An Adaptive Deconvolution Method with Improve Enhanced Envelope Spectrum and Its Application for Bearing Fault Feature Extraction

被引:2
|
作者
He, Fengxia [1 ]
Zheng, Chuansheng [1 ]
Pang, Chao [2 ]
Zhao, Chengying [1 ]
Yang, Mingyang [2 ]
Zhu, Yunpeng [3 ]
Luo, Zhong [2 ]
Luo, Haitao [4 ]
Li, Lei [2 ]
Jiang, Haotian [5 ]
机构
[1] Shenyang Jianzhu Univ, Sch Mech Engn, Shenyang 110168, Peoples R China
[2] Northeastern Univ, Sch Mech Engn & Automat, Shenyang 110819, Peoples R China
[3] Queen Mary Univ London, Sch Engn & Mat Sci, London E1 4NS, England
[4] Chinese Acad Sci, Shenyang Inst Automat, Key Lab Robot, Shenyang 110016, Peoples R China
[5] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
关键词
bearing faults; fault separation; IES-CYCBD; complex faults; fault diagnosis; FAST COMPUTATION; DIAGNOSTICS; VIBRATION; DEMODULATION; ALGORITHM; BAND;
D O I
10.3390/s24030951
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
To address the problem that complex bearing faults are coupled to each other, and the difficulty of diagnosis increases, an improved envelope spectrum-maximum second-order cyclostationary blind deconvolution (IES-CYCBD) method is proposed to realize the separation of vibration signal fault features. The improved envelope spectrum (IES) is obtained by integrating the part of the frequency axis containing resonance bands in the cyclic spectral coherence function. The resonant bands corresponding to different fault types are accurately located, and the IES with more prominent target characteristic frequency components are separated. Then, a simulation is carried out to prove the ability of this method, which can accurately separate and diagnose fault types under high noise and compound fault conditions. Finally, a compound bearing fault experiment with inner and outer ring faults is designed, and the inner and outer ring fault characteristics are successfully separated by the proposed IES-CYCBD method. Therefore, simulation and experiments demonstrate the strong capability of the proposed method for complex fault separation and diagnosis.
引用
收藏
页数:22
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