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Advanced Online Condition Monitoring for Wind and Marine Energy Conversion...
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Advanced Online Condition Monitoring for Wind and Marine Energy Conversion Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (30 December 2022) | Viewed by 9247

Special Issue Editors

Dr. Shahin Hedayati Kia

E-Mail Website
Guest Editor
Laboratoire MIS, Université de Picardie « Jules Verne », 80000 Amiens, France
Interests: hardware-in-the-loop; real-time simulation; condition monitoring
Prof. Dr. Hubert Razik

E-Mail Website
Guest Editor
Laboratoire Ampère, UNCBL Lyon 1, ECL, INSA, CNRS, Université de Lyon, 69100 Villeurbanne, France
Interests: renewable energy; diagnosis and prognosis of electric actuators

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit your recent research papers to a Special Issue of Energies Journal on the subject area of “Advanced Online Condition Monitoring for Wind and Marine Energy Conversion Systems”. Wind and marine turbines are composed of a large number of electrical and mechanical components. They are designed to efficiently and robustly convert the kinetic power of wind and water into the electric power. They operate mostly in harsh working conditions, subjected commonly to the electrical and mechanical stresses due to their interactions with the power network and the external environment. Detection and diagnosis of incipient faults in the drive-train main elements, i.e., the multistage gearbox, the main bearing, the main shaft, and the generator improve significantly the reliability and availability of such complex systems. The prediction of remaining useful life (RUL) is possible by using prognosis tools such as Kalman filters, particle filters, and hidden Markov's model. It allows the planning of the condition-based maintenance of the drive-train components. Studying the efficiency of developed approaches in real-time is also a crucial factor for online condition-based maintenance (CBM), which enables us to identify and to isolate any incipient defect at the earliest possible time. The subject of interest of this Special Issue is the newly developed advanced techniques for online condition monitoring of wind and marine energy conversion systems. Furthermore, the development of high-fidelity hardware-in-the-loop (H-i-L) facilities with the main aim of real-time evaluation of the developed techniques at low cost is included. The potential papers for publication may cover, but are not limited to, the following topics:

  • Wind and marine generators condition monitoring;
  • Multistage gearbox and bearing condition monitoring;
  • Online condition monitoring in time-varying working conditions;
  • Physical modeling of incipient faults in the wind and marine drive-train components;
  • Implementation of fault detection, diagnosis and prognosis algorithms in real-time platforms;
  • Real-time digital simulation of wind and marine energy conversion systems;
  • Hardware-in-the-loop facilities for real-time evaluation of condition monitoring methods.

Dr. Shahin Hedayati Kia
Prof. Dr. Hubert Razik
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • online condition monitoring
  • real-time simulation
  • wind and marine turbines
  • advanced techniques of fault detection, diagnosis and prognosis
  • wind and marine energies
  • non-invasive condition monitoring

Dr. Shahin Hedayati Kia
Prof. Dr. Hubert Razik
Guest Editors

Published Papers (3 papers)

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Research

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24 pages, 3241 KiB  
Article
PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems
by Abdenour Soualhi, Mourad Lamraoui, Bilal Elyousfi and Hubert Razik
Energies 2022, 15(19), 6909; https://doi.org/10.3390/en15196909 - 21 Sep 2022
Cited by 11 | Viewed by 3568
Abstract
Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause [...] Read more.
Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization. It allows for permanently monitoring the health of the system and provides operators and managers with relevant information to decide on actions to be taken to maintain the system in optimal operational conditions. This paper aims to present the emergence of the PHM thematically to describe the subjacent processes, particularly prognosis, how it supplies the different maintenance strategies and to explain the benefits that can be anticipated. More specifically, this paper establishes a state of the art in prognostic methods used today in the PHM strategy. In addition, this paper shows the multitude of possible prognostic approaches and the choice of one among them that will help to provide a framework for industrial companies. Full article
(This article belongs to the Special Issue Advanced Online Condition Monitoring for Wind and Marine Energy Conversion Systems)
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17 pages, 3307 KiB  
Article
Power-Hardware-in-the-Loop for Stator Windings Asymmetry Fault Analysis in Direct-Drive PMSG-Based Wind Turbines
by Meysam Yousefzadeh, Shahin Hedayati Kia, Mohammad Hoseintabar Marzebali, Davood Arab Khaburi and Hubert Razik
Energies 2022, 15(19), 6896; https://doi.org/10.3390/en15196896 - 21 Sep 2022
Cited by 2 | Viewed by 1588
Abstract
This article studies the stator windings asymmetry fault in direct-drive permanent magnet synchronous generator(PMSG)-based wind turbines (WTs), having passive converters at the generator side, through developing a power-hardware-in-the-loop (P-H-i-L) system. It is based on a digital real-time simulation (DRTS) of turbine blades, a [...] Read more.
This article studies the stator windings asymmetry fault in direct-drive permanent magnet synchronous generator(PMSG)-based wind turbines (WTs), having passive converters at the generator side, through developing a power-hardware-in-the-loop (P-H-i-L) system. It is based on a digital real-time simulation (DRTS) of turbine blades, a wind generator in the abc reference frame, and a three-phase diode rectifier mathematical models. The DC voltage, provided by the model of the three-phase diode rectifier, is linked to a one-level hardware boost converter by using a programmable DC power supply. Furthermore, the maximum power point tracking technique, based on the optimal torque, is evaluated when the one-level boost converter supplies a resistive load. Stator windings asymmetry fault in the PMSG is identified by analyzing the rectifier output voltage, the rotor speed, and the electrical signatures of the boost converter. It shows that this kind of fault clearly gives rise to the amplitudes of both 2·fs and 4·fs frequency components in the mentioned signatures, where fs is the main frequency component of the stator current. DRTSs are compared with digital offline simulations (DoSs), based on a Matlab/Simulink Simscape physical model, to demonstrate the efficacy of the proposed framework. Full article
(This article belongs to the Special Issue Advanced Online Condition Monitoring for Wind and Marine Energy Conversion Systems)
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Review

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36 pages, 2813 KiB  
Review
A Comprehensive Review of Conventional and Intelligence-Based Approaches for the Fault Diagnosis and Condition Monitoring of Induction Motors
by Rahul R. Kumar, Mauro Andriollo, Giansalvo Cirrincione, Maurizio Cirrincione and Andrea Tortella
Energies 2022, 15(23), 8938; https://doi.org/10.3390/en15238938 - 25 Nov 2022
Cited by 21 | Viewed by 2956
Abstract
This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ones that are common in Industry 4.0. After giving an overview on fault statistics, standard [...] Read more.
This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ones that are common in Industry 4.0. After giving an overview on fault statistics, standard methods for the FD and CM of rotating machines are first visited, and then its orientation towards intelligent approaches is discussed. Major diagnostic procedures are addressed in detail together with their advancements to date. In particular, the emphasis is given to motor current signature analysis (MCSA) and digital signal processing techniques (DSPTs) mostly used for feature engineering. Consequently, the statistical procedures and machine learning techniques (stemming from artificial intelligence—AI) are also visited to describe how FD is carried out in various systems. The effectiveness of the amalgamation of the model, signal, and data-based techniques for the FD and CM of inductions motors (IMs) is also highlighted in this review. It is worth mentioning that a variety of neural- and non-neural-based approaches are discussed concerning major faults in rotating machines. Finally, after a thorough survey of the diagnostic techniques based on specific faults for electrical drives, several open problems are identified and discussed. The paper concludes with important recommendations on where to divert the research focus considering the current advancements in the FD and CM of rotating machines. Full article
(This article belongs to the Special Issue Advanced Online Condition Monitoring for Wind and Marine Energy Conversion Systems)
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