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Applied Mechanics
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Vibration Monitoring of Wind Turbines: Predicting the Remaining Useful Life
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Vibration Monitoring of Wind Turbines: Predicting the Remaining Useful Life

A special issue of Applied Mechanics (ISSN 2673-3161).

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 3323

Special Issue Editor

Prof. Dr. Juan Carlos Jauregui-Correa

E-Mail Website
Guest Editor
Faculty of Engineering, Universidad Autonoma de Queretaro, Cerro de las Campanas S/N, Queretaro 76010, Mexico
Interests: vibration analysis; prediction of operating conditions; dynamics of machinery; signal analysis; prognostics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on using vibration analysis to assess the health of wind turbines and forecast their operational lifespan. Wind turbines operate under non-stationary dynamic conditions, which cause components like blades, bearings, and gearboxes to degrade over time. Through sensors placed on key components, vibration monitoring detects early signs of wear, component degradation, fatigue, and blade failures.

This Special Issue includes papers on signal analysis and artificial intelligence applied to vibration signals, their correlation with failure modes, and methods for predicting the remaining life of mechanical and electrical components. It also welcomes papers on integrating predictive and proactive maintenance strategies applied to wind turbines based on vibration data to reduce downtime and improve overall performance.

Publishing these findings is essential for the broader wind energy industry, as it supports the development of robust, data-driven maintenance frameworks. These papers will also contribute to optimizing wind farm operations, reducing the levelized cost of energy (LCOE), and improving the sustainability of renewable energy systems.

Prof. Dr. Juan Carlos Jauregui
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Applied Mechanics is an international peer-reviewed open access quarterly 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 1400 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

  • wind turbines
  • vibrations
  • conditioning monitoring
  • life prediction

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Published Papers (2 papers)

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32 pages, 8688 KB  
Article
Aero-Structural Analysis of a Wind Turbine Blade Lay-Up as a Preliminary Design Alternative
by Eduardo Alcantara-Rojas, Boris Miguel López-Rebollar, Jesús Ramiro Félix-Félix, Martha Fernanda Mohedano-Castillo, Carlos Roberto Fonseca Ortiz and Gerardo Cano-Perea
Appl. Mech. 2026, 7(1), 24; https://doi.org/10.3390/applmech7010024 - 17 Mar 2026
Viewed by 571
Abstract
Wind energy has become an essential resource for the development and diversification of the energy sector in México and worldwide. In this context, the mechanical design of turbine blades has emerged as a priority research topic, given its impact on performance and viability. [...] Read more.
Wind energy has become an essential resource for the development and diversification of the energy sector in México and worldwide. In this context, the mechanical design of turbine blades has emerged as a priority research topic, given its impact on performance and viability. The present research evaluates the aero-structural response of multiple lay-up configurations of a 6 m blade by coupling computational fluid dynamics (CFD) and finite element analysis (FEA). The fluid–structure interaction (FSI) was simulated in ANSYS, a commercial software chosen for its capacity for multivariable analysis. The nominal operating conditions included a wind speed of 10.5 m/s and a rotational speed of 100 rpm, leading to a theoretical power output of 6591 W. For the proposed lay-up configurations, the Tsai-Wu and Puck (Global IRF) criteria were estimated and remained below the critical threshold of 1.0, indicating no risk of structural failure. However, some carbon fiber/epoxy layers, including unidirectional layers in the spar caps and bidirectional layers in the structural shear web, may present failure risks under extreme loading conditions. This applies to configurations with the lowest number of layers in the mid-span spar caps; this fact is reinforced by the main effects analysis. The results emphasize the relevance of conducting comprehensive composite failure evaluations to optimize material selection and structural design, even for small-scale blades. Full article
(This article belongs to the Special Issue Vibration Monitoring of Wind Turbines: Predicting the Remaining Useful Life)
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44 pages, 1721 KB  
Systematic Review
Vibration-Based Predictive Maintenance for Wind Turbines: A PRISMA-Guided Systematic Review on Methods, Applications, and Remaining Useful Life Prediction
by Carlos D. Constantino-Robles, Francisco Alberto Castillo Leonardo, Jessica Hernández Galván, Yoisdel Castillo Alvarez, Luis Angel Iturralde Carrera and Juvenal Rodríguez-Reséndiz
Appl. Mech. 2026, 7(1), 11; https://doi.org/10.3390/applmech7010011 - 26 Jan 2026
Cited by 1 | Viewed by 1858
Abstract
This paper presents a systematic review conducted under the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, analyzing 286 scientific articles focused on vibration-based predictive maintenance strategies for wind turbines within the context of advanced Prognostics and Health Management (PHM). The [...] Read more.
This paper presents a systematic review conducted under the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, analyzing 286 scientific articles focused on vibration-based predictive maintenance strategies for wind turbines within the context of advanced Prognostics and Health Management (PHM). The review combines international standards (ISO 10816, ISO 13373, and IEC 61400) with recent developments in sensing technologies, including piezoelectric accelerometers, microelectromechanical systems (MEMS), and fiber Bragg grating (FBG) sensors. Classical signal processing techniques, such as the Fast Fourier Transform (FFT) and wavelet-based methods, are identified as key preprocessing tools for feature extraction prior to the application of machine-learning-based diagnostic algorithms. Special emphasis is placed on machine learning and deep learning techniques, including Support Vector Machines (SVM), Random Forest (RF), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and autoencoders, as well as on hybrid digital twin architectures that enable accurate Remaining Useful Life (RUL) estimation and support autonomous decision-making processes. The bibliometric and case study analysis covering the period 2020–2025 reveals a strong shift toward multisource data fusion—integrating vibration, acoustic, temperature, and Supervisory Control and Data Acquisition (SCADA) data—and the adoption of cloud-based platforms for real-time monitoring, particularly in offshore wind farms where physical accessibility is constrained. The results indicate that vibration-based predictive maintenance strategies can reduce operation and maintenance costs by more than 20%, extend component service life by up to threefold, and achieve turbine availability levels between 95% and 98%. These outcomes confirm that vibration-driven PHM frameworks represent a fundamental pillar for the development of smart, sustainable, and resilient next-generation wind energy systems. Full article
(This article belongs to the Special Issue Vibration Monitoring of Wind Turbines: Predicting the Remaining Useful Life)
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