[关键词]
[摘要]
针对受状态延时影响的风机变桨系统故障诊断,提出了一种基于多新息随机梯度(MISG)的故障诊断方法。该方法将复杂系统转化为状态空间模型,并建立系统辨识模型。将新息标量扩展成新息向量改善算法精度,利用系统发生故障引起参数改变的特征,算法对风机状态延时变桨系统完成参数估计,将系统故障诊断问题转换为系统辨识问题。仿真所得结果验证该方法可以达到诊断风机状态延时变桨系统故障的目的。
[Key word]
[Abstract]
Aiming at fault diagnosis of wind turbine pitch system affected by state delay, a new fault diagnosis method based on multiinnovation stochastic gradient algorithm was proposed. This complex system was modeled as a state space model, and the system identification model was established. The algorithm extended the innovation scalar into innovation vector to improve the accuracy. The changes of parameters could be caused by the fault of the system, and the algorithm was used to estimate the parameters of wind turbine pitch system with state delay. The fault diagnosis issue was transformed into identification problem. Simulation results showed that this method could achieve the purpose of diagnosing the fault of wind turbine pitch system with state delay.
[中图分类号]
TM 315
[基金项目]
国家自然科学基金项目(61374136,61473159);上海市人才发展资金项目(201511)