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Volumn 6, Issue , 2010, Pages 567-570

A fault diagnosis method for power transformer using Bayesian data analysis

Author keywords

Bayesian probability density theory; Fault diagnosis; Transformers

Indexed keywords

BAYESIAN DATA ANALYSIS; BAYESIAN PROBABILITIES; CONDITION BASED MAINTENANCE; EQUIPMENT FAULT DIAGNOSIS; FAULT DIAGNOSIS; FAULT DIAGNOSIS METHOD; FAULT MONITORING; MAINTENANCE COST; MEMBERSHIP PROBABILITY; NORMAL STATE; TEMPERATURE INFORMATION; TRANSFORMER FAULT DIAGNOSIS; TRANSFORMERS; WORKING TEMPERATURES;

EID: 77958539175     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCSIT.2010.5564983     Document Type: Conference Paper
Times cited : (5)

References (7)
  • 1
    • 77958589875 scopus 로고    scopus 로고
    • General introduction to condition maintenance technique and on-line monitoring of equipment
    • Zhou Zhimin, General introduction to condition maintenance technique and on-line monitoring of equipment, High Voltage Apparatus, 2002, 38(5):42-45.
    • (2002) High Voltage Apparatus , vol.38 , Issue.5 , pp. 42-45
    • Zhou, Z.1
  • 2
    • 78149284596 scopus 로고    scopus 로고
    • A fault diagnosis method for industrial gas turbines using bayesian data analysis
    • Lee Young K., Mavris Dimitri N., Volovoi Vitali V., Yuan Ming, Fisher Ted, A fault diagnosis method for industrial gas turbines using Bayesian data analysis, J. Engineering for gas turbines and power, 2010, 132(4):041602-041607.
    • (2010) J. Engineering for Gas Turbines and Power , vol.132 , Issue.4 , pp. 041602-041607
    • Lee, Y.K.1    Mavris, D.N.2    Volovoi, V.V.3    Yuan, M.4    Fisher, T.5
  • 3
    • 33645765255 scopus 로고    scopus 로고
    • Bayesian network approach for gas path fault diagnosis
    • Romessis C. Mathioudakis K. Bayesian network approach for gas path fault diagnosis, J. Engineering for gas turbines 570 and power, 2006, 128(1):64-72.
    • (2006) J. Engineering for Gas Turbines 570 and Power , vol.128 , Issue.1 , pp. 64-72
    • Romessis, C.M.K.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.