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Abstract:
Structural safety monitoring system uses an array of sensors to continuously monitor a structure to provide an early indication of problems such as damage to the structure from fatigue, corrosion or impact. The system is a large sensor network containing about two hundred nodes, each of which contains multiple sensors. So the sensor fault diagnosis is getting more and more important. A fuzzy-neural method is suggested in this paper. Based on the function equivalence between T-S fuzzy inference and RBF network, a kind of fuzzy neural controller based on RBF network with full-net structure is put forward. This paper proposes a real code GA to optimize all factors including scaling factors, membership functions and fuzzy rules. The RBF network with two inputs-one output model is used as fuzzy controller, the result of the simulation illustrates that the controller has good dynamic performance and strong robust.
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Source :
MACHINERY, MATERIALS SCIENCE AND ENERGY ENGINEERING
Year: 2015
Page: 633-641
Language: English
Cited Count:
WoS CC Cited Count: 0
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ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 0