Improved cyclostationary analysis method based on TKEO and its application on the faults diagnosis of induction motors

Zuolu Wang; Jie Yang; Haiyang Li; Dong Zhen; Fengshou Gu; Andrew Ball

doi:10.1016/j.isatra.2021.10.026

Improved cyclostationary analysis method based on TKEO and its application on the faults diagnosis of induction motors

ISA Trans. 2022 Sep;128(Pt A):513-530. doi: 10.1016/j.isatra.2021.10.026. Epub 2021 Oct 27.

Authors

Zuolu Wang¹, Jie Yang², Haiyang Li³, Dong Zhen⁴, Fengshou Gu³, Andrew Ball³

Affiliations

¹ Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, PR China; Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, HD1 3DH, UK.
² Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, PR China.
³ Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, HD1 3DH, UK.
⁴ Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, PR China. Electronic address: d.zhen@hebut.edu.cn.

PMID: 34743919
DOI: 10.1016/j.isatra.2021.10.026

Abstract

Cyclostationary analysis has been strongly recognized as an effective demodulation tool in identifying fault features of rotating machinery based on vibration signature analysis. This study improves two current mature cyclostationary approaches, cyclic modulation spectrum (CMS) and fast spectral correlation (Fast-SC), combined with the novel frequency-domain application of Teager Kaiser energy operator (TKEO). They can enhance fault feature identification with the lower computational burden. Firstly, the raw vibration signal is transformed into the time-frequency domain through the short-time Fourier transform (STFT) to realize the conversion of the multi-carrier signal to a multiple signal-carrier signal. Secondly, the TKEO is utilized to enhance the fault feature by taking full advantage of demodulating the mono-component. Finally, the spectral coherence and enhanced envelope spectrum (EES) are calculated to effectively exhibit fault features. The superiority of the proposed methods is successfully validated by the simulation study and diagnosing the broken rotor bar (BRB) and bearing outer race faults of induction motors (IMs) under various operating conditions.

Keywords: Cyclic modulation spectrum; Cyclostationarity; Enhanced envelope spectrum; Fast spectral correlation; Induction motors; Teager Kaiser energy operator.