A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform

被引:66
|
作者
Luo, Jiesi [1 ,2 ]
Yu, Dejie [3 ]
Liang, Ming [2 ]
机构
[1] Xiamen Univ Technol, Dept Mech Engn, Xiamen 361024, Peoples R China
[2] Univ Ottawa, Dept Mech Engn, Ottawa, ON K1N 6N5, Canada
[3] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China
基金
加拿大自然科学与工程研究理事会; 美国国家科学基金会;
关键词
adaptive demodulation; kurtosis; tunable-Q wavelet transform; bearings; fault detection; SPECTRAL KURTOSIS; DIAGNOSTICS;
D O I
10.1088/0957-0233/24/5/055009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents an adaptive demodulation technique for bearing fault detection. It is implemented via the tunable-Q wavelet transform (TQWT). With the TQWT, the bearing vibration signal is decomposed into sub-signals corresponding to different band-pass filters of the TQWT. Kurtosis as an effective indicator of signal impulsiveness is adopted to guide the merging of the sub-signals leading to a signal component which contains information most relevant to the bearing fault. The purpose of the proposed approach is to adaptively search for the best filter for envelope demodulation analysis. In fact, the implementation of the proposed method can be interpreted as the process to obtain the optimal filter for the Hilbert demodulation analysis by two steps of merging of the band-pass filters of the TQWT. The effectiveness of the proposed method has been demonstrated by both simulation and experimental analyses.
引用
收藏
页数:11
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