摘要
针对风电场环境恶劣,设备故障早期监测难且机组故障率高的问题,提出一种基于多参量建模与振动信号频谱分析的风电场主设备预警诊断方法。首先,采集风电场在线监测系统、点巡检系统、监控系统及其他系统中的结构化和非结构化数据,并根据设备特点和应用系统要求,对多源数据进行预处理和有效融合;然后,基于多参量建立预警模型,并通过预警模型输出与振动信号频谱分析实现对设备状态数据的趋势分析;最后,设计并开发预警诊断系统,展示设备预警信息、故障诊断结果与运维决策建议。风电场主设备预警诊断系统为风电机组智能在线监测提供了一种新思路,可实现设备故障提前预警,降低机组故障率,提高设备维护人员的工作效率。
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.
作者
张军军
陈果
卢应强
乔苏朋
胡忠忠
ZHANG Junjun;CHEN Guo;LU Yingqiang;QIAO Supeng;HU Zhongzhong(Guodian Nanjing Automation Co.,Ltd,Nanjing 211106)
出处
《电气技术》
2023年第5期52-57,共6页
Electrical Engineering
关键词
风电场
风力发电
多参量建模
预警诊断
在线监测
wind farm
wind power generation
multi-parameter modeling
early warning diagnosis
online monitoring
作者简介
张军军(1994-),男,硕士,工程师,主要从事电气设备在线监测与预警诊断智能化技术研究工作。
