Abstract Considering the harsh environment of wind farms, the difficulty of early fault monitoring and high unit failure rate, a wind farm main equipment early warning diagnosis method based on multi-parameter modeling and vibration signal spectrum analysis is proposed. First, the structured and unstructured data from the wind farm online monitoring system, point inspection system, monitoring system and other systems are collected, and the multi-source data are pre-processed and effectively fused according to the equipment characteristics and application system requirements. Then an early warning model is established based on multiple parameters, and the trend analysis of the equipment status data is realized based on the output of the early warning model and the vibration signal spectrum analysis. Finally, a system is designed and developed to display equipment warning information and fault diagnosis results with operation and maintenance decision suggestions. The wind farm main equipment early warning diagnosis system provides a new idea for intelligent online monitoring of wind turbines, which will effectively realize early warning of equipment failure, reduce the failure rate of equipment, and improve the efficiency of equipment maintenance personnel.
ZHANG Junjun,CHEN Guo,LU Yingqiang等. Design and development of wind farm main equipment early warning diagnosis system[J]. Electrical Engineering, 2023, 24(5): 52-57.
2023, Vol. 24 
