A Systematic Framework for Unsupervised Feature Mining and Fault Detection for Wind Turbine Drivetrain Systems

[1]  Michael Pecht,et al.  Using maintenance options to maximize the benefits of prognostics for wind farms , 2014 .

[2]  Yingning Qiu,et al.  Wind turbine condition monitoring: technical and commercial challenges , 2014 .

[3]  F. Bonnardot,et al.  Impact of the non-uniform angular sampling on mechanical signals , 2014 .

[4]  Han Jiguang,et al.  Wind turbine fault diagnosis method based on diagonal spectrum and clustering binary tree SVM , 2013 .

[5]  Quentin Leclere,et al.  A multi-order probabilistic approach for Instantaneous Angular Speed tracking debriefing of the CMMNO׳14 diagnosis contest , 2016 .

[6]  Lina Bertling,et al.  On the economic benefits of using Condition Monitoring Systems for maintenance management of wind power systems , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.

[7]  Robert B. Randall,et al.  Separation and enhancement of gear and bearing signals for the diagnosis of wind turbine transmission systems , 2014 .

[8]  Keith Worden,et al.  A Performance Monitoring Approach for the Novel Lillgrund Offshore Wind Farm , 2015, IEEE Transactions on Industrial Electronics.

[9]  Christopher Durugbo,et al.  Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes , 2016 .

[10]  Amir Ahadi,et al.  Wind Turbine Fault diagnosis Techniques and Related Algorithms , 2016, International Journal of Renewable Energy Research.

[11]  Jae-Kyung Lee,et al.  Development of a Novel Power Curve Monitoring Method for Wind Turbines and Its Field Tests , 2014, IEEE Transactions on Energy Conversion.

[12]  John Berry,et al.  Automated Helicopter Vibration Diagnostics for the US Army and National Guard , 2001 .

[13]  Andrew Kusiak,et al.  The prediction and diagnosis of wind turbine faults , 2011 .

[14]  D. P. Kothari,et al.  Simulation of Sensor Fault Diagnosis for Wind Turbine Generators DFIG and PMSM Using Kalman Filter , 2014 .

[15]  Robert B. Randall,et al.  Editorial for the special issue on Instantaneous Angular Speed (IAS) processing and angular applications , 2014 .

[16]  Jay Lee,et al.  Wind turbine performance assessment using multi-regime modeling approach , 2012 .

[17]  Stephen Grossberg,et al.  The ART of adaptive pattern recognition by a self-organizing neural network , 1988, Computer.

[18]  Jay Lee,et al.  Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications , 2014 .

[19]  Miguel A. Sanz-Bobi,et al.  Wind turbine condition assessment based on changes observed in its power curve , 2013, 2013 International Conference on Renewable Energy Research and Applications (ICRERA).

[20]  Tetsuo Tomiyama,et al.  Reliability of wind turbine technology through time , 2008 .

[21]  A. Fuels,et al.  Electric power monthly , 1992 .

[22]  Meik Schlechtingen,et al.  Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection , 2011 .

[23]  Huan Long,et al.  Data-Driven Wind Turbine Power Generation Performance Monitoring , 2015, IEEE Transactions on Industrial Electronics.

[24]  Allan May,et al.  Economic analysis of condition monitoring systems for offshore wind turbine sub-systems , 2014 .

[25]  Jay Lee,et al.  Novel method for rolling element bearing health assessment—A tachometer-less synchronously averaged envelope feature extraction technique , 2012 .

[26]  Jay Lee,et al.  Fault detection in a network of similar machines using clustering approach , 2012 .

[27]  Meik Schlechtingen,et al.  Condition monitoring with ordinary wind turbine SCADA data – A neuro-fuzzy approach , 2012 .

[28]  Peter Tavner,et al.  Wind turbine pitch faults prognosis using a-priori knowledge-based ANFIS , 2013, Expert Syst. Appl..

[29]  L.W.M.M. Rademakers,et al.  TOOLS FOR ESTIMATING OPERATION AND MAINTENANCE COSTS OF OFFSHORE WIND FARMS: State of the Art , 2008 .

[30]  María Isabel Blanco.  The economics of wind energy , 2009 .

[31]  Robert B. Randall,et al.  Rolling element bearing diagnostics—A tutorial , 2011 .

[32]  Peter Tavner,et al.  Reliability of wind turbine subassemblies , 2009 .

[33]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[34]  Tomasz Barszcz,et al.  A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram , 2011 .

[35]  Liliane Pintelon,et al.  Quantifying the added value of an imperfectly performing condition monitoring system - Application to a wind turbine gearbox , 2013, Reliab. Eng. Syst. Saf..

[36]  Wenhai Li,et al.  The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network , 2008, 2008 International Conference on Condition Monitoring and Diagnosis.

[37]  Jiahai Yuan,et al.  Wind turbine manufacturing in China: A review , 2015 .

[38]  Jay Lee,et al.  Robust performance degradation assessment methods for enhanced rolling element bearing prognostics , 2003, Adv. Eng. Informatics.

[39]  Robert B. Randall,et al.  The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines , 2006 .

[40]  Judith Gurney.  BP Statistical Review of World Energy , 1985 .

[41]  Wendy Foslien,et al.  Power Curve Analytic for Wind Turbine Performance Monitoring and Prognostics , 2011 .

[42]  Eric Bechhoefer,et al.  A Review of Time Synchronous Average Algorithms , 2009 .

[43]  M. Hand,et al.  2013 Cost of Wind Energy Review , 2015 .

[44]  Zhe Chen,et al.  An improved fuzzy synthetic condition assessment of a wind turbine generator system , 2013 .

[45]  A. Kusiak,et al.  A Data-Mining Approach to Monitoring Wind Turbines , 2012, IEEE Transactions on Sustainable Energy.

[46]  Sachin C. Patwardhan,et al.  A possibilistic clustering approach to novel fault detection and isolation , 2006 .

[47]  Peter Tavner,et al.  Survey of commercially available condition monitoring systems for wind turbines. , 2014 .

[48]  P. D. McFadden,et al.  Model for the vibration produced by a single point defect in a rolling element bearing , 1984 .

[49]  Fouad Slaoui-Hasnaoui,et al.  Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges , 2014 .

[50]  Shuangwen Sheng,et al.  Wind Turbine Drivetrain Condition Monitoring - An Overview , 2011 .

[51]  Robert B. Randall,et al.  Instantaneous Angular Speed (IAS) processing and related angular applications , 2014 .

[52]  Thomas L Lagö,et al.  Main Principles and Limitations of Current Order Tracking Methods , 2005 .

[53]  Jay Lee,et al.  An Integrated Framework of Drivetrain Degradation Assessment and Fault Localization for Offshore Wind Turbines , 2020 .

[54]  Huageng Luo,et al.  Effective and accurate approaches for wind turbine gearbox condition monitoring , 2014 .

[55]  A Kusiak,et al.  A Data-Driven Approach for Monitoring Blade Pitch Faults in Wind Turbines , 2011, IEEE Transactions on Sustainable Energy.

[56]  J. Antoni.  The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .

[57]  Tomasz Barszcz,et al.  Modeling of probability distribution functions for automatic threshold calculation in condition monitoring systems , 2013 .

[58]  James Carroll,et al.  Failure rate, repair time and unscheduled O&M cost analysis of offshore wind turbines , 2016 .

[59]  Hongwei Liu,et al.  Fault analysis of wind turbines in China , 2016 .

[60]  P. J. Tavner,et al.  Review of early operation of UK Round 1 offshore wind farms , 2010, IEEE PES General Meeting.

[61]  Zhenmin Tang,et al.  A Method Combining LPC-Based Cepstrum and Harmonic Product Spectrum for Pitch Detection , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[62]  Shuangwen Sheng,et al.  Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis , 2012 .

[63]  Radislav Smid,et al.  Condition Indicators for Gearbox Condition Monitoring Systems , 2005 .

[64]  Yaoyu Li,et al.  A review of recent advances in wind turbine condition monitoring and fault diagnosis , 2009, 2009 IEEE Power Electronics and Machines in Wind Applications.

[65]  Michel Verleysen,et al.  Statistical tools to assess the reliability of self-organizing maps , 2002, Neural Networks.

[66]  Zijun Zhang,et al.  Fault Analysis and Condition Monitoring of the Wind Turbine Gearbox , 2012, IEEE Transactions on Energy Conversion.

[67]  Maureen Hand,et al.  2010 Cost of Wind Energy Review , 2012 .

[68]  J. Antoni.  Fast computation of the kurtogram for the detection of transient faults , 2007 .

[69]  Peter W. Tse,et al.  The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2” , 2013 .