Fault diagnosis of complex system based on Bayesian networks

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS

Volumn 10, Issue 2, 2004, Pages 230-234

  Wang, Hua Wei ^a   Zhou, Jing Lun ^a   He, Zu Yu ^b   Sha, Ji Chang ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Bayesian networks; Complex system; Fault diagnosis; Information fusion

Indexed keywords

COMPUTATIONAL COMPLEXITY; DECISION MAKING; FAILURE ANALYSIS; MATHEMATICAL MODELS; NEURAL NETWORKS; PROBABILITY;

BAYESIAN NETWORKS; FAULT DIAGNOSIS; INFORMATION FUSION; LEAK NOISE OR MODELS; SMALL SAMPLES;

LARGE SCALE SYSTEMS;

EID: 2942572061     PISSN: 10065911     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. XU Zhangsui, FANG Liqing, WANG Xiwu, ZUO Xianzhang. Diagnosis principle and application for the fault Information [M]. Beijing: National Defence Industry Press, 2000 (in Chinese)
2. WU Jinpei. Intelligent fault diagnosis and neural networks [M]. Beijing: Science Press, 1997 (in Chinese).
3. PORTINALE L. Behavioral petri-nets: a model for diagnostic knowledge representing and reasoning [J]. IEEE Transactions on System, Man and Cybernetics - Part B: Cybernetics, 1997, 27(2): 184-195.
4. Inien SYU, LANG S D. Adapting a diagnostic problem-solving model to information retrieval [J]. Information Processing and Management, 2000, 36: 313-330.
5. FU Jun, HE Wei, ZHANG Hongcai, et al. A study of fault diagnosis based on Bayesian networks [J]. Journal of Shanghai Maritime University, 2001, 22(3): 68-71, 77.
6. BREESE J S, HECKERMAN D. Decision-theoretic case-based reasoning [J]. IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans, 1996, 26(6): 838-842.
7. RAKAR A, JURICIC D, BALLE P. Transferable belief model in fault diagnosis [J]. Engineering Applications of Artificial Intelligence, 1999, 12: 555-567.
8. HAHLL G. Combing disparate sources of information in the safety assessment of software-based system [J]. Nuclear Engine and Design, 2000, 195: 307-319.
9. MUSSI S. Diagnostic expert systems: a method for engineering knowledge used in sequential diagnosis [J]. Expert Systems, 2000, 17(4): 199-211.
10. PEARL J. Probabilistic reasoning in intelligent systems: networks of plausible inference [M]. San Mateo, CA: Morgan Kaufmann, 1988.
11. NEAPOLITAN R E. Probabilistic reasoning in expert systems [M]. New York: Wiley, 1990.
12. ONISKOA, DRUZDZEL M J, WAYSYLUK H. Learning bayesian network parameters from data sets: application of Noisy-OR Gates [J]. International Journal of Approximation Reasoning, 2001, 27: 165-182.
13. ZHANG Yulin, WU Jianjun. Liquid rocket engine health monitoring technology [M]. Changsha: National University of Defense Technology Press, 1998 (in Chinese).