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Volumn 237 LNEE, Issue , 2014, Pages 161-167

Application of Twin Support Vector Machine for fault diagnosis of rolling bearing

Author keywords

Fault diagnosis; Nonparallel plane; Rolling bearing; TWSVM

Indexed keywords

FAILURE ANALYSIS; ROLLER BEARINGS; SUPPORT VECTOR MACHINES;

EID: 84893808798     PISSN: 18761100     EISSN: 18761119     Source Type: Book Series    
DOI: 10.1007/978-3-319-01273-5_17     Document Type: Conference Paper
Times cited : (4)

References (9)
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  • 3
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  • 4
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    • Twin support vector machines for pattern classification
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    • Jayadeva, K.R.1    Chandra, S.2
  • 6
    • 84857646348 scopus 로고    scopus 로고
    • Training twin support vector regression via linear programming
    • Zhong P, Xu YT, Zhao YH (2012) Training twin support vector regression via linear programming. Neural Comput Appl 21(2):399-407
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  • 7
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    • IMS, University of Cincinnati, NASA Ames Prognostics Data Repository, NASA Ames, Moffett Field
    • Lee J, Qiu H, Yu G, Lin J (2007) Rexnord Technical Services, ?Bearing Data Set?, IMS, University of Cincinnati, NASA Ames Prognostics Data Repository, http://ti.arc.nasa.gov/project/prognostics-data-repository, NASA Ames, Moffett Field
    • (2007) Rexnord Technical Services, ?Bearing Data Set?
    • Lee, J.1    Qiu, H.2    Yu, G.3    Lin, J.4
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    • Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
    • Qiu H, Lee J, Lin J, Yu G (2006) Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics. J Sound Vib 289:1066-1090
    • (2006) J Sound Vib , vol.289 , pp. 1066-1090
    • Qiu, H.1    Lee, J.2    Lin, J.3    Yu, G.4
  • 9
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    • Application of relevance vector machine and logistic regression for machine degradation assessment
    • Caesarendra W, Widodo A, Yang BS (2010) Application of relevance vector machine and logistic regression for machine degradation assessment. Mech Syst Signal Process 24:1161-1171
    • (2010) Mech Syst Signal Process , vol.24 , pp. 1161-1171
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.