摘要
双馈异步发电机定子绕组发生不对称故障时,会在转子电流信号中引发一定的谐波分量。由于早期故障引起的故障特征信号十分微弱,如何准确提取故障特征量已经成为一个很重要的课题。本文在动模实验室进行了双馈机定子绕组故障模拟实验,获取了正常及定子绕组不对称故障情况下的转子电流信号,然后采用傅里叶变换、小波变换、希尔伯特-黄变换(HHT)三种方法提取其故障特征量,进行灵敏度与可靠性的比较。通过对比可知,希尔伯特-黄变换提取出的故障特征量比傅里叶变换及小波变换的特征量更加敏感、可靠。
Asymmetric faults of doubly-fed wind power generator stator winding cause the harmonic component in the signal of rotor current. How to accurately extract fault feature has become a very important taskdue to the weak fault signal of early failure. This paper built the experimental platform of stator faults diagnosis in laboratory. The rotor current was derived in both normal and stator fault conditions, then the Fouriertransform, wavelet transform, Hilbert-Huang transform were used to extract the fault feature. By comparingthe sensitivity and reliability, fault feature of Hilbert-Huang transform is more sensitive, reliable than theFourier transform and wavelet transform.
出处
《微电机》
北大核心
2014年第5期66-70,共5页
Micromotors
基金
国家自然科学基金项目(51177039)
教育部博士点基金项目(20090944110011)
关键词
双馈异步发电机
故障检测
实验平台
转子电流
希尔伯特-黄变换
double-fed induction generator
fault diagnosis
experimental platform
rotor current
Hilbert-Huang transform
