Journal ArticleDOI
A review of wind turbine bearing condition monitoring: State of the art and challenges
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In this article, the authors provide a review on wind turbine bearing condition monitoring techniques such as acoustic measurement, electrical effects monitoring, power quality, temperature monitoring, wear debris analysis and vibration analysis.Abstract:
Since the early 1980s, wind power technology has experienced an immense growth with respect to both the turbine size and market share. As the demand for large-scale wind turbines and lor operation & maintenance cost continues to raise, the interest on condition monitoring system has increased rapidly. The main components of wind turbines are the focus of all CMS since they frequently cause high repair costs and equipment downtime. However, vast quantities of their failures are caused due to a bearing failure. Therefore, bearing condition monitoring becomes crucial. This paper aims at providing a state-of-the-art review on wind turbine bearing condition monitoring techniques such as acoustic measurement, electrical effects monitoring, power quality, temperature monitoring, wear debris analysis and vibration analysis. Furthermore, this paper will present a literature review and discuss several technical, financial and operational challenges from the purchase of the CMS to the wind farm monitoring stage.read more
Citations
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Journal ArticleDOI
Machine learning methods for wind turbine condition monitoring: A review
Adrian Stetco,Fateme Dinmohammadi,Xingyu Zhao,Valentin Robu,David Flynn,Mike Barnes,John A. Keane,Goran Nenadic +7 more
TL;DR: This paper reviews the recent literature on machine learning models that have been used for condition monitoring in wind turbines and shows that most models use SCADA or simulated data, with almost two-thirds of methods using classification and the rest relying on regression.
Journal ArticleDOI
Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review
TL;DR: A systemic and pertinent state-of-art review on WT planetary gearbox condition monitoring techniques on the topics of fundamental analysis, signal processing, feature extraction, and fault detection is provided.
Journal ArticleDOI
A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings
Zepeng Liu,Long Zhang +1 more
TL;DR: This paper aims at systematically and comprehensively summarizing current large-scale wind turbine bearing failure modes and condition monitoring and fault diagnosis achievements, followed by a brief summary of future research directions for wind turbine Bearing fault diagnosis.
Journal ArticleDOI
Gearbox condition monitoring in wind turbines: A review
TL;DR: A review on different methods and techniques for gearbox condition monitoring in wind turbines aiming to increase lifetime expectancy of components while reducing operation and maintenance cost is gathered.
Journal ArticleDOI
A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery
Ming Zhao,Ming Zhao,Xiaodong Jia +2 more
TL;DR: In this paper, a reweighted singular value decomposition (RSVD) strategy is proposed for signal denoising and weak feature enhancement in a two-stage gearbox as well as train bearings.
References
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Journal ArticleDOI
Condition monitoring of wind turbines: Techniques and methods
TL;DR: A review of the state-of-the-art in the condition monitoring of wind turbines can be found in this article, which describes the different maintenance strategies, condition monitoring techniques and methods, and highlights in a table the various combinations of these that have been reported in the literature.
Journal ArticleDOI
Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals
TL;DR: In this article, a mathematical analysis to select the most significant intrinsic mode functions (IMFs) is presented, and the chosen features are used to train an artificial neural network (ANN) to classify bearing defects.
Journal ArticleDOI
Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression
TL;DR: The experimental results show that the use of the HHT, the SVM, and the SVR is a suitable strategy to improve the detection, diagnostic, and prognostic of bearing degradation.
Journal ArticleDOI
Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges
Pierre Tchakoua,Rene Wamkeue,Mohand Ouhrouche,Fouad Slaoui-Hasnaoui,Tommy Andy Tameghe,Gabriel Ekemb +5 more
TL;DR: In this article, a general review and classification of wind turbine condition monitoring methods and techniques with a focus on trends and future challenges is provided, and interesting insights from this research are used to point out strengths and weaknesses in today's WTCM industry and define research priorities needed for the industry to meet the challenges in wind industry technological evolution and market growth.
Journal ArticleDOI
Wind turbine condition monitoring: technical and commercial challenges
TL;DR: In this paper, the authors present the wind industry with a detailed analysis of the current practical challenges with existing wind turbine condition monitoring technology, in particular, reliability and value for money.