Enlightened by ASTFA method, adaptive sparsest narrow-band decomposition (ASNBD)
method is proposed in this paper. In ASNBD method, an optimized filter must be established …

Adaptive sparsest narrow‐band decomposition (ASNBD) method is proposed based on
matching pursuit (MP) and empirical mode decomposition (EMD). ASNBD obtains the local …

Sparse decomposition is a novel method for the fault diagnosis of rolling element bearing,
whether the construction of dictionary model is good or not will directly affect the results of …

Enlightened by empirical mode decomposition (EMD) and matching pursuit (MP), adaptive
sparsest narrow-band decomposition (ASNBD) method is proposed in this paper. The main …

Group-sparse mode decomposition (GSMD) is a decomposition method designed based on
the group sparse property of signals in frequency domain. It is proved to be highly efficient …

As the key rotating parts in machinery, it is crucial to extract the latent fault features of rolling
bearing in machinery condition monitoring to avoid the occurrence of sudden accidents …

Aiming at the problem that the vibration signals of rolling bearings working in a harsh
environment are mixed with many harmonic components and noise signals, while the …

A sparse squared envelope is crucial for efficient and accurate diagnosis of bearing faults.
Blind deconvolution (BD) is a well-established sparse feature enhancement method for the …

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis
has drawn considerable attention. In terms of the rich information hidden in fault vibration …

Sparsity-assisted signal decomposition (SASD) based on morphological component
analysis (MCA) for bearing fault diagnosis has been studied in-depth. However, existing …