A threshold self-setting condition monitoring scheme for wind turbine generator bearings based on deep convolutional generative adversarial networks

An improved process monitoring by mixed multivariate memory control charts: An application in wind turbine field

(2020) Babar Zaman et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Intelligent fault diagnosis of rotating machinery via wavelet transform, generative adversarial nets and convolutional neural network

(2020) Pengfei Liang et al.   MEASUREMENT

A novel knowledge transfer network with fluctuating operational condition adaptation for bearing fault pattern recognition

(2020) Peng Chen et al.   MEASUREMENT

Distributed Nash Equilibrium Seeking With Limited Cost Function Knowledge via a Consensus-Based Gradient-Free Method

(2020) Yipeng Pang et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

Wind turbine main‐bearing loading and wind field characteristics

(2019) Edward Hart et al.   WIND ENERGY

Maximizing receiver operating characteristics convex hull via dynamic reference point-based multi-objective evolutionary algorithm

(2019) Fan Cheng et al.   APPLIED SOFT COMPUTING

An ameliorated synchroextracting transform based on upgraded local instantaneous frequency approximation

(2019) Peng Chen et al.   MEASUREMENT

A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings

(2019) Zepeng Liu et al.   MEASUREMENT

An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples

(2019) Jinjiang Wang et al.   RENEWABLE ENERGY

A novel unsupervised deep learning model for global and local health condition assessment of structures

(2018) Mohammad Hossein Rafiei et al.   ENGINEERING STRUCTURES

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

(2018) Long Wen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Scalable and Unsupervised Feature Engineering Using Vibration-Imaging and Deep Learning for Rotor System Diagnosis

(2018) Hyunseok Oh et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information

(2018) Guoqian Jiang et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Deep Learning for Infrared Thermal Image Based Machine Health Monitoring

(2018) Olivier Janssens et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

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

(2018) Hongshan Zhao et al.   RENEWABLE ENERGY

Deep learning and its applications to machine health monitoring

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

Reliability assessment of wind turbine bearing based on the degradation-Hidden-Markov model

(2018) Jianlan Li et al.   RENEWABLE ENERGY

Learning from class-imbalanced data: Review of methods and applications

(2017) Guo Haixiang et al.   EXPERT SYSTEMS WITH APPLICATIONS

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

(2015) Wei Qiao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Application of computed order tracking, Vold–Kalman filtering and EMD in rotating machine vibration

(2010) K.S. Wang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Nonlinear Dynamic Process Monitoring Using Canonical Variate Analysis and Kernel Density Estimations

(2009) P.-E.P. Odiowei et al.   IEEE Transactions on Industrial Informatics

A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

(2008) Alexander Statnikov et al.   BMC BIOINFORMATICS

Structural health monitoring for a wind turbine system: a review of damage detection methods

(2008) Chia Chen Ciang et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Condition monitoring and fault detection of wind turbines and related algorithms: A review

(2007) Z. Hameed et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS