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Volumn 28, Issue 8, 2007, Pages 2379-2386

A Naïve-Bayes classifier for damage detection in engineering materials

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DAMAGE DETECTION; FEATURE EXTRACTION;

EID: 34249093069     PISSN: 02613069     EISSN: 18734197     Source Type: Journal    
DOI: 10.1016/j.matdes.2006.07.018     Document Type: Article
Times cited : (55)

References (14)
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    • Structural health monitoring in composite materials using frequency response methods
    • Kessler S., Spearing S., Atalla M., Cesnika E., and Soutisb C. Structural health monitoring in composite materials using frequency response methods. Compos B 33 (2002) 87-95
    • (2002) Compos B , vol.33 , pp. 87-95
    • Kessler, S.1    Spearing, S.2    Atalla, M.3    Cesnika, E.4    Soutisb, C.5
  • 2
    • 8644219580 scopus 로고    scopus 로고
    • Detection of operational abnormality of ball bearing with ultrasonic technique
    • Takeuchi A. Detection of operational abnormality of ball bearing with ultrasonic technique. Eng Mater 270-273 (2004) 252-257
    • (2004) Eng Mater , vol.270-273 , pp. 252-257
    • Takeuchi, A.1
  • 3
    • 84903325739 scopus 로고    scopus 로고
    • Dempsey PJ, Certo JM, Morales W, Current status of hybrid bearing damage detection. In: Annual meeting and exhibition sponsored by the Society of tribologists and lubrication engineers, Toronto, Canada; 2004.
  • 5
    • 84903325741 scopus 로고    scopus 로고
    • S. Hall, The effective management and use of structural health data. In: Proceedings of the 2nd international workshop on structural health monitoring; 1999. p. 265-75.
  • 6
    • 13844315810 scopus 로고    scopus 로고
    • Neural network method based on a new damage signature for structural health monitoring
    • Shenfang Y., Lei W., and Ge P. Neural network method based on a new damage signature for structural health monitoring. Thin-walled Struct 43 (2005) 553-563
    • (2005) Thin-walled Struct , vol.43 , pp. 553-563
    • Shenfang, Y.1    Lei, W.2    Ge, P.3
  • 7
    • 8844253104 scopus 로고    scopus 로고
    • Artificial neural network based delamination prediction in laminated composites
    • Chakraborty D. Artificial neural network based delamination prediction in laminated composites. Mater Des 26 (2004) 1-7
    • (2004) Mater Des , vol.26 , pp. 1-7
    • Chakraborty, D.1
  • 8
    • 4143055740 scopus 로고    scopus 로고
    • Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithm
    • Su Z., and Ye L. Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithm. Compos Struct 66 (2004) 627637
    • (2004) Compos Struct , vol.66 , pp. 627637
    • Su, Z.1    Ye, L.2
  • 11
    • 84903325742 scopus 로고    scopus 로고
    • D. Heckerman, A tutorial on learning with bayesian networks, Microsoft Research Technical Report; 1995.
  • 12
    • 84903325743 scopus 로고    scopus 로고
    • Tabaszewski M, Cempel C. Available from: www.sidanet.org.
  • 13
    • 0035360461 scopus 로고    scopus 로고
    • Damage identification using support vector machines
    • Worden K., and Lane A. Damage identification using support vector machines. Smart Mater Struct 10 (2001) 540547
    • (2001) Smart Mater Struct , vol.10 , pp. 540547
    • Worden, K.1    Lane, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.