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Volumn 25, Issue 19, 2014, Pages 2634-2641

Fault diagnosis of rolling bearings based on DLMD sample entropy and fuzzy clustering

Author keywords

Differential local mean decomposition(DLMD); Fault diagnosis; Fuzzy clustering; Rolling bearing; Sample entropy

Indexed keywords


EID: 84908116018     PISSN: 1004132X     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1004-132X.2014.19.015     Document Type: Article
Times cited : (7)

References (11)
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  • 2
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  • 4
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  • 7
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    • The Local Mean Decomposition and Its Application to EEG Perception Data
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  • 8
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    • Feature Extraction of Rolling Element Bearing Fault Using Wavelet Packet Sample Entropy
    • Su Wensheng, Wang Fengtao, Zhu Hong, et al. Feature Extraction of Rolling Element Bearing Fault Using Wavelet Packet Sample Entropy [J]. Journal of Vibration, Measurement & Diagnosis, 2011, 31(2):162-166.
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  • 9
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  • 10
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    • Fault Diagnosis of Roller Bearing Based on EMD and Fuzzy Cluster
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  • 11
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.