A Rolling Bearing Fault Classification Scheme Based on k-Optimized Adaptive Local Iterative Filterin...
A Rolling Bearing Fault Classification Scheme Based on k-Optimized Adaptive Local Iterative Filtering and Improved Multiscale Permutation Entropy
About this item
Full title
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
The health condition of the rolling bearing seriously affects the operation of the whole mechanical system. When the rolling bearing parts fail, the time series collected in the field generally shows strong nonlinearity and non-stationarity. To obtain the faulty characteristics of mechanical equipment accurately, a rolling bearing fault detection t...
Alternative Titles
Full title
A Rolling Bearing Fault Classification Scheme Based on k-Optimized Adaptive Local Iterative Filtering and Improved Multiscale Permutation Entropy
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TN_cdi_doaj_primary_oai_doaj_org_article_c19d50ace67a4126ba82eef2e77c101b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c19d50ace67a4126ba82eef2e77c101b
Other Identifiers
ISSN
1099-4300
E-ISSN
1099-4300
DOI
10.3390/e23020191
