张 磊,李欣竹.基于ANFIS的风力发电机状态监测研究[J].中南民族大学学报自然科学版,2017,(1):92-95,137
基于ANFIS的风力发电机状态监测研究
The Reserch of Wind Turbine Condition Monitoring Based on ANFIS
  
DOI:
中文关键词: 风力发电机  状态检测  自适应神经模糊推理系统
英文关键词: wind turbine  condition monitoring  ANFIS
基金项目:河北省自然科学基金资助项目(F2015202231)
作者单位
张 磊,李欣竹* 河北工业大学 控制科学与工程学院天津 300130 
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中文摘要:
      针对风力发电机系统故障诊断中非线性和建模困难的问题,提出了一种风力发电机状态监测方法,利用 从风力发电机的 SCADA 数据中挖掘出20种输入输出对应关系,分别建立了自适应模糊神经推理系统(ANFIS)模 型,并给出了一种基于预测误差的概率分布函数的适用于所有模型的异常检测方法.使用20个模型单独进行状态 诊断,得出诊断正确率,综合使用20个模型的状态诊断结果,得到了最终的判定结论,仿真结果表明:该方法能准 确地诊断出风力发电机系统故障.
英文摘要:
      With the continuous development of wind power industry, the number of installed wind power generator isincreasing. Due to its complicated structure and poor working conditions, easily happened all kinds of faults. For the nonlinear problems and difficulty in modeling of wind turbine system fault diagnosis , this paper proposes a wind turbine monitoring system, using 20 different SCADA normal data developed 20 adaptive fuzzy neural inference system ( ANFIS) model, and proposes a kind of can apply to all models of anomaly detection method, using the prediction error to evaluate the practicability of model in a simulated SCADA signal, comprehensive 20 anomaly detection results of the model, get the final decision to the conclusion that the simulation results show that the system can accurately diagnose the wind turbine system fault.
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