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• W2353638624 abstract "To improve the efficiency of fault diagnosis,a fault diagnosis system based on rough set was put forward.For a high-power diesel engine,the fault characteristics were extracted with the time-frequency analysis and wavelet packet energy spectrum analysis method.By comparison and analysis,it was decided that the latter extracted characteristics,which had better sensitivity and stability,were optimized with rough set.Finally,the fault modes were categorized with neural network.The results show that the characteristics extracted by wavelet packet energy spectrum method have better sensitivity and stability.With rough set,the characteristic attributes are simplified,which reduces the input nodes of neural network.Accordingly,the accuracy of fault classification improves." @default.
• W2353638624 created "2016-06-24" @default.
• W2353638624 creator A5007252640 @default.
• W2353638624 date "2010-01-01" @default.
• W2353638624 modified "2023-09-28" @default.
• W2353638624 title "Characteristic Optimization and Diesel Engine Fault Diagnosis Based on Rough Set" @default.
• W2353638624 hasPublicationYear "2010" @default.
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