 pages, 3129 KiB  
Article
A New Post-Fault Reconfiguration Strategy under Open-Phase Operation Conditions of Asymmetrical Double-Star Induction Machines
by Koussaila Iffouzar, Mohamed-Fouad Benkhoris, Bessam Amrouche, Azeddine Houari, Kaci Ghedamsi and Ali Djerioui
Energies 2023, 16(15), 5740; https://doi.org/10.3390/en16155740 - 1 Aug 2023
Viewed by 906
Abstract
The fault tolerance proprieties of multiphase induction machines make them candidate technologies for future electrified transport systems. Indeed, the use of multiphase drives is primarily recommended for their redundancy, which allows them to handle increasing power demands as well as provide fault-tolerant operation. [...] Read more.
The fault tolerance proprieties of multiphase induction machines make them candidate technologies for future electrified transport systems. Indeed, the use of multiphase drives is primarily recommended for their redundancy, which allows them to handle increasing power demands as well as provide fault-tolerant operation. One of the most common failures in polyphase induction machines is open-phase fault (OPF). Under this degraded mode, machine performance deteriorates with increased torque ripples and copper losses. This work investigates the fault-tolerant operation of dual star induction machines (DSIM) with two connected neutral points in which a new post-fault operation technique is introduced to manage the OPFs. The machine was modeled on the natural reference frame, and no transformations were used. The phase opening is caused by inserting a high-value resistor in series with the faulty phase, which cancels the current flowing in the latter. A post-fault reconfiguration strategy that reorganizes the power converter in order to cancel torque ripples by exploiting the principle of multi-biphase modeling of the DSIM is proposed. The performance of the proposed reconfiguration strategy was verified through detailed simulation results. Full article
(This article belongs to the Special Issue Failure Diagnosis and Prognosis of AC Rotating Machines)
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19 pages, 10383 KiB  
Article
Wind Turbine Gearbox Diagnosis Based on Stator Current
by Idris Issaadi, Kamel Eddine Hemsas and Abdenour Soualhi
Energies 2023, 16(14), 5286; https://doi.org/10.3390/en16145286 - 10 Jul 2023
Cited by 1 | Viewed by 1463
Abstract
Early detection of faults in wind energy systems can reduce downtime, operating, and maintenance costs while increasing productivity. This paper proposes a method based on the analysis of generator stator current signals to detect faults in a wind turbine gearbox equipped with a [...] Read more.
Early detection of faults in wind energy systems can reduce downtime, operating, and maintenance costs while increasing productivity. This paper proposes a method based on the analysis of generator stator current signals to detect faults in a wind turbine gearbox equipped with a doubly fed induction generator (DFIG). A localized parameter model was established to simulate the vibratory response of a two-stage gear system under healthy and faulty conditions. The simulation was performed in the MATLAB/Simulink environment. The results include a detailed analysis of the mechanical part of the gearbox, highlighting mesh stiffness, output speed, and accelerations. Additionally, the electrical part was evaluated based on the current supplied by the doubly fed induction generator. The results were presented in the case of healthy gears and in the presence of faults such as a broken or cracked tooth. Fast Fourier transform (FFT) analysis was employed to detect gear defects in the stator current signal. The presence of a crack or broken tooth in the gearbox induces modulation of the DFIG stator current signals according to the shaft frequencies corresponding to the faulty gear. These findings provide a preliminary basis for the detection and diagnosis of this type of failure. Full article
(This article belongs to the Special Issue Failure Diagnosis and Prognosis of AC Rotating Machines)
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