基于区间预测的风力机桨距执行器LPV故障诊断

针对风力机桨距系统故障导致的桨距角输出变化的问题，在建立风力机桨距系统线性参数变化(Linear Parameter Vary, LPV)模型的基础上，提出了基于区间预测方法的故障诊断方法。首先，以液油含量为调度变量，将风力机桨距系统非线性模型转化为LPV模型，使模型更加精确。其次，考虑到模型不确定性描述的边界问题，引入区间预测算法，根据桨距角输出是否处于区间预测输出上下限内判断故障发生与否。最后，将所提出的算法在风力机系统中进行仿真。仿真结果表明，所提出的算法能够很好地估计出桨距执行器故障，提高了故障诊断的鲁棒性。

LPV fault diagnosis of wind turbine pitch actuator based on interval prediction

In light of the problem that the pitch angle output changes caused by the pitch system faults of the wind turbine, an inverter predictor approach is proposed to diagnose the fault of the pitch actuator based on the Linear Parameter Vary (LPV) model of pitch system of the wind turbine. Firstly, the hydraulic pressure is selected as the scheduling variable and the nonlinear model of pitch system of the wind turbine is transformed into LPV model, making the model more precise. Secondly, considering the boundary problem described by model uncertainties, the interval prediction algorithm is introduced. Then the fault is judged according to whether the output of the pitch angle is in the range upper and lower bound. Finally, the proposed algorithm is simulated in the wind turbine system. The simulation results show that the proposed algorithm can estimate the pitch actuator fault well and the robustness of the fault diagnosis is improved. This work is supported by National Natural Science Foundation of China (No. 61572237).