- Project Dates: January 2015 - December 2016
- Project Leader: Dr Wenxian Yang
- Staff: Dr Wenye Tian, Dr Pu Shi
- Sponsors: XEMC Wind Power Ltd
- Partners: Shanghai Jiao Tong University
A large wind farm often consists of hundreds turbines. If each turbine is equipped with a commercially available vibration-analysis-based condition monitoring system with more than 10 data acquisition channels, a large amount of condition monitoring data will be created in short time. How to quickly transport these data from wind farm to central office for further analysis, how to process these data in the first time, and how to store and manage these data in the long-term are challenging issues facing to the wind farm operator.
This project aims to address these issues by developing an innovative cooperative condition monitoring strategy through deeply exploring the added value of the low rated data collected by the wind farm Supervisory Control and Data Acquisition system. The technique reduces the amount of data used for condition monitoring, while improves the reliability of wind turbine condition monitoring result via assessing the health condition of the turbine by examining its performance over time rather than by inspecting the instantaneous change of its dynamic response which would be affected by inconsistent wind load.