Anomaly Detection of Wind Turbines Based on Deep Small-World Neural Network

Dynamic Fault Monitoring of Pitch System in Wind Turbines using Selective Ensemble Small-World Neural Networks

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Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox

(2018) Guoqian Jiang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

The optimized deep belief networks with improved logistic Sigmoid units and their application in fault diagnosis for planetary gearboxes of wind turbines

(2018) Yi Qin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Short-term wind power prediction based on improved small-world neural network

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Anomaly detection and fault analysis of wind turbine components based on deep learning network

(2018) Hongshan Zhao et al.   RENEWABLE ENERGY

Fault Diagnosis Based on an Approach Combining a Spectrogram and a Convolutional Neural Network with Application to a Wind Turbine System

(2018) Wenxin Yu et al.   Energies

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Research on intelligent fault diagnosis of mechanical equipment based on sparse deep neural networks

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Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network

(2015) Yushi Chen et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Deep learning

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Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 2: Application examples

(2013) Meik Schlechtingen et al.   APPLIED SOFT COMPUTING

Wind turbine condition monitoring by the approach of SCADA data analysis

(2013) Wenxian Yang et al.   RENEWABLE ENERGY

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