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- W2393598316 abstract "Rolling bearing is the important part of mechanical drive system, and its fault rate is very high that affect the equipment operation directly. A fault diagnosis method of rolling bearing based on fuzzy entropy of LMD and PNN is proposed. The vibration signal of rolling bearing is decomposed into7 PF components adaptively, and for each PF, the fuzzy entropy is extracted by setting fuzzy function.Feature quantization of each PF is realized, and PNN is used to identify fault status. The experiment results show that the fault identify rate used this method reaches 86.25%, and it is an effective method of rolling bearing fault diagnosis." @default.
- W2393598316 created "2016-06-24" @default.
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- W2393598316 date "2015-01-01" @default.
- W2393598316 modified "2023-09-25" @default.
- W2393598316 title "Fault Diagnosis of Rolling Bearing Based on Fuzzy Entropy of LMD and PNN" @default.
- W2393598316 hasPublicationYear "2015" @default.
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