关键词: 故障预测, 可拓聚类, 物元, 可拓理论, 人工智能

Abstract: In view of the complexity?of running status?and?the uncertainty of health?diagnosis, the fault prediction method of the large complex?equipment is studied. A fault prediction model based on extension clustering algorithm is put forward. In these models, the running status and the diagnostic data are described formalized?and modeled by matter element?model. Using the correlation functions of extension theory, the qualitative?and?quantitative?prediction analysis method of the equipments state is studied. Based on these, a rapid?prediction?of fault states?of complex equipment is achieved, and it provides?a support to the?computer aided design of?the equipment fault prediction. An example is provided to prove its feasibility and validity.

Key words: fault prediction, extension clustering algorithm, matter element, extension theory, aritificial intellegence