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Volumn 13 E, Issue 3, 2008, Pages 318-322

Dynamic Bayesian network based prognosis in machining processes

Author keywords

Dynamic Bayesian network (DBN); Prognosis; Remaining useful life

Indexed keywords

DISTRIBUTED PARAMETER NETWORKS; INFERENCE ENGINES; INTELLIGENT NETWORKS; MACHINING; MAINTENANCE; SIGNAL FILTERING AND PREDICTION; SPEECH ANALYSIS;

EID: 47549119341     PISSN: 10071172     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12204-008-0318-y     Document Type: Article
Times cited : (24)

References (11)
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  • 2
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    • A review on machinery diagnostics and prognostics implementing condition-based maintenance
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    • (2006) Mechanical Systems and Signal Processing , vol.20 , Issue.6 , pp. 1483-1510
    • Jardine, A.K.S.1    Lin, D.M.2    Banjevic, D.3
  • 3
    • 2442473405 scopus 로고    scopus 로고
    • On-line parameter estimation for a failure-prone system subject to condition monitoring
    • Lin D, Markis V. On-line parameter estimation for a failure-prone system subject to condition monitoring [J]. Journal of Applied Probability, 2004, 41 (1): 211-220.
    • (2004) Journal of Applied Probability , vol.41 , Issue.1 , pp. 211-220
    • Lin, D.1    Markis, V.2
  • 6
    • 2442430480 scopus 로고    scopus 로고
    • Utilising statistical Residual life estimates of bearings to quantify the influence of preventive maintenance actions
    • Volk P J, Wnek M, Zygmunt M. Utilising statistical Residual life estimates of bearings to quantify the influence of preventive maintenance actions [J]. Mechanical Systems and Signal Processing, 2004, 18 (4): 833-847.
    • (2004) Mechanical Systems and Signal Processing , vol.18 , Issue.4 , pp. 833-847
    • Volk, P.J.1    Wnek, M.2    Zygmunt, M.3
  • 7
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    • A prognostic algorithm for machine performance assessment and its application
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  • 8
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    • HMMs for diagnostics and prognostics in machining processes
    • Baruah P, Chinnam R B. HMMs for diagnostics and prognostics in machining processes [J]. International Journal of Production Research, 2005, 43 (6): 1275-1293.
    • (2005) International Journal of Production Research , vol.43 , Issue.6 , pp. 1275-1293
    • Baruah, P.1    Chinnam, R.B.2
  • 10
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    • Dynamic bayesian networks: Representation, inference and learning
    • Berkeley: University of California
    • Murphy K P. Dynamic bayesian networks: representation, inference and learning [D]. Berkeley: University of California, 2002.
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    • Murphy, K.P.1
  • 11
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    • Bayes net toolbox
    • Murphy K P. Bayes net toolbox [EB/OL]. http://www.ai.mit.edu/murphyk/Software/BNT/bnt.html, 2003.
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    • Murphy, K.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.