Title :
Novel Adaptive Filter Method and Application in Broken Rotor Bar Fault Diagnosis of Induction Motor
Author :
Wang Xin ; Zhao Zhike
Author_Institution :
Sch. of Electr. Eng. & Autom., Henan Polytech. Univ., Jiaozuo, China
Abstract :
To improve the fault diagnosis accuracy of the broken rotor bar (BRB) of the squirrel-cage induction motor, a novel fault diagnosis method of the BRB based on the adaptive notch filter (ANF) and the Hilbert-huang transform (HHT) was proposed. The stator current signal of the squirrel-cage induction motor was used to detect the feature of the BRB. The ANF was used to deal subsidence with the BRB signal. It can eliminate the interference from the power frequency component to the frequency component of the BRB and achieve the precise identification to the frequency component of the BRB in the special marginal spectrum of the HHT. Experiments show that the combination of the ANF and the HHT can achieve the precise location to the frequency component of the BRB and also avoid the mode alias phenomenon from the HHT.
Keywords :
Hilbert transforms; adaptive filters; fault diagnosis; induction motors; notch filters; rotors; squirrel cage motors; stators; Hilbert-Huang transform; adaptive notch filter; broken rotor bar fault diagnosis; mode alias phenomenon; power frequency component; special marginal spectrum; squirrel-cage induction motor; stator current signal; Adaptive filters; Fault diagnosis; Frequency measurement; Induction motors; Rotors; Spectral analysis; Transforms; Adaptive Notch Filter; Broken Rotor Bar; Fault Diagnosis; Hilbert-Huang Transformation;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2011 Second International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-1-4577-0755-1
Electronic_ISBN :
978-0-7695-4455-7
DOI :
10.1109/ICDMA.2011.191