DOI: 10.3390/s24030951 ISSN: 1424-8220

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

Fengxia He, Chuansheng Zheng, Chao Pang, Chengying Zhao, Mingyang Yang, Yunpeng Zhu, Zhong Luo, Haitao Luo, Lei Li, Haotian Jiang
  • Electrical and Electronic Engineering
  • Biochemistry
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Analytical Chemistry

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.

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