基于改进多胞形观测器的桨距执行器故障诊断

Fault Diagnosis of Pitch Actuator Using Improved Polytope Observer

针对非线性风力机系统故障诊断受到干扰、噪声影响的问题,设计改进多胞形未知输入观测器,实现桨距执行器的故障诊断.首先,基于风力机线性变参数模型,设计多胞形未知输入观测器实现干扰项的解耦;其次,考虑到噪声的影响,利用卡尔曼滤波器算法增强对噪声的鲁棒性;然后,采用均方根法设计阈值进行残差评估,从而确定故障发生与否.最后,通过风力机桨距执行器系统故障残差信号的仿真,验证改进多胞形未知输入观测器的性能.

We investigate the fault diagnosis of nonlinear wind-turbine systems with disturbance and noise, and design an improved polytope unknown input observer to diagnose faults in the pitch actuator. First, to decouple the interference term, we design a polytope unknown input observer based on a linear variable parameter model of the wind turbine. Next, considering the influence of noise, we use a Kalman filter algorithm to enhance robustness to noise. Then, we used the mean square method to design a threshold for evaluating the residual, which detemines whether or not a fault occurs. Lastly, we verify the performance of the improved polytope hull-type unknown input observer by simulating the fault residual signal of the wind-turbine pitch-actuator system.