海上风电机组发电机轴承异常状态监测研究  

Research on Abnormal State Monitoring of Generator Bearing of Offshore Wind Turbine

作　　者：柯福惠 KE Fuhui(Longyuan Pingtan Wind Power Generation Co.,Ltd.,Fuzhou 350000)

机构地区：[1]龙源平潭风力发电有限公司,福州350000

出　　处：《现代制造技术与装备》2025年第2期172-174,共3页Modern Manufacturing Technology and Equipment

摘　　要：海上风电机组面临着复杂且严苛的运行环境,当负载突然变化时,轴承振动特征变化,导致异常状态监测难度加大。为此,研究海上风电机组发电机轴承异常状态监测方法。首先,通过振动传感器捕捉发电机轴承出现异常状态时的特征振动频率并进行数据归一化,构成参数集合。其次,利用大数据运算求得低维空间的决策函数和最优超平面,提升判断准确性。最后,判定轴承异常状态参数类别,实现轴承异常状态监测。实验结果表明,所提方法的监测精度可快速趋近于1,且测试损失最终稳定在一个相对较低的水平,充分证实了该方法精准度高。Offshore wind turbines are faced with a complex and harsh operating environment,when the load changes suddenly,the bearing vibration characteristics change,resulting in abnormal state monitoring is very difficult.Therefore,the monitoring method of abnormal bearing condition of offshore wind turbine generator is studied.The characteristic vibration frequency of generator bearing in abnormal state is captured by vibration sensor and the data is normalized to form a parameter set.The decision function and the optimal hyperplane of low dimensional space are obtained by big data operation to improve the judgment accuracy.Finally,the classification of bearing abnormal state parameters is determined to realize bearing abnormal state monitoring.The experimental results show that the monitoring accuracy of the proposed method can quickly approach 1,and the test loss finally stabilizes at a relatively low level,which fully confirms the high accuracy of the method.

关 键 词：发电机轴承 异常状态监测 海上风电机组 特征参数 

分 类 号：G63[文化科学—教育学]