基于风力发电系统的风电机组变桨距故障诊断

Faults Diagnosis of Wind Turbine Pitch System Based on ANFIS

在对风电机组变浆矩故障诊断优化的研究中,为了解决风电机组变桨距系统故障诊断中的非线性和建模困难的问题,提出了一种采用自适应神经模糊推理系统(ANFIS)的故障诊断方法,并详细论述了上述故障诊断方法的构造原理。以含有非线性项的变桨距系统为研究对象,以风电机组SCADA系统数据为基础,通过构造ANFIS故障诊断模型来拟合风速、桨距角、电机转速、功率输出与风电机组运行状态之间的规律,实现故障诊断的自适应。仿真结果表明,改进方法为变桨距故障诊断提供了准确可靠的决策依据。

In order to solve the nonlinear and difficult modeling problem in pitch system, a fault diagnosis method based on adaptive neuron fuzzy inference system （ANFIS） is proposed. This method sets the pitch system as the re- search object, and is based on data from the SCADA system. By constructing ANFIS fault diagnosis models to fit the law in the wind speed, pitch angle, motor speed, the power output, and the wind turbine operating status, this meth- od realizes adaptive fault diagnosis. The simulation results demonstrate that the proposed approach can supply the ac- curate and reliable decision-making support in the fault diagnosis.