摘要
采用最小二乘法RLS自适应滤波算法对鼠笼式异步电动机定子侧电流信号进行自适应滤波,以滤除电流信号中的噪声干扰,再经过50 Hz的极窄带陷波器消除工频分量对断条特征分量的干扰,并在傅里叶频谱上实现断条的检测。实验证明,采用自适应滤波算法与极窄带陷波器相结合的方法,很好地解决了噪声对定子侧电流信号的干扰,能够实现鼠笼式异步电动机断条分量的识别。
The method of RLS Algorithmic proposed is used to process noise of induction motor stator current. The extremely narrowband notch filter was used to deal subsidence with broken rotor bar signal. It can eliminate interference from power frequency component to frequency component of broken rotor bar and achieve precise identification to frequency component of broken rotor bar fi＇om FFT. Results show： the noise problem of stator current was solved by auto-adapted filter algorithm and extremely narrowband notch filter, which is good solution method can detect broken rotor bar frequency of induction motor stator current.
出处
《煤矿机械》
北大核心
2011年第8期258-260,共3页
Coal Mine Machinery
基金
河南省高校科技创新人才支持计划项目(2008HASTIT022)
河南省控制工程重点学科开放实验室开发基金项目(KG2009-10)
关键词
RLS算法
转子断条
故障诊断
least-square algorithm
fault diagnosis
broken rotor bar
