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Volumn 36, Issue 5, 2003, Pages 813-818

Combining AI, FDI, and statistical hypothesis-testing in a framework for diagnosis

Author keywords

AI methods; Fault diagnosis; Fault isolation; FDI methods; Multiple faults; Noise

Indexed keywords

ELECTRIC FAULT CURRENTS; FAILURE ANALYSIS; PLANT MANAGEMENT; STATISTICAL TESTS;

EID: 84974651407     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/S1474-6670(17)36593-X     Document Type: Conference Paper
Times cited : (35)

References (9)
  • 3
    • 0035452382 scopus 로고    scopus 로고
    • A minimal polynomial basis solution to residual generation for fault diagnosis in linear systems
    • E. Frisk, and M. Nyberg A minimal polynomial basis solution to residual generation for fault diagnosis in linear systems. Automatica 37 2001 1417 1424
    • (2001) Automatica , vol.37 , pp. 1417-1424
    • Frisk, E.1    Nyberg, M.2
  • 4
    • 0025403582 scopus 로고
    • A new structural framework for parity equation-based failure detecation and isolation
    • J. Gertler, and D. Singer A new structural framework for parity equation-based failure detecation and isolation. Automatica 26 2 1990 381 388
    • (1990) Automatica , vol.26 , Issue.2 , pp. 381-388
    • Gertler, J.1    Singer, D.2
  • 8
    • 0036714934 scopus 로고    scopus 로고
    • Model-based diagnosis of an automotive engine using several types of fault models
    • M. Nyberg Model-based diagnosis of an automotive engine using several types of fault models. IEEE Transactions on Control Systems Technology 10 5 2002 679 689
    • (2002) IEEE Transactions on Control Systems Technology , vol.10 , Issue.5 , pp. 679-689
    • Nyberg, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.