Application of Adaptive MOMEDA with Iterative Autocorrelation to Enhance Weak Features of Hoist Bearings

Low-speed hoist bearings are characterized by fault features that are weak and difficult to extract. Multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is an effective method for extracting periodic pulses in a signal. However, the decomposition effect of MOMEDA largely depends on th...

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Váldodahkkit:	Tengyu Li, Ziming Kou, Juan Wu, Fen Yang
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	MDPI AG 2021-06-01
Ráidu:	Entropy
Fáttát:	low-speed hoist bearing weak feature extraction iterative autocorrelation autocorrelation kurtosis entropy multipoint optimal minimum entropy deconvolution adjusted
Liŋkkat:	https://www.mdpi.com/1099-4300/23/7/789
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