Mar 11, 2022 · Abstract: The effective separation of fault characteristic components is the core of compound fault diagnosis of rolling bearings.

(1) A novel MDSRCFD method based on optimized MCKD and sparse representation is proposed for rolling bearings. (2) The AFS with the global search capability and ...

Deng et al [24] proposed a composite fault diagnosis method based on optimal maximum correlation kurtosis deconvolution (MCKD) and sparse representation. Lyu et ...

Periodicity weighted Kurtosis is proposed to evaluate repetitive impulse. •. Adaptive sparse denoising model detects compound faults in rolling bearing.

Mar 11, 2022 · The effective separation of fault characteristic components is the core of compound fault diagnosis of rolling bearings.

W Deng, Z Li, X Li, et al. Compound fault diagnosis using optimized MCKD and sparse representation for rolling bearings[J]. IEEE Transactions on ...

Jan 19, 2024 · First, the adaptive multi-strategy cuckoo search algorithm (MSACS) is used to iteratively optimize the important parameters of MCKD. Second, the ...

Compound faults diagnosis method of rolling bearing based on sparse representation ... Combined MCKD-Teager energy operator with LSTM for rolling bearing fault ...

Sep 7, 2022 · Firstly, the acoustic signal of bearing compound faults is decomposed by AVMD to generate several modal components, and the optimal modal ...

Summary: This article proposes a novel compound fault diagnosis method MDSRCFD based on optimized MCKD and sparse representation, which separates and extracts ...