Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis

Improving the availability of wind turbines is critical for minimising the cost of wind energy, especially offshore. The development of reliable and cost-effective gearbox condition monitoring systems (CMSs) is of concern to the wind industry, because the gearbox downtime has a significant effect on the wind turbine availabilities. Timely detection and diagnosis of developing gear defects is essential for minimising an unplanned downtime. One of the main limitations of most current CMSs is the time consuming and costly manual handling of large amounts of monitoring data, therefore automated algorithms would be welcome. This study presents a fault detection algorithm for incorporation into a commercial CMS for automatic gear fault detection and diagnosis. Based on the experimental evidence from the Durham Condition Monitoring Test Rig, a gear condition indicator was proposed to evaluate the gear damage during non-stationary load and speed operating conditions. The performance of the proposed technique was then successfully tested on signals from a full-size wind turbine gearbox that had sustained gear damage, and had been studied in a National Renewable Energy Laboratory's (NREL) programme. The results show that the proposed technique proves efficient and reliable for detecting gear damage. Once implemented into the wind turbine CMSs, this algorithm can automate the data interpretation, thus reducing the quantity of the information that the wind turbine operators must handle.

[1]  Mayorkinos Papaelias,et al.  Condition monitoring of wind turbines: Techniques and methods , 2012 .

[2]  Shuangwen Sheng,et al.  Investigation of Various Condition Monitoring Techniques Based on a Damaged Wind Turbine Gearbox , 2011 .

[3]  Simon J. Watson,et al.  Physics of Failure approach to wind turbine condition based maintenance , 2009 .

[4]  Sung-Hoon Ahn,et al.  Condition monitoring and fault detection of wind turbines and related algorithms: A review , 2009 .

[5]  James F. Manwell,et al.  Condition monitoring and prognosis of utility scale wind turbines , 2006 .

[6]  Yingning Qiu,et al.  Monitoring wind turbine gearboxes , 2013 .

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

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

[9]  Steve Goldman,et al.  Vibration Spectrum Analysis: A Practical Approach , 1991 .

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

[11]  Peter Tavner,et al.  Wind turbine downtime and its importance for offshore deployment. , 2011 .

[12]  B. McNiff,et al.  Wind Turbine Testing in the NREL Dynamometer Test Bed , 2000 .

[13]  David McMillan,et al.  Quantification of Condition Monitoring Benefit for Offshore Wind Turbines , 2007 .

[14]  Christopher A. Walford,et al.  Wind Turbine Reliability: Understanding and Minimizing Wind Turbine Operation and Maintenance Costs , 2006 .

[15]  C. J. Crabtree Condition monitoring techniques for wind turbines , 2011 .

[16]  F. Spinato,et al.  Condition Monitoring of Generators & Other Subassemblies in Wind Turbine Drive Trains , 2007, 2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[17]  Robert B. Randall,et al.  A New Method of Modeling Gear Faults , 1982 .

[18]  R. Errichello,et al.  Gearbox Reliability Collaborative Gearbox 1 Failure Analysis Report: December 2010 - January 2011 , 2012 .

[19]  Peter Tavner,et al.  Offshore Wind Turbines: Reliability, availability and maintenance , 2012 .

[20]  Robert B. Randall,et al.  Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications , 2011 .

[21]  E. J. Wiggelinkhuizen,et al.  Assessment of Condition Monitoring Techniques for Offshore Wind Farms , 2008 .