Journal ArticleDOI
An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples
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TLDR
The integrated fault diagnosis and prognosis approach is validated using bearing lifetime test data acquired from a wind turbine in field, and the performance comparison with typical data driven technique outlines the significance of the presented method.About:
This article is published in Renewable Energy.The article was published on 2020-01-01. It has received 113 citations till now. The article focuses on the topics: Predictive maintenance & Bearing (mechanical).read more
Citations
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A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin
TL;DR: To realize reliable predictive maintenance of CNCMT, a hybrid approach driven by Digital Twin (DT) is studied and shows that the proposed method is feasible and more accurate than single approach.
Journal ArticleDOI
Critical Wind Turbine Components Prognostics: A Comprehensive Review
Milad Rezamand,Mojtaba Kordestani,Rupp Carriveau,David S.-K. Ting,Marcos E. Orchard,Mehrdad Saif +5 more
TL;DR: A comprehensive review of modeling developments for the RUL prediction of critical WT components reveals that hybrid methods are now the leading and most accurate tools for WT failure predictions over individual hybrid components.
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Fault Diagnosis of Wind Turbines Based on a Support Vector Machine Optimized by the Sparrow Search Algorithm
TL;DR: In this paper, the sparrow search algorithm (SSA) is used to optimize the penalty factor and kernel function parameter of SVM and to construct the SSA-SVM wind turbine fault diagnosis model.
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A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing
TL;DR: A novel deep convolutional neural network-bootstrap-based integrated prognostic approach for the remaining useful life (RUL) prediction of rolling bearing is developed and the RUL prediction interval can be effectively quantified without relying on the bearing’s physical or statistical prior information based on bootstrap implementation paradigm.
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A hybrid DBN-SOM-PF-based prognostic approach of remaining useful life for wind turbine gearbox
TL;DR: A novel performance degradation assessment method based on deep belief network (DBN) and self-organizing map (SOM) is proposed to de-noise and merge multi-sensor vibration signals and predict RUL of WT gearbox effectively.
References
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TL;DR: Both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters are reviewed.
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Opportunities and challenges for a sustainable energy future
Steven Chu,Arun Majumdar +1 more
TL;DR: This Perspective provides a snapshot of the current energy landscape and discusses several research and development opportunities and pathways that could lead to a prosperous, sustainable and secure energy future for the world.
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Market efficiency, long-term returns, and behavioral finance1The comments of Brad Barber, David Hirshleifer, S.P. Kothari, Owen Lamont, Mark Mitchell, Hersh Shefrin, Robert Shiller, Rex Sinquefield, Richard Thaler, Theo Vermaelen, Robert Vishny, Ivo Welch, and a referee have been helpful. Kenneth French and Jay Ritter get special thanks.1
TL;DR: In this paper, the authors show that most long-term return anomalies tend to disappear with reasonable changes in technique and that apparent overreaction to information is about as common as underreaction.