基于PSO-ADMMF和WPE的发电机转子匝间短路故障诊断

Fault Diagnosis for Rotor Inter-turn Short Circuit Based on PSO-ADMMF and Wavelet Packet Entropy

针对常规的数学形态滤波器对定子电流信号滤波效果不理想,提出粒子群算法改进的数学形态滤波器。引用粒子群算法寻找最优的数学形态滤波器中开-闭和闭-开运算的权系数,建立自适应数学形态滤波器模型,对定子电流信号进行滤波处理。结合小波包理论和信息熵理论,提出小波包熵作为故障特征的故障诊断方法。仿真实验对比了PSO算法改进的自适应数学形态滤波器和常规数学形态滤波器的滤波效果,计算了滤波后的不同状态信号的小波包熵,并以此进行了转子匝间短路故障诊断,仿真验证表明本方法是有效的。

Rotor inter-turn short circuit fault is hard to be diagnosed because mathematical morphology fil-ter process stator current is not ideal.The method of PSO-adaptive mathematical morphology filtering is used to wipe out the noise interference.Firstly,the best weight coefficient of open-close and close-open op-eration is found by using PSO,and the best de-noise mathematical morphology filtering is built.Secondly, a fault diagnosis method of taking the wavelet packet entropy as a fault character is proposed combined with wavelet packet analysis and information entropy .Finally,the filtering effectiveness of the de-noise result of PSO-ADMMF and that of the conventional mathematical morphology are compared,and the wavelet entropy after de-noise is figured out.The result shows that the method is useful and effective.