基于非线性状态估计算法的风机设备故障预警模型研究  

作　　者：张劲戈 

机构地区：[1]英飞同仁风机股份有限公司,上海201806

出　　处：《科技创新与应用》2025年第7期67-70,共4页Technology Innovation and Application

摘　　要：该文提出一种基于非线性状态估计算法(NSET)的风机设备故障预警模型。该模型通过实时监测与分析风电机组的关键参数数据,利用NSET算法进行状态估计,并通过预测值与实际值之间的残差判断设备的健康状况。研究结果表明,该模型能够提前预警潜在故障,有效降低设备停机时长,提高风电场的运行效率和经济效益。此外,模型还具备自适应调整能力,能够随着系统状态的变化动态更新,从而提升故障预警的准确性和可靠性。This paper proposes a wind turbine equipment fault early warning model based on nonlinear state estimation algorithm(NSET).The model monitors and analyzes key parameter data of wind turbines in real time,uses NSET algorithm to estimate state,and judges the health status of the equipment through the residual error between the predicted value and the actual value.Research results show that the model can warn potential faults in advance,effectively reduce equipment downtime,and improve the operating efficiency and economic benefits of the wind farm.In addition,the model also has adaptive adjustment capabilities and can be dynamically updated as the system state changes,thereby improving the accuracy and reliability of fault warning.

关 键 词：非线性状态估计 风机设备 故障预警模型 残差分析 风电场 

分 类 号：TM315[电气工程—电机]