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- W2364490017 abstract "Considering the fuzzy and coupling characteristics of fault diagnosis for hydroelectric generating sets,this paper proposed a vibration fault on-line diagnosis method based on fuzzy neural networks(FNN).At first,fractal dimension was applied to extracting structure feature of shaft orbit,which reflectd vibration state of rotor,to realize figure quantification for on-line recognition of FNN.Aiming at six typical vibration faults,including shaft orbit,four categories in all fourteen fault symptoms were summarized,their fuzzy attributes were analyzed and the corresponding fuzzifications were described.Then a six-layer FNN was established to express fuzzy inference from symptom to fault,and its learning algorithm was provided to modify network parameter.By self-learning,FNN could guarantee a higher precision of the on-line diagnosis.The analytical results of cases verify the feasibility of the diagnosis system based on FNN." @default.
- W2364490017 created "2016-06-24" @default.
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- W2364490017 date "2007-01-01" @default.
- W2364490017 modified "2023-09-23" @default.
- W2364490017 title "Vibration fault on-line diagnosis of hydroelectric generating sets based on fractal theory and fuzzy neural networks" @default.
- W2364490017 hasPublicationYear "2007" @default.
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