Fast Sparsity-Assisted Signal Decomposition With Nonconvex Enhancement for Bearing Fault Diagnosis

Sparsity-assisted signal decomposition (SASD) based on morphological component analysis (MCA) for bearing fault diagnosis has been studied in-depth. However, existing algorithms often use different combinations of representation dictionaries and priors, leading to difficult dictionary choice and hig...

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Vydané v:	IEEE/ASME transactions on mechatronics Ročník 27; číslo 4; s. 2333 - 2344
Hlavní autori:	Zhao, Zhibin, Wang, Shibin, Wong, David, Wang, Wendong, Yan, Ruqiang, Chen, Xuefeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive algorithms Algorithms Complexity Computational complexity Computational modeling Convex optimization Convexity Decomposition Dictionaries Discrimination enhanced fault diagnosis Fault diagnosis morphological component analysis Morphology Parameters Signal resolution Sparsity sparsity-assisted signal decomposition Time-domain analysis Time-frequency analysis
ISSN:	1083-4435, 1941-014X
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