CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis
CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Contents
Due to the complex operating environment of valves, when a fault occurs inside a valve, the vibration signal generated by the fault is easily affected by the environmental noise, making the extraction of fault features difficult. To address this problem, this paper proposes a feature extraction method based on the combination of Complete Ensemble E...
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Full title
CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis
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TN_cdi_doaj_primary_oai_doaj_org_article_a5d6ccfd91c14fa0b8e4a441a33263d6
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a5d6ccfd91c14fa0b8e4a441a33263d6
Other Identifiers
ISSN
1999-4893
E-ISSN
1999-4893
DOI
10.3390/a18030148
