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- W2363567265 abstract "In fault diagnosis, there are not one to one definite relations between the fault reasons and the fault symptoms with relatively high information redundancy. We always try to decrease redundance of diagnostic information by reduction. In this paper, we propose a method based on VPRS model and neural network is applied to fault diagnosis of rotating machinery, where the aim is to solve fault features extraction and diagnostic rules acquisition." @default.
- W2363567265 created "2016-06-24" @default.
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- W2363567265 date "2008-01-01" @default.
- W2363567265 modified "2023-09-23" @default.
- W2363567265 title "Rotating Machinery Fault Diagnosis Based on VPRS and Neural Network" @default.
- W2363567265 hasPublicationYear "2008" @default.
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